Serverless
OpenShift Serverless installation, usage, and release notes
Abstract
Chapter 1. Release notes
For additional information about the OpenShift Serverless life cycle and supported platforms, refer to the Platform Life Cycle Policy.
Release notes contain information about new and deprecated features, breaking changes, and known issues. The following release notes apply for the most recent OpenShift Serverless releases on OpenShift Container Platform.
For an overview of OpenShift Serverless functionality, see About OpenShift Serverless.
OpenShift Serverless is based on the open source Knative project.
For details about the latest Knative component releases, see the Knative blog.
1.1. About API versions
API versions are an important measure of the development status of certain features and custom resources in OpenShift Serverless. Creating resources on your cluster that do not use the correct API version can cause issues in your deployment.
The OpenShift Serverless Operator automatically upgrades older resources that use deprecated versions of APIs to use the latest version. For example, if you have created resources on your cluster that use older versions of the ApiServerSource
API, such as v1beta1
, the OpenShift Serverless Operator automatically updates these resources to use the v1
version of the API when this is available and the v1beta1
version is deprecated.
After they have been deprecated, older versions of APIs might be removed in any upcoming release. Using deprecated versions of APIs does not cause resources to fail. However, if you try to use a version of an API that has been removed, it will cause resources to fail. Ensure that your manifests are updated to use the latest version to avoid issues.
1.2. Generally Available and Technology Preview features
Features which are Generally Available (GA) are fully supported and are suitable for production use. Technology Preview (TP) features are experimental features and are not intended for production use. See the Technology Preview scope of support on the Red Hat Customer Portal for more information about TP features.
The following table provides information about which OpenShift Serverless features are GA and which are TP:
Feature | 1.26 | 1.27 | 1.28 |
---|---|---|---|
| GA | GA | GA |
Quarkus functions | GA | GA | GA |
Node.js functions | TP | TP | GA |
TypeScript functions | TP | TP | GA |
Python functions | - | - | TP |
Service Mesh mTLS | GA | GA | GA |
| GA | GA | GA |
HTTPS redirection | GA | GA | GA |
Kafka broker | GA | GA | GA |
Kafka sink | GA | GA | GA |
Init containers support for Knative services | GA | GA | GA |
PVC support for Knative services | GA | GA | GA |
TLS for internal traffic | TP | TP | TP |
Namespace-scoped brokers | - | TP | TP |
| - | - | TP |
1.3. Deprecated and removed features
Some features that were Generally Available (GA) or a Technology Preview (TP) in previous releases have been deprecated or removed. Deprecated functionality is still included in OpenShift Serverless and continues to be supported; however, it will be removed in a future release of this product and is not recommended for new deployments.
For the most recent list of major functionality deprecated and removed within OpenShift Serverless, refer to the following table:
Feature | 1.20 | 1.21 | 1.22 to 1.26 | 1.27 | 1.28 |
---|---|---|---|---|---|
| Deprecated | Deprecated | Removed | Removed | Removed |
| Deprecated | Removed | Removed | Removed | Removed |
Serving and Eventing | - | - | - | Deprecated | Deprecated |
| - | - | - | - | Deprecated |
1.4. Release notes for Red Hat OpenShift Serverless 1.28
OpenShift Serverless 1.28 is now available. New features, changes, and known issues that pertain to OpenShift Serverless on OpenShift Container Platform are included in this topic.
1.4.1. New features
- OpenShift Serverless now uses Knative Serving 1.7.
- OpenShift Serverless now uses Knative Eventing 1.7.
- OpenShift Serverless now uses Kourier 1.7.
-
OpenShift Serverless now uses Knative (
kn
) CLI 1.7. - OpenShift Serverless now uses Knative Kafka 1.7.
-
The
kn func
CLI plug-in now usesfunc
1.9.1 version. - Node.js and TypeScript runtimes for OpenShift Serverless Functions are now Generally Available (GA).
- Python runtime for OpenShift Serverless Functions is now available as a Technology Preview.
- Multi-container support for Knative Serving is now available as a Technology Preview. This feature allows you to use a single Knative service to deploy a multi-container pod.
In OpenShift Serverless 1.29 or later, the following components of Knative Eventing will be scaled down from two pods to one:
-
imc-controller
-
imc-dispatcher
-
mt-broker-controller
-
mt-broker-filter
-
mt-broker-ingress
-
The
serverless.openshift.io/enable-secret-informer-filtering
annotation for the Serving CR is now deprecated. The annotation is valid only for Istio, and not for Kourier.With OpenShift Serverless 1.28, the OpenShift Serverless Operator allows injecting the environment variable
ENABLE_SECRET_INFORMER_FILTERING_BY_CERT_UID
for bothnet-istio
andnet-kourier
.If you enable secret filtering, all of your secrets need to be labeled with
networking.internal.knative.dev/certificate-uid: "<id>"
. Otherwise, Knative Serving does not detect them, which leads to failures. You must label both new and existing secrets.In one of the following OpenShift Serverless releases, secret filtering will become enabled by default. To prevent failures, label your secrets in advance.
1.4.2. Known issues
Currently, runtimes for Python are not supported for OpenShift Serverless Functions on IBM Power, IBM zSystems, and IBM® LinuxONE.
Node.js, TypeScript, and Quarkus functions are supported on these architectures.
On the Windows platform, Python functions cannot be locally built, run, or deployed using the Source-to-Image builder due to the
app.sh
file permissions.To work around this problem, use the Windows Subsystem for Linux.
1.5. Release notes for Red Hat OpenShift Serverless 1.27
OpenShift Serverless 1.27 is now available. New features, changes, and known issues that pertain to OpenShift Serverless on OpenShift Container Platform are included in this topic.
OpenShift Serverless 1.26 is the earliest release that is fully supported on OpenShift Container Platform 4.12. OpenShift Serverless 1.25 and older does not deploy on OpenShift Container Platform 4.12.
For this reason, before upgrading OpenShift Container Platform to version 4.12, first upgrade OpenShift Serverless to version 1.26 or 1.27.
1.5.1. New features
- OpenShift Serverless now uses Knative Serving 1.6.
- OpenShift Serverless now uses Knative Eventing 1.6.
- OpenShift Serverless now uses Kourier 1.6.
-
OpenShift Serverless now uses Knative (
kn
) CLI 1.6. - OpenShift Serverless now uses Knative Kafka 1.6.
-
The
kn func
CLI plug-in now usesfunc
1.8.1. - Namespace-scoped brokers are now available as a Technology Preview. Such brokers can be used, for instance, to implement role-based access control (RBAC) policies.
-
KafkaSink
now uses theCloudEvent
binary content mode by default. The binary content mode is more efficient than the structured mode because it uses headers in its body instead of aCloudEvent
. For example, for the HTTP protocol, it uses HTTP headers. - You can now use the gRPC framework over the HTTP/2 protocol for external traffic using the OpenShift Route on OpenShift Container Platform 4.10 and later. This improves efficiency and speed of the communications between the client and server.
-
API version
v1alpha1
of the Knative Operator Serving and Eventings CRDs is deprecated in 1.27. It will be removed in future versions. Red Hat strongly recommends to use thev1beta1
version instead. This does not affect the existing installations, because CRDs are updated automatically when upgrading the Serverless Operator. - The delivery timeout feature is now enabled by default. It allows you to specify the timeout for each sent HTTP request. The feature remains a Technology Preview.
1.5.2. Fixed issues
-
Previously, Knative services sometimes did not get into the
Ready
state, reporting waiting for the load balancer to be ready. This issue has been fixed.
1.5.3. Known issues
-
Integrating OpenShift Serverless with Red Hat OpenShift Service Mesh causes the
net-kourier
pod to run out of memory on startup when too many secrets are present on the cluster. Namespace-scoped brokers might leave
ClusterRoleBindings
in the user namespace even after deletion of namespace-scoped brokers.If this happens, delete the
ClusterRoleBinding
namedrbac-proxy-reviews-prom-rb-knative-kafka-broker-data-plane-{{.Namespace}}
in the user namespace.If you use
net-istio
for Ingress and enable mTLS via SMCP usingsecurity.dataPlane.mtls: true
, Service Mesh deploysDestinationRules
for the*.local
host, which does not allowDomainMapping
for OpenShift Serverless.To work around this issue, enable mTLS by deploying
PeerAuthentication
instead of usingsecurity.dataPlane.mtls: true
.
1.6. Release notes for Red Hat OpenShift Serverless 1.26
OpenShift Serverless 1.26 is now available. New features, changes, and known issues that pertain to OpenShift Serverless on OpenShift Container Platform are included in this topic.
1.6.1. New features
- OpenShift Serverless Functions with Quarkus is now GA.
- OpenShift Serverless now uses Knative Serving 1.5.
- OpenShift Serverless now uses Knative Eventing 1.5.
- OpenShift Serverless now uses Kourier 1.5.
-
OpenShift Serverless now uses Knative (
kn
) CLI 1.5. - OpenShift Serverless now uses Knative Kafka 1.5.
- OpenShift Serverless now uses Knative Operator 1.3.
-
The
kn func
CLI plugin now usesfunc
1.8.1. - Persistent volume claims (PVCs) are now GA. PVCs provide permanent data storage for your Knative services.
The new trigger filters feature is now available as a Developer Preview. It allows users to specify a set of filter expressions, where each expression evaluates to either true or false for each event.
To enable new trigger filters, add the
new-trigger-filters: enabled
entry in the section of theKnativeEventing
type in the operator config map:apiVersion: operator.knative.dev/v1beta1 kind: KnativeEventing ... ... spec: config: features: new-trigger-filters: enabled ...
Knative Operator 1.3 adds the updated
v1beta1
version of the API foroperator.knative.dev
.To update from
v1alpha1
tov1beta1
in yourKnativeServing
andKnativeEventing
custom resource config maps, edit theapiVersion
key:Example
KnativeServing
custom resource config mapapiVersion: operator.knative.dev/v1beta1 kind: KnativeServing ...
Example
KnativeEventing
custom resource config mapapiVersion: operator.knative.dev/v1beta1 kind: KnativeEventing ...
1.6.2. Fixed issues
- Previously, Federal Information Processing Standards (FIPS) mode was disabled for Kafka broker, Kafka source, and Kafka sink. This has been fixed, and FIPS mode is now available.
1.6.3. Known issues
If you use
net-istio
for Ingress and enable mTLS via SMCP usingsecurity.dataPlane.mtls: true
, Service Mesh deploysDestinationRules
for the*.local
host, which does not allowDomainMapping
for OpenShift Serverless.To work around this issue, enable mTLS by deploying
PeerAuthentication
instead of usingsecurity.dataPlane.mtls: true
.
Additional resources
1.7. Release notes for Red Hat OpenShift Serverless 1.25.0
OpenShift Serverless 1.25.0 is now available. New features, changes, and known issues that pertain to OpenShift Serverless on OpenShift Container Platform are included in this topic.
1.7.1. New features
- OpenShift Serverless now uses Knative Serving 1.4.
- OpenShift Serverless now uses Knative Eventing 1.4.
- OpenShift Serverless now uses Kourier 1.4.
-
OpenShift Serverless now uses Knative (
kn
) CLI 1.4. - OpenShift Serverless now uses Knative Kafka 1.4.
-
The
kn func
CLI plugin now usesfunc
1.7.0. - Integrated development environment (IDE) plugins for creating and deploying functions are now available for Visual Studio Code and IntelliJ.
Knative Kafka broker is now GA. Knative Kafka broker is a highly performant implementation of the Knative broker API, directly targeting Apache Kafka.
It is recommended to not use the MT-Channel-Broker, but the Knative Kafka broker instead.
-
Knative Kafka sink is now GA. A
KafkaSink
takes aCloudEvent
and sends it to an Apache Kafka topic. Events can be specified in either structured or binary content modes. - Enabling TLS for internal traffic is now available as a Technology Preview.
1.7.2. Fixed issues
- Previously, Knative Serving had an issue where the readiness probe failed if the container was restarted after a liveness probe fail. This issue has been fixed.
1.7.3. Known issues
- The Federal Information Processing Standards (FIPS) mode is disabled for Kafka broker, Kafka source, and Kafka sink.
-
The
SinkBinding
object does not support custom revision names for services. The Knative Serving Controller pod adds a new informer to watch secrets in the cluster. The informer includes the secrets in the cache, which increases memory consumption of the controller pod.
If the pod runs out of memory, you can work around the issue by increasing the memory limit for the deployment.
If you use
net-istio
for Ingress and enable mTLS via SMCP usingsecurity.dataPlane.mtls: true
, Service Mesh deploysDestinationRules
for the*.local
host, which does not allowDomainMapping
for OpenShift Serverless.To work around this issue, enable mTLS by deploying
PeerAuthentication
instead of usingsecurity.dataPlane.mtls: true
.
Additional resources
1.8. Release notes for Red Hat OpenShift Serverless 1.24.0
OpenShift Serverless 1.24.0 is now available. New features, changes, and known issues that pertain to OpenShift Serverless on OpenShift Container Platform are included in this topic.
1.8.1. New features
- OpenShift Serverless now uses Knative Serving 1.3.
- OpenShift Serverless now uses Knative Eventing 1.3.
- OpenShift Serverless now uses Kourier 1.3.
-
OpenShift Serverless now uses Knative
kn
CLI 1.3. - OpenShift Serverless now uses Knative Kafka 1.3.
-
The
kn func
CLI plugin now usesfunc
0.24. - Init containers support for Knative services is now generally available (GA).
- OpenShift Serverless logic is now available as a Developer Preview. It enables defining declarative workflow models for managing serverless applications.
- You can now use the cost management service with OpenShift Serverless.
1.8.2. Fixed issues
Integrating OpenShift Serverless with Red Hat OpenShift Service Mesh causes the
net-istio-controller
pod to run out of memory on startup when too many secrets are present on the cluster.It is now possible to enable secret filtering, which causes
net-istio-controller
to consider only secrets with anetworking.internal.knative.dev/certificate-uid
label, thus reducing the amount of memory needed.- The OpenShift Serverless Functions Technology Preview now uses Cloud Native Buildpacks by default to build container images.
1.8.3. Known issues
- The Federal Information Processing Standards (FIPS) mode is disabled for Kafka broker, Kafka source, and Kafka sink.
In OpenShift Serverless 1.23, support for KafkaBindings and the
kafka-binding
webhook were removed. However, an existingkafkabindings.webhook.kafka.sources.knative.dev MutatingWebhookConfiguration
might remain, pointing to thekafka-source-webhook
service, which no longer exists.For certain specifications of KafkaBindings on the cluster,
kafkabindings.webhook.kafka.sources.knative.dev MutatingWebhookConfiguration
might be configured to pass any create and update events to various resources, such as Deployments, Knative Services, or Jobs, through the webhook, which would then fail.To work around this issue, manually delete
kafkabindings.webhook.kafka.sources.knative.dev MutatingWebhookConfiguration
from the cluster after upgrading to OpenShift Serverless 1.23:$ oc delete mutatingwebhookconfiguration kafkabindings.webhook.kafka.sources.knative.dev
If you use
net-istio
for Ingress and enable mTLS via SMCP usingsecurity.dataPlane.mtls: true
, Service Mesh deploysDestinationRules
for the*.local
host, which does not allowDomainMapping
for OpenShift Serverless.To work around this issue, enable mTLS by deploying
PeerAuthentication
instead of usingsecurity.dataPlane.mtls: true
.
1.9. Release notes for Red Hat OpenShift Serverless 1.23.0
OpenShift Serverless 1.23.0 is now available. New features, changes, and known issues that pertain to OpenShift Serverless on OpenShift Container Platform are included in this topic.
1.9.1. New features
- OpenShift Serverless now uses Knative Serving 1.2.
- OpenShift Serverless now uses Knative Eventing 1.2.
- OpenShift Serverless now uses Kourier 1.2.
-
OpenShift Serverless now uses Knative (
kn
) CLI 1.2. - OpenShift Serverless now uses Knative Kafka 1.2.
-
The
kn func
CLI plugin now usesfunc
0.24. -
It is now possible to use the
kafka.eventing.knative.dev/external.topic
annotation with the Kafka broker. This annotation makes it possible to use an existing externally managed topic instead of the broker creating its own internal topic. -
The
kafka-ch-controller
andkafka-webhook
Kafka components no longer exist. These components have been replaced by thekafka-webhook-eventing
component. - The OpenShift Serverless Functions Technology Preview now uses Source-to-Image (S2I) by default to build container images.
1.9.2. Known issues
- The Federal Information Processing Standards (FIPS) mode is disabled for Kafka broker, Kafka source, and Kafka sink.
-
If you delete a namespace that includes a Kafka broker, the namespace finalizer may fail to be removed if the broker’s
auth.secret.ref.name
secret is deleted before the broker. Running OpenShift Serverless with a large number of Knative services can cause Knative activator pods to run close to their default memory limits of 600MB. These pods might be restarted if memory consumption reaches this limit. Requests and limits for the activator deployment can be configured by modifying the
KnativeServing
custom resource:apiVersion: operator.knative.dev/v1beta1 kind: KnativeServing metadata: name: knative-serving namespace: knative-serving spec: deployments: - name: activator resources: - container: activator requests: cpu: 300m memory: 60Mi limits: cpu: 1000m memory: 1000Mi
-
If you are using Cloud Native Buildpacks as the local build strategy for a function,
kn func
is unable to automatically start podman or use an SSH tunnel to a remote daemon. The workaround for these issues is to have a Docker or podman daemon already running on the local development computer before deploying a function. - On-cluster function builds currently fail for Quarkus and Golang runtimes. They work correctly for Node, Typescript, Python, and Springboot runtimes.
If you use
net-istio
for Ingress and enable mTLS via SMCP usingsecurity.dataPlane.mtls: true
, Service Mesh deploysDestinationRules
for the*.local
host, which does not allowDomainMapping
for OpenShift Serverless.To work around this issue, enable mTLS by deploying
PeerAuthentication
instead of usingsecurity.dataPlane.mtls: true
.
Additional resources
1.10. Release notes for Red Hat OpenShift Serverless 1.22.0
OpenShift Serverless 1.22.0 is now available. New features, changes, and known issues that pertain to OpenShift Serverless on OpenShift Container Platform are included in this topic.
1.10.1. New features
- OpenShift Serverless now uses Knative Serving 1.1.
- OpenShift Serverless now uses Knative Eventing 1.1.
- OpenShift Serverless now uses Kourier 1.1.
-
OpenShift Serverless now uses Knative (
kn
) CLI 1.1. - OpenShift Serverless now uses Knative Kafka 1.1.
-
The
kn func
CLI plugin now usesfunc
0.23. - Init containers support for Knative services is now available as a Technology Preview.
- Persistent volume claim (PVC) support for Knative services is now available as a Technology Preview.
-
The
knative-serving
,knative-serving-ingress
,knative-eventing
andknative-kafka
system namespaces now have theknative.openshift.io/part-of: "openshift-serverless"
label by default. - The Knative Eventing - Kafka Broker/Trigger dashboard has been added, which allows visualizing Kafka broker and trigger metrics in the web console.
- The Knative Eventing - KafkaSink dashboard has been added, which allows visualizing KafkaSink metrics in the web console.
- The Knative Eventing - Broker/Trigger dashboard is now called Knative Eventing - Channel-based Broker/Trigger.
-
The
knative.openshift.io/part-of: "openshift-serverless"
label has substituted theknative.openshift.io/system-namespace
label. -
Naming style in Knative Serving YAML configuration files changed from camel case (
ExampleName
) to hyphen style (example-name
). Beginning with this release, use the hyphen style notation when creating or editing Knative Serving YAML configuration files.
1.10.2. Known issues
- The Federal Information Processing Standards (FIPS) mode is disabled for Kafka broker, Kafka source, and Kafka sink.
1.11. Release notes for Red Hat OpenShift Serverless 1.21.0
OpenShift Serverless 1.21.0 is now available. New features, changes, and known issues that pertain to OpenShift Serverless on OpenShift Container Platform are included in this topic.
1.11.1. New features
- OpenShift Serverless now uses Knative Serving 1.0
- OpenShift Serverless now uses Knative Eventing 1.0.
- OpenShift Serverless now uses Kourier 1.0.
-
OpenShift Serverless now uses Knative (
kn
) CLI 1.0. - OpenShift Serverless now uses Knative Kafka 1.0.
-
The
kn func
CLI plugin now usesfunc
0.21. - The Kafka sink is now available as a Technology Preview.
-
The Knative open source project has begun to deprecate camel-cased configuration keys in favor of using kebab-cased keys consistently. As a result, the
defaultExternalScheme
key, previously mentioned in the OpenShift Serverless 1.18.0 release notes, is now deprecated and replaced by thedefault-external-scheme
key. Usage instructions for the key remain the same.
1.11.2. Fixed issues
-
In OpenShift Serverless 1.20.0, there was an event delivery issue affecting the use of
kn event send
to send events to a service. This issue is now fixed. -
In OpenShift Serverless 1.20.0 (
func
0.20), TypeScript functions created with thehttp
template failed to deploy on the cluster. This issue is now fixed. -
In OpenShift Serverless 1.20.0 (
func
0.20), deploying a function using thegcr.io
registry failed with an error. This issue is now fixed. -
In OpenShift Serverless 1.20.0 (
func
0.20), creating a Springboot function project directory with thekn func create
command and then running thekn func build
command failed with an error message. This issue is now fixed. -
In OpenShift Serverless 1.19.0 (
func
0.19), some runtimes were unable to build a function by using podman. This issue is now fixed.
1.11.3. Known issues
Currently, the domain mapping controller cannot process the URI of a broker, which contains a path that is currently not supported.
This means that, if you want to use a
DomainMapping
custom resource (CR) to map a custom domain to a broker, you must configure theDomainMapping
CR with the broker’s ingress service, and append the exact path of the broker to the custom domain:Example
DomainMapping
CRapiVersion: serving.knative.dev/v1alpha1 kind: DomainMapping metadata: name: <domain-name> namespace: knative-eventing spec: ref: name: broker-ingress kind: Service apiVersion: v1
The URI for the broker is then
<domain-name>/<broker-namespace>/<broker-name>
.
1.12. Release notes for Red Hat OpenShift Serverless 1.20.0
OpenShift Serverless 1.20.0 is now available. New features, changes, and known issues that pertain to OpenShift Serverless on OpenShift Container Platform are included in this topic.
1.12.1. New features
- OpenShift Serverless now uses Knative Serving 0.26.
- OpenShift Serverless now uses Knative Eventing 0.26.
- OpenShift Serverless now uses Kourier 0.26.
-
OpenShift Serverless now uses Knative (
kn
) CLI 0.26. - OpenShift Serverless now uses Knative Kafka 0.26.
-
The
kn func
CLI plugin now usesfunc
0.20. The Kafka broker is now available as a Technology Preview.
ImportantThe Kafka broker, which is currently in Technology Preview, is not supported on FIPS.
-
The
kn event
plugin is now available as a Technology Preview. -
The
--min-scale
and--max-scale
flags for thekn service create
command have been deprecated. Use the--scale-min
and--scale-max
flags instead.
1.12.2. Known issues
OpenShift Serverless deploys Knative services with a default address that uses HTTPS. When sending an event to a resource inside the cluster, the sender does not have the cluster certificate authority (CA) configured. This causes event delivery to fail, unless the cluster uses globally accepted certificates.
For example, an event delivery to a publicly accessible address works:
$ kn event send --to-url https://ce-api.foo.example.com/
On the other hand, this delivery fails if the service uses a public address with an HTTPS certificate issued by a custom CA:
$ kn event send --to Service:serving.knative.dev/v1:event-display
Sending an event to other addressable objects, such as brokers or channels, is not affected by this issue and works as expected.
- The Kafka broker currently does not work on a cluster with Federal Information Processing Standards (FIPS) mode enabled.
If you create a Springboot function project directory with the
kn func create
command, subsequent running of thekn func build
command fails with this error message:[analyzer] no stack metadata found at path '' [analyzer] ERROR: failed to : set API for buildpack 'paketo-buildpacks/ca-certificates@3.0.2': buildpack API version '0.7' is incompatible with the lifecycle
As a workaround, you can change the
builder
property togcr.io/paketo-buildpacks/builder:base
in the function configuration filefunc.yaml
.Deploying a function using the
gcr.io
registry fails with this error message:Error: failed to get credentials: failed to verify credentials: status code: 404
As a workaround, use a different registry than
gcr.io
, such asquay.io
ordocker.io
.TypeScript functions created with the
http
template fail to deploy on the cluster.As a workaround, in the
func.yaml
file, replace the following section:buildEnvs: []
with this:
buildEnvs: - name: BP_NODE_RUN_SCRIPTS value: build
In
func
version 0.20, some runtimes might be unable to build a function by using podman. You might see an error message similar to the following:ERROR: failed to image: error during connect: Get "http://%2Fvar%2Frun%2Fdocker.sock/v1.40/info": EOF
The following workaround exists for this issue:
Update the podman service by adding
--time=0
to the serviceExecStart
definition:Example service configuration
ExecStart=/usr/bin/podman $LOGGING system service --time=0
Restart the podman service by running the following commands:
$ systemctl --user daemon-reload
$ systemctl restart --user podman.socket
Alternatively, you can expose the podman API by using TCP:
$ podman system service --time=0 tcp:127.0.0.1:5534 & export DOCKER_HOST=tcp://127.0.0.1:5534
1.13. Release notes for Red Hat OpenShift Serverless 1.19.0
OpenShift Serverless 1.19.0 is now available. New features, changes, and known issues that pertain to OpenShift Serverless on OpenShift Container Platform are included in this topic.
1.13.1. New features
- OpenShift Serverless now uses Knative Serving 0.25.
- OpenShift Serverless now uses Knative Eventing 0.25.
- OpenShift Serverless now uses Kourier 0.25.
-
OpenShift Serverless now uses Knative (
kn
) CLI 0.25. - OpenShift Serverless now uses Knative Kafka 0.25.
-
The
kn func
CLI plugin now usesfunc
0.19. -
The
KafkaBinding
API is deprecated in OpenShift Serverless 1.19.0 and will be removed in a future release. - HTTPS redirection is now supported and can be configured either globally for a cluster or per each Knative service.
1.13.2. Fixed issues
- In previous releases, the Kafka channel dispatcher waited only for the local commit to succeed before responding, which might have caused lost events in the case of an Apache Kafka node failure. The Kafka channel dispatcher now waits for all in-sync replicas to commit before responding.
1.13.3. Known issues
In
func
version 0.19, some runtimes might be unable to build a function by using podman. You might see an error message similar to the following:ERROR: failed to image: error during connect: Get "http://%2Fvar%2Frun%2Fdocker.sock/v1.40/info": EOF
The following workaround exists for this issue:
Update the podman service by adding
--time=0
to the serviceExecStart
definition:Example service configuration
ExecStart=/usr/bin/podman $LOGGING system service --time=0
Restart the podman service by running the following commands:
$ systemctl --user daemon-reload
$ systemctl restart --user podman.socket
Alternatively, you can expose the podman API by using TCP:
$ podman system service --time=0 tcp:127.0.0.1:5534 & export DOCKER_HOST=tcp://127.0.0.1:5534
1.14. Release notes for Red Hat OpenShift Serverless 1.18.0
OpenShift Serverless 1.18.0 is now available. New features, changes, and known issues that pertain to OpenShift Serverless on OpenShift Container Platform are included in this topic.
1.14.1. New features
- OpenShift Serverless now uses Knative Serving 0.24.0.
- OpenShift Serverless now uses Knative Eventing 0.24.0.
- OpenShift Serverless now uses Kourier 0.24.0.
-
OpenShift Serverless now uses Knative (
kn
) CLI 0.24.0. - OpenShift Serverless now uses Knative Kafka 0.24.7.
-
The
kn func
CLI plugin now usesfunc
0.18.0. In the upcoming OpenShift Serverless 1.19.0 release, the URL scheme of external routes will default to HTTPS for enhanced security.
If you do not want this change to apply for your workloads, you can override the default setting before upgrading to 1.19.0, by adding the following YAML to your
KnativeServing
custom resource (CR):... spec: config: network: defaultExternalScheme: "http" ...
If you want the change to apply in 1.18.0 already, add the following YAML:
... spec: config: network: defaultExternalScheme: "https" ...
In the upcoming OpenShift Serverless 1.19.0 release, the default service type by which the Kourier Gateway is exposed will be
ClusterIP
and notLoadBalancer
.If you do not want this change to apply to your workloads, you can override the default setting before upgrading to 1.19.0, by adding the following YAML to your
KnativeServing
custom resource (CR):... spec: ingress: kourier: service-type: LoadBalancer ...
-
You can now use
emptyDir
volumes with OpenShift Serverless. See the OpenShift Serverless documentation about Knative Serving for details. -
Rust templates are now available when you create a function using
kn func
.
1.14.2. Fixed issues
- The prior 1.4 version of Camel-K was not compatible with OpenShift Serverless 1.17.0. The issue in Camel-K has been fixed, and Camel-K version 1.4.1 can be used with OpenShift Serverless 1.17.0.
Previously, if you created a new subscription for a Kafka channel, or a new Kafka source, a delay was possible in the Kafka data plane becoming ready to dispatch messages after the newly created subscription or sink reported a ready status.
As a result, messages that were sent during the time when the data plane was not reporting a ready status, might not have been delivered to the subscriber or sink.
In OpenShift Serverless 1.18.0, the issue is fixed and the initial messages are no longer lost. For more information about the issue, see Knowledgebase Article #6343981.
1.14.3. Known issues
Older versions of the Knative
kn
CLI might use older versions of the Knative Serving and Knative Eventing APIs. For example, version 0.23.2 of thekn
CLI uses thev1alpha1
API version.On the other hand, newer releases of OpenShift Serverless might no longer support older API versions. For example, OpenShift Serverless 1.18.0 no longer supports version
v1alpha1
of thekafkasources.sources.knative.dev
API.Consequently, using an older version of the Knative
kn
CLI with a newer OpenShift Serverless might produce an error because thekn
cannot find the outdated API. For example, version 0.23.2 of thekn
CLI does not work with OpenShift Serverless 1.18.0.To avoid issues, use the latest
kn
CLI version available for your OpenShift Serverless release. For OpenShift Serverless 1.18.0, use Knativekn
CLI 0.24.0.
Chapter 2. About Serverless
2.1. OpenShift Serverless overview
OpenShift Serverless provides Kubernetes native building blocks that enable developers to create and deploy serverless, event-driven applications on OpenShift Container Platform. OpenShift Serverless is based on the open source Knative project, which provides portability and consistency for hybrid and multi-cloud environments by enabling an enterprise-grade serverless platform.
Because OpenShift Serverless releases on a different cadence from OpenShift Container Platform, the OpenShift Serverless documentation does not maintain separate documentation sets for minor versions of the product. The current documentation set applies to all currently supported versions of OpenShift Serverless unless version-specific limitations are called out in a particular topic or for a particular feature.
For additional information about the OpenShift Serverless life cycle and supported platforms, refer to the Platform Life Cycle Policy.
2.1.1. Additional resources
2.2. Knative Serving
Knative Serving supports developers who want to create, deploy, and manage cloud-native applications. It provides a set of objects as Kubernetes custom resource definitions (CRDs) that define and control the behavior of serverless workloads on an OpenShift Container Platform cluster.
Developers use these CRDs to create custom resource (CR) instances that can be used as building blocks to address complex use cases. For example:
- Rapidly deploying serverless containers.
- Automatically scaling pods.
2.2.1. Knative Serving resources
- Service
-
The
service.serving.knative.dev
CRD automatically manages the life cycle of your workload to ensure that the application is deployed and reachable through the network. It creates a route, a configuration, and a new revision for each change to a user created service, or custom resource. Most developer interactions in Knative are carried out by modifying services. - Revision
-
The
revision.serving.knative.dev
CRD is a point-in-time snapshot of the code and configuration for each modification made to the workload. Revisions are immutable objects and can be retained for as long as necessary. - Route
-
The
route.serving.knative.dev
CRD maps a network endpoint to one or more revisions. You can manage the traffic in several ways, including fractional traffic and named routes. - Configuration
-
The
configuration.serving.knative.dev
CRD maintains the desired state for your deployment. It provides a clean separation between code and configuration. Modifying a configuration creates a new revision.
2.3. Knative Eventing
Knative Eventing on OpenShift Container Platform enables developers to use an event-driven architecture with serverless applications. An event-driven architecture is based on the concept of decoupled relationships between event producers and event consumers.
Event producers create events, and event sinks, or consumers, receive events. Knative Eventing uses standard HTTP POST requests to send and receive events between event producers and sinks. These events conform to the CloudEvents specifications, which enables creating, parsing, sending, and receiving events in any programming language.
Knative Eventing supports the following use cases:
- Publish an event without creating a consumer
- You can send events to a broker as an HTTP POST, and use binding to decouple the destination configuration from your application that produces events.
- Consume an event without creating a publisher
- You can use a trigger to consume events from a broker based on event attributes. The application receives events as an HTTP POST.
To enable delivery to multiple types of sinks, Knative Eventing defines the following generic interfaces that can be implemented by multiple Kubernetes resources:
- Addressable resources
-
Able to receive and acknowledge an event delivered over HTTP to an address defined in the
status.address.url
field of the event. The KubernetesService
resource also satisfies the addressable interface. - Callable resources
-
Able to receive an event delivered over HTTP and transform it, returning
0
or1
new events in the HTTP response payload. These returned events may be further processed in the same way that events from an external event source are processed.
2.3.1. Using Knative Kafka
Knative Kafka provides integration options for you to use supported versions of the Apache Kafka message streaming platform with OpenShift Serverless. Kafka provides options for event source, channel, broker, and event sink capabilities.
Knative Kafka is not currently supported for IBM Z and IBM Power.
Knative Kafka provides additional options, such as:
- Kafka source
- Kafka channel
- Kafka broker
- Kafka sink
2.3.2. Additional resources
2.4. About OpenShift Serverless Functions
OpenShift Serverless Functions enables developers to create and deploy stateless, event-driven functions as a Knative service on OpenShift Container Platform. The kn func
CLI is provided as a plugin for the Knative kn
CLI. You can use the kn func
CLI to create, build, and deploy the container image as a Knative service on the cluster.
2.4.1. Included runtimes
OpenShift Serverless Functions provides templates that can be used to create basic functions for the following runtimes:
2.4.2. Next steps
Chapter 3. Installing Serverless
3.1. Preparing to install OpenShift Serverless
Read the following information about supported configurations and prerequisites before you install OpenShift Serverless.
- OpenShift Serverless is supported for installation in a restricted network environment.
- OpenShift Serverless currently cannot be used in a multi-tenant configuration on a single cluster.
3.1.1. Supported configurations
The set of supported features, configurations, and integrations for OpenShift Serverless, current and past versions, are available at the Supported Configurations page.
3.1.2. Scalability and performance
OpenShift Serverless has been tested with a configuration of 3 main nodes and 3 worker nodes, each of which has 64 CPUs, 457 GB of memory, and 394 GB of storage each.
The maximum number of Knative services that can be created using this configuration is 3,000. This corresponds to the OpenShift Container Platform Kubernetes services limit of 10,000, since 1 Knative service creates 3 Kubernetes services.
The average scale from zero response time was approximately 3.4 seconds, with a maximum response time of 8 seconds, and a 99.9th percentile of 4.5 seconds for a simple Quarkus application. These times might vary depending on the application and the runtime of the application.
3.1.3. Defining cluster size requirements
To install and use OpenShift Serverless, the OpenShift Container Platform cluster must be sized correctly.
The following requirements relate only to the pool of worker machines of the OpenShift Container Platform cluster. Control plane nodes are not used for general scheduling and are omitted from the requirements.
The minimum requirement to use OpenShift Serverless is a cluster with 10 CPUs and 40GB memory. By default, each pod requests ~400m of CPU, so the minimum requirements are based on this value.
The total size requirements to run OpenShift Serverless are dependent on the components that are installed and the applications that are deployed, and might vary depending on your deployment.
3.1.4. Scaling your cluster using compute machine sets
You can use the OpenShift Container Platform MachineSet
API to manually scale your cluster up to the desired size. The minimum requirements usually mean that you must scale up one of the default compute machine sets by two additional machines. See Manually scaling a compute machine set.
3.1.4.1. Additional requirements for advanced use-cases
For more advanced use-cases such as logging or metering on OpenShift Container Platform, you must deploy more resources. Recommended requirements for such use-cases are 24 CPUs and 96GB of memory.
If you have high availability (HA) enabled on your cluster, this requires between 0.5 - 1.5 cores and between 200MB - 2GB of memory for each replica of the Knative Serving control plane. HA is enabled for some Knative Serving components by default. You can disable HA by following the documentation on "Configuring high availability replicas".
3.1.5. Additional resources
3.2. Installing the OpenShift Serverless Operator
Installing the OpenShift Serverless Operator enables you to install and use Knative Serving, Knative Eventing, and Knative Kafka on a OpenShift Container Platform cluster. The OpenShift Serverless Operator manages Knative custom resource definitions (CRDs) for your cluster and enables you to configure them without directly modifying individual config maps for each component.
3.2.1. Installing the OpenShift Serverless Operator from the web console
You can install the OpenShift Serverless Operator from the OperatorHub by using the OpenShift Container Platform web console. Installing this Operator enables you to install and use Knative components.
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- You have logged in to the OpenShift Container Platform web console.
Procedure
- In the OpenShift Container Platform web console, navigate to the Operators → OperatorHub page.
- Scroll, or type the keyword Serverless into the Filter by keyword box to find the OpenShift Serverless Operator.
- Review the information about the Operator and click Install.
On the Install Operator page:
-
The Installation Mode is All namespaces on the cluster (default). This mode installs the Operator in the default
openshift-serverless
namespace to watch and be made available to all namespaces in the cluster. -
The Installed Namespace is
openshift-serverless
. - Select the stable channel as the Update Channel. The stable channel will enable installation of the latest stable release of the OpenShift Serverless Operator.
- Select Automatic or Manual approval strategy.
-
The Installation Mode is All namespaces on the cluster (default). This mode installs the Operator in the default
- Click Install to make the Operator available to the selected namespaces on this OpenShift Container Platform cluster.
From the Catalog → Operator Management page, you can monitor the OpenShift Serverless Operator subscription’s installation and upgrade progress.
- If you selected a Manual approval strategy, the subscription’s upgrade status will remain Upgrading until you review and approve its install plan. After approving on the Install Plan page, the subscription upgrade status moves to Up to date.
- If you selected an Automatic approval strategy, the upgrade status should resolve to Up to date without intervention.
Verification
After the Subscription’s upgrade status is Up to date, select Catalog → Installed Operators to verify that the OpenShift Serverless Operator eventually shows up and its Status ultimately resolves to InstallSucceeded in the relevant namespace.
If it does not:
- Switch to the Catalog → Operator Management page and inspect the Operator Subscriptions and Install Plans tabs for any failure or errors under Status.
-
Check the logs in any pods in the
openshift-serverless
project on the Workloads → Pods page that are reporting issues to troubleshoot further.
If you want to use Red Hat OpenShift distributed tracing with OpenShift Serverless, you must install and configure Red Hat OpenShift distributed tracing before you install Knative Serving or Knative Eventing.
3.2.2. Installing the OpenShift Serverless Operator from the CLI
You can install the OpenShift Serverless Operator from the OperatorHub by using the CLI. Installing this Operator enables you to install and use Knative components.
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- Your cluster has the Marketplace capability enabled or the Red Hat Operator catalog source configured manually.
- You have logged in to the OpenShift Container Platform cluster.
Procedure
Create a YAML file containing
Namespace
,OperatorGroup
, andSubscription
objects to subscribe a namespace to the OpenShift Serverless Operator. For example, create the fileserverless-subscription.yaml
with the following content:Example subscription
--- apiVersion: v1 kind: Namespace metadata: name: openshift-serverless --- apiVersion: operators.coreos.com/v1 kind: OperatorGroup metadata: name: serverless-operators namespace: openshift-serverless spec: {} --- apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: serverless-operator namespace: openshift-serverless spec: channel: stable 1 name: serverless-operator 2 source: redhat-operators 3 sourceNamespace: openshift-marketplace 4
- 1
- The channel name of the Operator. The
stable
channel enables installation of the most recent stable version of the OpenShift Serverless Operator. - 2
- The name of the Operator to subscribe to. For the OpenShift Serverless Operator, this is always
serverless-operator
. - 3
- The name of the CatalogSource that provides the Operator. Use
redhat-operators
for the default OperatorHub catalog sources. - 4
- The namespace of the CatalogSource. Use
openshift-marketplace
for the default OperatorHub catalog sources.
Create the
Subscription
object:$ oc apply -f serverless-subscription.yaml
Verification
Check that the cluster service version (CSV) has reached the Succeeded
phase:
Example command
$ oc get csv
Example output
NAME DISPLAY VERSION REPLACES PHASE serverless-operator.v1.25.0 Red Hat OpenShift Serverless 1.25.0 serverless-operator.v1.24.0 Succeeded
If you want to use Red Hat OpenShift distributed tracing with OpenShift Serverless, you must install and configure Red Hat OpenShift distributed tracing before you install Knative Serving or Knative Eventing.
3.2.3. Global configuration
The OpenShift Serverless Operator manages the global configuration of a Knative installation, including propagating values from the KnativeServing
and KnativeEventing
custom resources to system config maps. Any updates to config maps which are applied manually are overwritten by the Operator. However, modifying the Knative custom resources allows you to set values for these config maps.
Knative has multiple config maps that are named with the prefix config-
. All Knative config maps are created in the same namespace as the custom resource that they apply to. For example, if the KnativeServing
custom resource is created in the knative-serving
namespace, all Knative Serving config maps are also created in this namespace.
The spec.config
in the Knative custom resources have one <name>
entry for each config map, named config-<name>
, with a value which is be used for the config map data
.
3.2.4. Additional resources
3.2.5. Next steps
- After the OpenShift Serverless Operator is installed, you can install Knative Serving or install Knative Eventing.
3.3. Installing the Knative CLI
The Knative (kn
) CLI does not have its own login mechanism. To log in to the cluster, you must install the OpenShift CLI (oc
) and use the oc login
command. Installation options for the CLIs may vary depending on your operating system.
For more information on installing the OpenShift CLI (oc
) for your operating system and logging in with oc
, see the OpenShift CLI getting started documentation.
OpenShift Serverless cannot be installed using the Knative (kn
) CLI. A cluster administrator must install the OpenShift Serverless Operator and set up the Knative components, as described in the Installing the OpenShift Serverless Operator documentation.
If you try to use an older version of the Knative (kn
) CLI with a newer OpenShift Serverless release, the API is not found and an error occurs.
For example, if you use the 1.23.0 release of the Knative (kn
) CLI, which uses version 1.2, with the 1.24.0 OpenShift Serverless release, which uses the 1.3 versions of the Knative Serving and Knative Eventing APIs, the CLI does not work because it continues to look for the outdated 1.2 API versions.
Ensure that you are using the latest Knative (kn
) CLI version for your OpenShift Serverless release to avoid issues.
3.3.1. Installing the Knative CLI using the OpenShift Container Platform web console
Using the OpenShift Container Platform web console provides a streamlined and intuitive user interface to install the Knative (kn
) CLI. After the OpenShift Serverless Operator is installed, you will see a link to download the Knative (kn
) CLI for Linux (amd64, s390x, ppc64le), macOS, or Windows from the Command Line Tools page in the OpenShift Container Platform web console.
Prerequisites
- You have logged in to the OpenShift Container Platform web console.
The OpenShift Serverless Operator and Knative Serving are installed on your OpenShift Container Platform cluster.
ImportantIf libc is not available, you might see the following error when you run CLI commands:
$ kn: No such file or directory
-
If you want to use the verification steps for this procedure, you must install the OpenShift (
oc
) CLI.
Procedure
-
Download the Knative (
kn
) CLI from the Command Line Tools page. You can access the Command Line Tools page by clicking the icon in the top right corner of the web console and selecting Command Line Tools in the list. Unpack the archive:
$ tar -xf <file>
-
Move the
kn
binary to a directory on yourPATH
. To check your
PATH
, run:$ echo $PATH
Verification
Run the following commands to check that the correct Knative CLI resources and route have been created:
$ oc get ConsoleCLIDownload
Example output
NAME DISPLAY NAME AGE kn kn - OpenShift Serverless Command Line Interface (CLI) 2022-09-20T08:41:18Z oc-cli-downloads oc - OpenShift Command Line Interface (CLI) 2022-09-20T08:00:20Z
$ oc get route -n openshift-serverless
Example output
NAME HOST/PORT PATH SERVICES PORT TERMINATION WILDCARD kn kn-openshift-serverless.apps.example.com knative-openshift-metrics-3 http-cli edge/Redirect None
3.3.2. Installing the Knative CLI for Linux by using an RPM package manager
For Red Hat Enterprise Linux (RHEL), you can install the Knative (kn
) CLI as an RPM by using a package manager, such as yum
or dnf
. This allows the Knative CLI version to be automatically managed by the system. For example, using a command like dnf upgrade
upgrades all packages, including kn
, if a new version is available.
Prerequisites
- You have an active OpenShift Container Platform subscription on your Red Hat account.
Procedure
Register with Red Hat Subscription Manager:
# subscription-manager register
Pull the latest subscription data:
# subscription-manager refresh
Attach the subscription to the registered system:
# subscription-manager attach --pool=<pool_id> 1
- 1
- Pool ID for an active OpenShift Container Platform subscription
Enable the repositories required by the Knative (
kn
) CLI:Linux (x86_64, amd64)
# subscription-manager repos --enable="openshift-serverless-1-for-rhel-8-x86_64-rpms"
Linux on IBM Z and LinuxONE (s390x)
# subscription-manager repos --enable="openshift-serverless-1-for-rhel-8-s390x-rpms"
Linux on IBM Power (ppc64le)
# subscription-manager repos --enable="openshift-serverless-1-for-rhel-8-ppc64le-rpms"
Install the Knative (
kn
) CLI as an RPM by using a package manager:Example
yum
command# yum install openshift-serverless-clients
3.3.3. Installing the Knative CLI for Linux
If you are using a Linux distribution that does not have RPM or another package manager installed, you can install the Knative (kn
) CLI as a binary file. To do this, you must download and unpack a tar.gz
archive and add the binary to a directory on your PATH
.
Prerequisites
If you are not using RHEL or Fedora, ensure that libc is installed in a directory on your library path.
ImportantIf libc is not available, you might see the following error when you run CLI commands:
$ kn: No such file or directory
Procedure
Download the relevant Knative (
kn
) CLItar.gz
archive:You can also download any version of
kn
by navigating to that version’s corresponding directory in the Serverless client download mirror.Unpack the archive:
$ tar -xf <filename>
-
Move the
kn
binary to a directory on yourPATH
. To check your
PATH
, run:$ echo $PATH
3.3.4. Installing the Knative CLI for macOS
If you are using macOS, you can install the Knative (kn
) CLI as a binary file. To do this, you must download and unpack a tar.gz
archive and add the binary to a directory on your PATH
.
Procedure
Download the Knative (
kn
) CLItar.gz
archive.You can also download any version of
kn
by navigating to that version’s corresponding directory in the Serverless client download mirror.- Unpack and extract the archive.
-
Move the
kn
binary to a directory on yourPATH
. To check your
PATH
, open a terminal window and run:$ echo $PATH
3.3.5. Installing the Knative CLI for Windows
If you are using Windows, you can install the Knative (kn
) CLI as a binary file. To do this, you must download and unpack a ZIP archive and add the binary to a directory on your PATH
.
Procedure
Download the Knative (
kn
) CLI ZIP archive.You can also download any version of
kn
by navigating to that version’s corresponding directory in the Serverless client download mirror.- Extract the archive with a ZIP program.
-
Move the
kn
binary to a directory on yourPATH
. To check your
PATH
, open the command prompt and run the command:C:\> path
3.4. Installing Knative Serving
Installing Knative Serving allows you to create Knative services and functions on your cluster. It also allows you to use additional functionality such as autoscaling and networking options for your applications.
After you install the OpenShift Serverless Operator, you can install Knative Serving by using the default settings, or configure more advanced settings in the KnativeServing
custom resource (CR). For more information about configuration options for the KnativeServing
CR, see Global configuration.
If you want to use Red Hat OpenShift distributed tracing with OpenShift Serverless, you must install and configure Red Hat OpenShift distributed tracing before you install Knative Serving.
3.4.1. Installing Knative Serving by using the web console
After you install the OpenShift Serverless Operator, install Knative Serving by using the OpenShift Container Platform web console. You can install Knative Serving by using the default settings or configure more advanced settings in the KnativeServing
custom resource (CR).
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- You have logged in to the OpenShift Container Platform web console.
- You have installed the OpenShift Serverless Operator.
Procedure
- In the Administrator perspective of the OpenShift Container Platform web console, navigate to Operators → Installed Operators.
- Check that the Project dropdown at the top of the page is set to Project: knative-serving.
- Click Knative Serving in the list of Provided APIs for the OpenShift Serverless Operator to go to the Knative Serving tab.
- Click Create Knative Serving.
In the Create Knative Serving page, you can install Knative Serving using the default settings by clicking Create.
You can also modify settings for the Knative Serving installation by editing the
KnativeServing
object using either the form provided, or by editing the YAML.-
Using the form is recommended for simpler configurations that do not require full control of
KnativeServing
object creation. Editing the YAML is recommended for more complex configurations that require full control of
KnativeServing
object creation. You can access the YAML by clicking the edit YAML link in the top right of the Create Knative Serving page.After you complete the form, or have finished modifying the YAML, click Create.
NoteFor more information about configuration options for the KnativeServing custom resource definition, see the documentation on Advanced installation configuration options.
-
Using the form is recommended for simpler configurations that do not require full control of
-
After you have installed Knative Serving, the
KnativeServing
object is created, and you are automatically directed to the Knative Serving tab. You will see theknative-serving
custom resource in the list of resources.
Verification
-
Click on
knative-serving
custom resource in the Knative Serving tab. You will be automatically directed to the Knative Serving Overview page.
- Scroll down to look at the list of Conditions.
You should see a list of conditions with a status of True, as shown in the example image.
NoteIt may take a few seconds for the Knative Serving resources to be created. You can check their status in the Resources tab.
- If the conditions have a status of Unknown or False, wait a few moments and then check again after you have confirmed that the resources have been created.
3.4.2. Installing Knative Serving by using YAML
After you install the OpenShift Serverless Operator, you can install Knative Serving by using the default settings, or configure more advanced settings in the KnativeServing
custom resource (CR). You can use the following procedure to install Knative Serving by using YAML files and the oc
CLI.
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- You have installed the OpenShift Serverless Operator.
-
Install the OpenShift CLI (
oc
).
Procedure
Create a file named
serving.yaml
and copy the following example YAML into it:apiVersion: operator.knative.dev/v1beta1 kind: KnativeServing metadata: name: knative-serving namespace: knative-serving
Apply the
serving.yaml
file:$ oc apply -f serving.yaml
Verification
To verify the installation is complete, enter the following command:
$ oc get knativeserving.operator.knative.dev/knative-serving -n knative-serving --template='{{range .status.conditions}}{{printf "%s=%s\n" .type .status}}{{end}}'
Example output
DependenciesInstalled=True DeploymentsAvailable=True InstallSucceeded=True Ready=True
NoteIt may take a few seconds for the Knative Serving resources to be created.
If the conditions have a status of
Unknown
orFalse
, wait a few moments and then check again after you have confirmed that the resources have been created.Check that the Knative Serving resources have been created:
$ oc get pods -n knative-serving
Example output
NAME READY STATUS RESTARTS AGE activator-67ddf8c9d7-p7rm5 2/2 Running 0 4m activator-67ddf8c9d7-q84fz 2/2 Running 0 4m autoscaler-5d87bc6dbf-6nqc6 2/2 Running 0 3m59s autoscaler-5d87bc6dbf-h64rl 2/2 Running 0 3m59s autoscaler-hpa-77f85f5cc4-lrts7 2/2 Running 0 3m57s autoscaler-hpa-77f85f5cc4-zx7hl 2/2 Running 0 3m56s controller-5cfc7cb8db-nlccl 2/2 Running 0 3m50s controller-5cfc7cb8db-rmv7r 2/2 Running 0 3m18s domain-mapping-86d84bb6b4-r746m 2/2 Running 0 3m58s domain-mapping-86d84bb6b4-v7nh8 2/2 Running 0 3m58s domainmapping-webhook-769d679d45-bkcnj 2/2 Running 0 3m58s domainmapping-webhook-769d679d45-fff68 2/2 Running 0 3m58s storage-version-migration-serving-serving-0.26.0--1-6qlkb 0/1 Completed 0 3m56s webhook-5fb774f8d8-6bqrt 2/2 Running 0 3m57s webhook-5fb774f8d8-b8lt5 2/2 Running 0 3m57s
Check that the necessary networking components have been installed to the automatically created
knative-serving-ingress
namespace:$ oc get pods -n knative-serving-ingress
Example output
NAME READY STATUS RESTARTS AGE net-kourier-controller-7d4b6c5d95-62mkf 1/1 Running 0 76s net-kourier-controller-7d4b6c5d95-qmgm2 1/1 Running 0 76s 3scale-kourier-gateway-6688b49568-987qz 1/1 Running 0 75s 3scale-kourier-gateway-6688b49568-b5tnp 1/1 Running 0 75s
3.4.3. Next steps
- If you want to use Knative event-driven architecture you can install Knative Eventing.
3.5. Installing Knative Eventing
To use event-driven architecture on your cluster, install Knative Eventing. You can create Knative components such as event sources, brokers, and channels and then use them to send events to applications or external systems.
After you install the OpenShift Serverless Operator, you can install Knative Eventing by using the default settings, or configure more advanced settings in the KnativeEventing
custom resource (CR). For more information about configuration options for the KnativeEventing
CR, see Global configuration.
If you want to use Red Hat OpenShift distributed tracing with OpenShift Serverless, you must install and configure Red Hat OpenShift distributed tracing before you install Knative Eventing.
3.5.1. Installing Knative Eventing by using the web console
After you install the OpenShift Serverless Operator, install Knative Eventing by using the OpenShift Container Platform web console. You can install Knative Eventing by using the default settings or configure more advanced settings in the KnativeEventing
custom resource (CR).
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- You have logged in to the OpenShift Container Platform web console.
- You have installed the OpenShift Serverless Operator.
Procedure
- In the Administrator perspective of the OpenShift Container Platform web console, navigate to Operators → Installed Operators.
- Check that the Project dropdown at the top of the page is set to Project: knative-eventing.
- Click Knative Eventing in the list of Provided APIs for the OpenShift Serverless Operator to go to the Knative Eventing tab.
- Click Create Knative Eventing.
In the Create Knative Eventing page, you can choose to configure the
KnativeEventing
object by using either the default form provided, or by editing the YAML.Using the form is recommended for simpler configurations that do not require full control of
KnativeEventing
object creation.Optional. If you are configuring the
KnativeEventing
object using the form, make any changes that you want to implement for your Knative Eventing deployment.
Click Create.
Editing the YAML is recommended for more complex configurations that require full control of
KnativeEventing
object creation. You can access the YAML by clicking the edit YAML link in the top right of the Create Knative Eventing page.Optional. If you are configuring the
KnativeEventing
object by editing the YAML, make any changes to the YAML that you want to implement for your Knative Eventing deployment.
- Click Create.
-
After you have installed Knative Eventing, the
KnativeEventing
object is created, and you are automatically directed to the Knative Eventing tab. You will see theknative-eventing
custom resource in the list of resources.
Verification
-
Click on the
knative-eventing
custom resource in the Knative Eventing tab. You are automatically directed to the Knative Eventing Overview page.
- Scroll down to look at the list of Conditions.
You should see a list of conditions with a status of True, as shown in the example image.
NoteIt may take a few seconds for the Knative Eventing resources to be created. You can check their status in the Resources tab.
- If the conditions have a status of Unknown or False, wait a few moments and then check again after you have confirmed that the resources have been created.
3.5.2. Installing Knative Eventing by using YAML
After you install the OpenShift Serverless Operator, you can install Knative Eventing by using the default settings, or configure more advanced settings in the KnativeEventing
custom resource (CR). You can use the following procedure to install Knative Eventing by using YAML files and the oc
CLI.
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- You have installed the OpenShift Serverless Operator.
-
Install the OpenShift CLI (
oc
).
Procedure
-
Create a file named
eventing.yaml
. Copy the following sample YAML into
eventing.yaml
:apiVersion: operator.knative.dev/v1beta1 kind: KnativeEventing metadata: name: knative-eventing namespace: knative-eventing
- Optional. Make any changes to the YAML that you want to implement for your Knative Eventing deployment.
Apply the
eventing.yaml
file by entering:$ oc apply -f eventing.yaml
Verification
Verify the installation is complete by entering the following command and observing the output:
$ oc get knativeeventing.operator.knative.dev/knative-eventing \ -n knative-eventing \ --template='{{range .status.conditions}}{{printf "%s=%s\n" .type .status}}{{end}}'
Example output
InstallSucceeded=True Ready=True
NoteIt may take a few seconds for the Knative Eventing resources to be created.
-
If the conditions have a status of
Unknown
orFalse
, wait a few moments and then check again after you have confirmed that the resources have been created. Check that the Knative Eventing resources have been created by entering:
$ oc get pods -n knative-eventing
Example output
NAME READY STATUS RESTARTS AGE broker-controller-58765d9d49-g9zp6 1/1 Running 0 7m21s eventing-controller-65fdd66b54-jw7bh 1/1 Running 0 7m31s eventing-webhook-57fd74b5bd-kvhlz 1/1 Running 0 7m31s imc-controller-5b75d458fc-ptvm2 1/1 Running 0 7m19s imc-dispatcher-64f6d5fccb-kkc4c 1/1 Running 0 7m18s
3.5.3. Installing Knative Kafka
Knative Kafka provides integration options for you to use supported versions of the Apache Kafka message streaming platform with OpenShift Serverless. Knative Kafka functionality is available in an OpenShift Serverless installation if you have installed the KnativeKafka
custom resource.
Prerequisites
- You have installed the OpenShift Serverless Operator and Knative Eventing on your cluster.
- You have access to a Red Hat AMQ Streams cluster.
-
Install the OpenShift CLI (
oc
) if you want to use the verification steps.
- You have cluster administrator permissions on OpenShift Container Platform.
- You are logged in to the OpenShift Container Platform web console.
Procedure
- In the Administrator perspective, navigate to Operators → Installed Operators.
- Check that the Project dropdown at the top of the page is set to Project: knative-eventing.
- In the list of Provided APIs for the OpenShift Serverless Operator, find the Knative Kafka box and click Create Instance.
Configure the KnativeKafka object in the Create Knative Kafka page.
ImportantTo use the Kafka channel, source, broker, or sink on your cluster, you must toggle the enabled switch for the options you want to use to true. These switches are set to false by default. Additionally, to use the Kafka channel, broker, or sink you must specify the bootstrap servers.
Example
KnativeKafka
custom resourceapiVersion: operator.serverless.openshift.io/v1alpha1 kind: KnativeKafka metadata: name: knative-kafka namespace: knative-eventing spec: channel: enabled: true 1 bootstrapServers: <bootstrap_servers> 2 source: enabled: true 3 broker: enabled: true 4 defaultConfig: bootstrapServers: <bootstrap_servers> 5 numPartitions: <num_partitions> 6 replicationFactor: <replication_factor> 7 sink: enabled: true 8
- 1
- Enables developers to use the
KafkaChannel
channel type in the cluster. - 2
- A comma-separated list of bootstrap servers from your AMQ Streams cluster.
- 3
- Enables developers to use the
KafkaSource
event source type in the cluster. - 4
- Enables developers to use the Knative Kafka broker implementation in the cluster.
- 5
- A comma-separated list of bootstrap servers from your Red Hat AMQ Streams cluster.
- 6
- Defines the number of partitions of the Kafka topics, backed by the
Broker
objects. The default is10
. - 7
- Defines the replication factor of the Kafka topics, backed by the
Broker
objects. The default is3
. - 8
- Enables developers to use a Kafka sink in the cluster.
NoteThe
replicationFactor
value must be less than or equal to the number of nodes of your Red Hat AMQ Streams cluster.- Using the form is recommended for simpler configurations that do not require full control of KnativeKafka object creation.
- Editing the YAML is recommended for more complex configurations that require full control of KnativeKafka object creation. You can access the YAML by clicking the Edit YAML link in the top right of the Create Knative Kafka page.
- Click Create after you have completed any of the optional configurations for Kafka. You are automatically directed to the Knative Kafka tab where knative-kafka is in the list of resources.
Verification
- Click on the knative-kafka resource in the Knative Kafka tab. You are automatically directed to the Knative Kafka Overview page.
View the list of Conditions for the resource and confirm that they have a status of True.
If the conditions have a status of Unknown or False, wait a few moments to refresh the page.
Check that the Knative Kafka resources have been created:
$ oc get pods -n knative-eventing
Example output
NAME READY STATUS RESTARTS AGE kafka-broker-dispatcher-7769fbbcbb-xgffn 2/2 Running 0 44s kafka-broker-receiver-5fb56f7656-fhq8d 2/2 Running 0 44s kafka-channel-dispatcher-84fd6cb7f9-k2tjv 2/2 Running 0 44s kafka-channel-receiver-9b7f795d5-c76xr 2/2 Running 0 44s kafka-controller-6f95659bf6-trd6r 2/2 Running 0 44s kafka-source-dispatcher-6bf98bdfff-8bcsn 2/2 Running 0 44s kafka-webhook-eventing-68dc95d54b-825xs 2/2 Running 0 44s
3.5.4. Next steps
- If you want to use Knative services you can install Knative Serving.
3.6. Configuring Knative Kafka
Knative Kafka provides integration options for you to use supported versions of the Apache Kafka message streaming platform with OpenShift Serverless. Kafka provides options for event source, channel, broker, and event sink capabilities.
In addition to the Knative Eventing components that are provided as part of a core OpenShift Serverless installation, cluster administrators can install the KnativeKafka
custom resource (CR).
Knative Kafka is not currently supported for IBM Z and IBM Power.
The KnativeKafka
CR provides users with additional options, such as:
- Kafka source
- Kafka channel
- Kafka broker
- Kafka sink
3.7. Configuring OpenShift Serverless Functions
To improve the process of deployment of your application code, you can use OpenShift Serverless to deploy stateless, event-driven functions as a Knative service on OpenShift Container Platform. If you want to develop functions, you must complete the set up steps.
3.7.1. Prerequisites
To enable the use of OpenShift Serverless Functions on your cluster, you must complete the following steps:
The OpenShift Serverless Operator and Knative Serving are installed on your cluster.
NoteFunctions are deployed as a Knative service. If you want to use event-driven architecture with your functions, you must also install Knative Eventing.
-
You have the
oc
CLI installed. -
You have the Knative (
kn
) CLI installed. Installing the Knative CLI enables the use ofkn func
commands which you can use to create and manage functions. - You have installed Docker Container Engine or Podman version 3.4.7 or higher.
- You have access to an available image registry, such as the OpenShift Container Registry.
- If you are using Quay.io as the image registry, you must ensure that either the repository is not private, or that you have followed the OpenShift Container Platform documentation on Allowing pods to reference images from other secured registries.
- If you are using the OpenShift Container Registry, a cluster administrator must expose the registry.
3.7.2. Setting up Podman
To use advanced container management features, you might want to use Podman with OpenShift Serverless Functions. To do so, you need to start the Podman service and configure the Knative (kn
) CLI to connect to it.
Procedure
Start the Podman service that serves the Docker API on a UNIX socket at
${XDG_RUNTIME_DIR}/podman/podman.sock
:$ systemctl start --user podman.socket
NoteOn most systems, this socket is located at
/run/user/$(id -u)/podman/podman.sock
.Establish the environment variable that is used to build a function:
$ export DOCKER_HOST="unix://${XDG_RUNTIME_DIR}/podman/podman.sock"
Run the build command inside your function project directory with the
-v
flag to see verbose output. You should see a connection to your local UNIX socket:$ kn func build -v
3.7.3. Setting up Podman on macOS
To use advanced container management features, you might want to use Podman with OpenShift Serverless Functions. To do so on macOS, you need to start the Podman machine and configure the Knative (kn
) CLI to connect to it.
Procedure
Create the Podman machine:
$ podman machine init --memory=8192 --cpus=2 --disk-size=20
Start the Podman machine, which serves the Docker API on a UNIX socket:
$ podman machine start Starting machine "podman-machine-default" Waiting for VM ... Mounting volume... /Users/myuser:/Users/user [...truncated output...] You can still connect Docker API clients by setting DOCKER_HOST using the following command in your terminal session: export DOCKER_HOST='unix:///Users/myuser/.local/share/containers/podman/machine/podman-machine-default/podman.sock' Machine "podman-machine-default" started successfully
NoteOn most macOS systems, this socket is located at
/Users/myuser/.local/share/containers/podman/machine/podman-machine-default/podman.sock
.Establish the environment variable that is used to build a function:
$ export DOCKER_HOST='unix:///Users/myuser/.local/share/containers/podman/machine/podman-machine-default/podman.sock'
Run the build command inside your function project directory with the
-v
flag to see verbose output. You should see a connection to your local UNIX socket:$ kn func build -v
3.7.4. Next steps
- For more information about Docker Container Engine or Podman, see Container build tool options.
- See Getting started with functions.
3.8. Serverless upgrades
OpenShift Serverless should be upgraded without skipping release versions. This section shows how to resolve problems with upgrading.
3.8.1. Resolving an OpenShift Serverless Operator upgrade failure
You might encounter an error when upgrading OpenShift Serverless Operator, for example, when performing manual uninstalls and reinstalls. If you encounter an error, you must manually reinstall OpenShift Serverless Operator.
Procedure
Identify the version of OpenShift Serverless Operator that was installed originally by searching in the OpenShift Serverless Release Notes.
For example, the error message during attempted upgrade might contain the following string:
The installed KnativeServing version is v1.5.0.
In this example, the KnativeServing
MAJOR.MINOR
version is1.5
, which is covered in the release notes for OpenShift Serverless 1.26: OpenShift Serverless now uses Knative Serving 1.5.- Uninstall OpenShift Serverless Operator and all of its install plans.
Manually install the version of OpenShift Serverless Operator that you discovered in the first step. To install, first create a
serverless-subscription.yaml
file as shown in the following example:apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: serverless-operator namespace: openshift-serverless spec: channel: stable name: serverless-operator source: redhat-operators sourceNamespace: openshift-marketplace installPlanApproval: Manual startingCSV: serverless-operator.v1.26.0
Then, install the subscription by running the following command:
$ oc apply -f serverless-subscription.yaml
- Upgrade by manually approving the upgrade install plans as they appear.
Chapter 4. Serving
4.1. Getting started with Knative Serving
4.1.1. Serverless applications
Serverless applications are created and deployed as Kubernetes services, defined by a route and a configuration, and contained in a YAML file. To deploy a serverless application using OpenShift Serverless, you must create a Knative Service
object.
Example Knative Service
object YAML file
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: hello 1 namespace: default 2 spec: template: spec: containers: - image: docker.io/openshift/hello-openshift 3 env: - name: RESPONSE 4 value: "Hello Serverless!"
You can create a serverless application by using one of the following methods:
Create a Knative service from the OpenShift Container Platform web console.
See Creating applications using the Developer perspective for more information.
-
Create a Knative service by using the Knative (
kn
) CLI. -
Create and apply a Knative
Service
object as a YAML file, by using theoc
CLI.
4.1.1.1. Creating serverless applications by using the Knative CLI
Using the Knative (kn
) CLI to create serverless applications provides a more streamlined and intuitive user interface over modifying YAML files directly. You can use the kn service create
command to create a basic serverless application.
Prerequisites
- OpenShift Serverless Operator and Knative Serving are installed on your cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Create a Knative service:
$ kn service create <service-name> --image <image> --tag <tag-value>
Where:
-
--image
is the URI of the image for the application. --tag
is an optional flag that can be used to add a tag to the initial revision that is created with the service.Example command
$ kn service create event-display \ --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest
Example output
Creating service 'event-display' in namespace 'default': 0.271s The Route is still working to reflect the latest desired specification. 0.580s Configuration "event-display" is waiting for a Revision to become ready. 3.857s ... 3.861s Ingress has not yet been reconciled. 4.270s Ready to serve. Service 'event-display' created with latest revision 'event-display-bxshg-1' and URL: http://event-display-default.apps-crc.testing
-
4.1.1.2. Creating serverless applications using YAML
Creating Knative resources by using YAML files uses a declarative API, which enables you to describe applications declaratively and in a reproducible manner. To create a serverless application by using YAML, you must create a YAML file that defines a Knative Service
object, then apply it by using oc apply
.
After the service is created and the application is deployed, Knative creates an immutable revision for this version of the application. Knative also performs network programming to create a route, ingress, service, and load balancer for your application and automatically scales your pods up and down based on traffic.
Prerequisites
- OpenShift Serverless Operator and Knative Serving are installed on your cluster.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
Install the OpenShift CLI (
oc
).
Procedure
Create a YAML file containing the following sample code:
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: event-delivery namespace: default spec: template: spec: containers: - image: quay.io/openshift-knative/knative-eventing-sources-event-display:latest env: - name: RESPONSE value: "Hello Serverless!"
Navigate to the directory where the YAML file is contained, and deploy the application by applying the YAML file:
$ oc apply -f <filename>
If you do not want to switch to the Developer perspective in the OpenShift Container Platform web console or use the Knative (kn
) CLI or YAML files, you can create Knative components by using the Administator perspective of the OpenShift Container Platform web console.
4.1.1.3. Creating serverless applications using the Administrator perspective
Serverless applications are created and deployed as Kubernetes services, defined by a route and a configuration, and contained in a YAML file. To deploy a serverless application using OpenShift Serverless, you must create a Knative Service
object.
Example Knative Service
object YAML file
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: hello 1 namespace: default 2 spec: template: spec: containers: - image: docker.io/openshift/hello-openshift 3 env: - name: RESPONSE 4 value: "Hello Serverless!"
After the service is created and the application is deployed, Knative creates an immutable revision for this version of the application. Knative also performs network programming to create a route, ingress, service, and load balancer for your application and automatically scales your pods up and down based on traffic.
Prerequisites
To create serverless applications using the Administrator perspective, ensure that you have completed the following steps.
- The OpenShift Serverless Operator and Knative Serving are installed.
- You have logged in to the web console and are in the Administrator perspective.
Procedure
- Navigate to the Serverless → Serving page.
- In the Create list, select Service.
- Manually enter YAML or JSON definitions, or by dragging and dropping a file into the editor.
- Click Create.
4.1.1.4. Creating a service using offline mode
You can execute kn service
commands in offline mode, so that no changes happen on the cluster, and instead the service descriptor file is created on your local machine. After the descriptor file is created, you can modify the file before propagating changes to the cluster.
The offline mode of the Knative CLI is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.
For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope.
Prerequisites
- OpenShift Serverless Operator and Knative Serving are installed on your cluster.
-
You have installed the Knative (
kn
) CLI.
Procedure
In offline mode, create a local Knative service descriptor file:
$ kn service create event-display \ --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest \ --target ./ \ --namespace test
Example output
Service 'event-display' created in namespace 'test'.
The
--target ./
flag enables offline mode and specifies./
as the directory for storing the new directory tree.If you do not specify an existing directory, but use a filename, such as
--target my-service.yaml
, then no directory tree is created. Instead, only the service descriptor filemy-service.yaml
is created in the current directory.The filename can have the
.yaml
,.yml
, or.json
extension. Choosing.json
creates the service descriptor file in the JSON format.The
--namespace test
option places the new service in thetest
namespace.If you do not use
--namespace
, and you are logged in to an OpenShift Container Platform cluster, the descriptor file is created in the current namespace. Otherwise, the descriptor file is created in thedefault
namespace.
Examine the created directory structure:
$ tree ./
Example output
./ └── test └── ksvc └── event-display.yaml 2 directories, 1 file
-
The current
./
directory specified with--target
contains the newtest/
directory that is named after the specified namespace. -
The
test/
directory contains theksvc
directory, named after the resource type. -
The
ksvc
directory contains the descriptor fileevent-display.yaml
, named according to the specified service name.
-
The current
Examine the generated service descriptor file:
$ cat test/ksvc/event-display.yaml
Example output
apiVersion: serving.knative.dev/v1 kind: Service metadata: creationTimestamp: null name: event-display namespace: test spec: template: metadata: annotations: client.knative.dev/user-image: quay.io/openshift-knative/knative-eventing-sources-event-display:latest creationTimestamp: null spec: containers: - image: quay.io/openshift-knative/knative-eventing-sources-event-display:latest name: "" resources: {} status: {}
List information about the new service:
$ kn service describe event-display --target ./ --namespace test
Example output
Name: event-display Namespace: test Age: URL: Revisions: Conditions: OK TYPE AGE REASON
The
--target ./
option specifies the root directory for the directory structure containing namespace subdirectories.Alternatively, you can directly specify a YAML or JSON filename with the
--target
option. The accepted file extensions are.yaml
,.yml
, and.json
.The
--namespace
option specifies the namespace, which communicates tokn
the subdirectory that contains the necessary service descriptor file.If you do not use
--namespace
, and you are logged in to an OpenShift Container Platform cluster,kn
searches for the service in the subdirectory that is named after the current namespace. Otherwise,kn
searches in thedefault/
subdirectory.
Use the service descriptor file to create the service on the cluster:
$ kn service create -f test/ksvc/event-display.yaml
Example output
Creating service 'event-display' in namespace 'test': 0.058s The Route is still working to reflect the latest desired specification. 0.098s ... 0.168s Configuration "event-display" is waiting for a Revision to become ready. 23.377s ... 23.419s Ingress has not yet been reconciled. 23.534s Waiting for load balancer to be ready 23.723s Ready to serve. Service 'event-display' created to latest revision 'event-display-00001' is available at URL: http://event-display-test.apps.example.com
4.1.1.5. Additional resources
4.1.2. Verifying your serverless application deployment
To verify that your serverless application has been deployed successfully, you must get the application URL created by Knative, and then send a request to that URL and observe the output. OpenShift Serverless supports the use of both HTTP and HTTPS URLs, however the output from oc get ksvc
always prints URLs using the http://
format.
4.1.2.1. Verifying your serverless application deployment
To verify that your serverless application has been deployed successfully, you must get the application URL created by Knative, and then send a request to that URL and observe the output. OpenShift Serverless supports the use of both HTTP and HTTPS URLs, however the output from oc get ksvc
always prints URLs using the http://
format.
Prerequisites
- OpenShift Serverless Operator and Knative Serving are installed on your cluster.
-
You have installed the
oc
CLI. - You have created a Knative service.
Prerequisites
-
Install the OpenShift CLI (
oc
).
Procedure
Find the application URL:
$ oc get ksvc <service_name>
Example output
NAME URL LATESTCREATED LATESTREADY READY REASON event-delivery http://event-delivery-default.example.com event-delivery-4wsd2 event-delivery-4wsd2 True
Make a request to your cluster and observe the output.
Example HTTP request
$ curl http://event-delivery-default.example.com
Example HTTPS request
$ curl https://event-delivery-default.example.com
Example output
Hello Serverless!
Optional. If you receive an error relating to a self-signed certificate in the certificate chain, you can add the
--insecure
flag to the curl command to ignore the error:$ curl https://event-delivery-default.example.com --insecure
Example output
Hello Serverless!
ImportantSelf-signed certificates must not be used in a production deployment. This method is only for testing purposes.
Optional. If your OpenShift Container Platform cluster is configured with a certificate that is signed by a certificate authority (CA) but not yet globally configured for your system, you can specify this with the
curl
command. The path to the certificate can be passed to the curl command by using the--cacert
flag:$ curl https://event-delivery-default.example.com --cacert <file>
Example output
Hello Serverless!
4.2. Autoscaling
4.2.1. Autoscaling
Knative Serving provides automatic scaling, or autoscaling, for applications to match incoming demand. For example, if an application is receiving no traffic, and scale-to-zero is enabled, Knative Serving scales the application down to zero replicas. If scale-to-zero is disabled, the application is scaled down to the minimum number of replicas configured for applications on the cluster. Replicas can also be scaled up to meet demand if traffic to the application increases.
Autoscaling settings for Knative services can be global settings that are configured by cluster administrators, or per-revision settings that are configured for individual services.
You can modify per-revision settings for your services by using the OpenShift Container Platform web console, by modifying the YAML file for your service, or by using the Knative (kn
) CLI.
Any limits or targets that you set for a service are measured against a single instance of your application. For example, setting the target
annotation to 50
configures the autoscaler to scale the application so that each revision handles 50 requests at a time.
4.2.2. Scale bounds
Scale bounds determine the minimum and maximum numbers of replicas that can serve an application at any given time. You can set scale bounds for an application to help prevent cold starts or control computing costs.
4.2.2.1. Minimum scale bounds
The minimum number of replicas that can serve an application is determined by the min-scale
annotation. If scale to zero is not enabled, the min-scale
value defaults to 1
.
The min-scale
value defaults to 0
replicas if the following conditions are met:
-
The
min-scale
annotation is not set - Scaling to zero is enabled
-
The class
KPA
is used
Example service spec with min-scale
annotation
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: example-service namespace: default spec: template: metadata: annotations: autoscaling.knative.dev/min-scale: "0" ...
4.2.2.1.1. Setting the min-scale annotation by using the Knative CLI
Using the Knative (kn
) CLI to set the min-scale
annotation provides a more streamlined and intuitive user interface over modifying YAML files directly. You can use the kn service
command with the --scale-min
flag to create or modify the min-scale
value for a service.
Prerequisites
- Knative Serving is installed on the cluster.
-
You have installed the Knative (
kn
) CLI.
Procedure
Set the minimum number of replicas for the service by using the
--scale-min
flag:$ kn service create <service_name> --image <image_uri> --scale-min <integer>
Example command
$ kn service create example-service --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest --scale-min 2
4.2.2.2. Maximum scale bounds
The maximum number of replicas that can serve an application is determined by the max-scale
annotation. If the max-scale
annotation is not set, there is no upper limit for the number of replicas created.
Example service spec with max-scale
annotation
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: example-service namespace: default spec: template: metadata: annotations: autoscaling.knative.dev/max-scale: "10" ...
4.2.2.2.1. Setting the max-scale annotation by using the Knative CLI
Using the Knative (kn
) CLI to set the max-scale
annotation provides a more streamlined and intuitive user interface over modifying YAML files directly. You can use the kn service
command with the --scale-max
flag to create or modify the max-scale
value for a service.
Prerequisites
- Knative Serving is installed on the cluster.
-
You have installed the Knative (
kn
) CLI.
Procedure
Set the maximum number of replicas for the service by using the
--scale-max
flag:$ kn service create <service_name> --image <image_uri> --scale-max <integer>
Example command
$ kn service create example-service --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest --scale-max 10
4.2.3. Concurrency
Concurrency determines the number of simultaneous requests that can be processed by each replica of an application at any given time. Concurrency can be configured as a soft limit or a hard limit:
- A soft limit is a targeted requests limit, rather than a strictly enforced bound. For example, if there is a sudden burst of traffic, the soft limit target can be exceeded.
A hard limit is a strictly enforced upper bound requests limit. If concurrency reaches the hard limit, surplus requests are buffered and must wait until there is enough free capacity to execute the requests.
ImportantUsing a hard limit configuration is only recommended if there is a clear use case for it with your application. Having a low, hard limit specified may have a negative impact on the throughput and latency of an application, and might cause cold starts.
Adding a soft target and a hard limit means that the autoscaler targets the soft target number of concurrent requests, but imposes a hard limit of the hard limit value for the maximum number of requests.
If the hard limit value is less than the soft limit value, the soft limit value is tuned down, because there is no need to target more requests than the number that can actually be handled.
4.2.3.1. Configuring a soft concurrency target
A soft limit is a targeted requests limit, rather than a strictly enforced bound. For example, if there is a sudden burst of traffic, the soft limit target can be exceeded. You can specify a soft concurrency target for your Knative service by setting the autoscaling.knative.dev/target
annotation in the spec, or by using the kn service
command with the correct flags.
Procedure
Optional: Set the
autoscaling.knative.dev/target
annotation for your Knative service in the spec of theService
custom resource:Example service spec
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: example-service namespace: default spec: template: metadata: annotations: autoscaling.knative.dev/target: "200"
Optional: Use the
kn service
command to specify the--concurrency-target
flag:$ kn service create <service_name> --image <image_uri> --concurrency-target <integer>
Example command to create a service with a concurrency target of 50 requests
$ kn service create example-service --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest --concurrency-target 50
4.2.3.2. Configuring a hard concurrency limit
A hard concurrency limit is a strictly enforced upper bound requests limit. If concurrency reaches the hard limit, surplus requests are buffered and must wait until there is enough free capacity to execute the requests. You can specify a hard concurrency limit for your Knative service by modifying the containerConcurrency
spec, or by using the kn service
command with the correct flags.
Procedure
Optional: Set the
containerConcurrency
spec for your Knative service in the spec of theService
custom resource:Example service spec
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: example-service namespace: default spec: template: spec: containerConcurrency: 50
The default value is
0
, which means that there is no limit on the number of simultaneous requests that are permitted to flow into one replica of the service at a time.A value greater than
0
specifies the exact number of requests that are permitted to flow into one replica of the service at a time. This example would enable a hard concurrency limit of 50 requests.Optional: Use the
kn service
command to specify the--concurrency-limit
flag:$ kn service create <service_name> --image <image_uri> --concurrency-limit <integer>
Example command to create a service with a concurrency limit of 50 requests
$ kn service create example-service --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest --concurrency-limit 50
4.2.3.3. Concurrency target utilization
This value specifies the percentage of the concurrency limit that is actually targeted by the autoscaler. This is also known as specifying the hotness at which a replica runs, which enables the autoscaler to scale up before the defined hard limit is reached.
For example, if the containerConcurrency
value is set to 10, and the target-utilization-percentage
value is set to 70 percent, the autoscaler creates a new replica when the average number of concurrent requests across all existing replicas reaches 7. Requests numbered 7 to 10 are still sent to the existing replicas, but additional replicas are started in anticipation of being required after the containerConcurrency
value is reached.
Example service configured using the target-utilization-percentage annotation
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: example-service namespace: default spec: template: metadata: annotations: autoscaling.knative.dev/target-utilization-percentage: "70" ...
4.2.4. Scale-to-zero
Knative Serving provides automatic scaling, or autoscaling, for applications to match incoming demand.
4.2.4.1. Enabling scale-to-zero
You can use the enable-scale-to-zero
spec to enable or disable scale-to-zero globally for applications on the cluster.
Prerequisites
- You have installed OpenShift Serverless Operator and Knative Serving on your cluster.
- You have cluster administrator permissions.
- You are using the default Knative Pod Autoscaler. The scale to zero feature is not available if you are using the Kubernetes Horizontal Pod Autoscaler.
Procedure
Modify the
enable-scale-to-zero
spec in theKnativeServing
custom resource (CR):Example KnativeServing CR
apiVersion: operator.knative.dev/v1beta1 kind: KnativeServing metadata: name: knative-serving spec: config: autoscaler: enable-scale-to-zero: "false" 1
- 1
- The
enable-scale-to-zero
spec can be either"true"
or"false"
. If set to true, scale-to-zero is enabled. If set to false, applications are scaled down to the configured minimum scale bound. The default value is"true"
.
4.2.4.2. Configuring the scale-to-zero grace period
Knative Serving provides automatic scaling down to zero pods for applications. You can use the scale-to-zero-grace-period
spec to define an upper bound time limit that Knative waits for scale-to-zero machinery to be in place before the last replica of an application is removed.
Prerequisites
- You have installed OpenShift Serverless Operator and Knative Serving on your cluster.
- You have cluster administrator permissions.
- You are using the default Knative Pod Autoscaler. The scale-to-zero feature is not available if you are using the Kubernetes Horizontal Pod Autoscaler.
Procedure
Modify the
scale-to-zero-grace-period
spec in theKnativeServing
custom resource (CR):Example KnativeServing CR
apiVersion: operator.knative.dev/v1beta1 kind: KnativeServing metadata: name: knative-serving spec: config: autoscaler: scale-to-zero-grace-period: "30s" 1
- 1
- The grace period time in seconds. The default value is 30 seconds.
4.3. Configuring Serverless applications
4.3.1. Overriding Knative Serving system deployment configurations
You can override the default configurations for some specific deployments by modifying the deployments
spec in the KnativeServing
custom resources (CRs).
You can only override probes that are defined in the deployment by default.
All Knative Serving deployments define a readiness and a liveness probe by default, with these exceptions:
-
net-kourier-controller
and3scale-kourier-gateway
only define a readiness probe. -
net-istio-controller
andnet-istio-webhook
define no probes.
4.3.1.1. Overriding system deployment configurations
Currently, overriding default configuration settings is supported for the resources
, replicas
, labels
, annotations
, and nodeSelector
fields, as well as for the readiness
and liveness
fields for probes.
In the following example, a KnativeServing
CR overrides the webhook
deployment so that:
-
The
readiness
probe timeout fornet-kourier-controller
is set to be 10 seconds. - The deployment has specified CPU and memory resource limits.
- The deployment has 3 replicas.
-
The
example-label: label
label is added. -
The
example-annotation: annotation
annotation is added. -
The
nodeSelector
field is set to select nodes with thedisktype: hdd
label.
The KnativeServing
CR label and annotation settings override the deployment’s labels and annotations for both the deployment itself and the resulting pods.
KnativeServing CR example
apiVersion: operator.knative.dev/v1beta1
kind: KnativeServing
metadata:
name: ks
namespace: knative-serving
spec:
high-availability:
replicas: 2
deployments:
- name: net-kourier-controller
readinessProbes: 1
- container: controller
timeoutSeconds: 10
- name: webhook
resources:
- container: webhook
requests:
cpu: 300m
memory: 60Mi
limits:
cpu: 1000m
memory: 1000Mi
replicas: 3
labels:
example-label: label
annotations:
example-annotation: annotation
nodeSelector:
disktype: hdd
- 1
- You can use the
readiness
andliveness
probe overrides to override all fields of a probe in a container of a deployment as specified in the Kubernetes API except for the fields related to the probe handler:exec
,grpc
,httpGet
, andtcpSocket
.
Additional resources
4.3.2. Multi-container support for Serving
You can deploy a multi-container pod by using a single Knative service. This method is useful for separating application responsibilities into smaller, specialized parts.
Multi-container support for Serving is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.
For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope.
4.3.2.1. Configuring a multi-container service
Multi-container support is enabled by default. You can create a multi-container pod by specifiying multiple containers in the service.
Procedure
Modify your service to include additional containers. Only one container can handle requests, so specify
ports
for exactly one container. Here is an example configuration with two containers:Multiple containers configuration
apiVersion: serving.knative.dev/v1 kind: Service ... spec: template: spec: containers: - name: first-container 1 image: gcr.io/knative-samples/helloworld-go ports: - containerPort: 8080 2 - name: second-container 3 image: gcr.io/knative-samples/helloworld-java
4.3.3. EmptyDir volumes
emptyDir
volumes are empty volumes that are created when a pod is created, and are used to provide temporary working disk space. emptyDir
volumes are deleted when the pod they were created for is deleted.
4.3.3.1. Configuring the EmptyDir extension
The kubernetes.podspec-volumes-emptydir
extension controls whether emptyDir
volumes can be used with Knative Serving. To enable using emptyDir
volumes, you must modify the KnativeServing
custom resource (CR) to include the following YAML:
Example KnativeServing CR
apiVersion: operator.knative.dev/v1beta1 kind: KnativeServing metadata: name: knative-serving spec: config: features: kubernetes.podspec-volumes-emptydir: enabled ...
4.3.4. Persistent Volume Claims for Serving
Some serverless applications need permanent data storage. To achieve this, you can configure persistent volume claims (PVCs) for your Knative services.
4.3.4.1. Enabling PVC support
Procedure
To enable Knative Serving to use PVCs and write to them, modify the
KnativeServing
custom resource (CR) to include the following YAML:Enabling PVCs with write access
... spec: config: features: "kubernetes.podspec-persistent-volume-claim": enabled "kubernetes.podspec-persistent-volume-write": enabled ...
-
The
kubernetes.podspec-persistent-volume-claim
extension controls whether persistent volumes (PVs) can be used with Knative Serving. -
The
kubernetes.podspec-persistent-volume-write
extension controls whether PVs are available to Knative Serving with the write access.
-
The
To claim a PV, modify your service to include the PV configuration. For example, you might have a persistent volume claim with the following configuration:
NoteUse the storage class that supports the access mode that you are requesting. For example, you can use the
ocs-storagecluster-cephfs
class for theReadWriteMany
access mode.PersistentVolumeClaim configuration
apiVersion: v1 kind: PersistentVolumeClaim metadata: name: example-pv-claim namespace: my-ns spec: accessModes: - ReadWriteMany storageClassName: ocs-storagecluster-cephfs resources: requests: storage: 1Gi
In this case, to claim a PV with write access, modify your service as follows:
Knative service PVC configuration
apiVersion: serving.knative.dev/v1 kind: Service metadata: namespace: my-ns ... spec: template: spec: containers: ... volumeMounts: 1 - mountPath: /data name: mydata readOnly: false volumes: - name: mydata persistentVolumeClaim: 2 claimName: example-pv-claim readOnly: false 3
NoteTo successfully use persistent storage in Knative services, you need additional configuration, such as the user permissions for the Knative container user.
4.3.4.2. Additional resources
4.3.5. Init containers
Init containers are specialized containers that are run before application containers in a pod. They are generally used to implement initialization logic for an application, which may include running setup scripts or downloading required configurations. You can enable the use of init containers for Knative services by modifying the KnativeServing
custom resource (CR).
Init containers may cause longer application start-up times and should be used with caution for serverless applications, which are expected to scale up and down frequently.
4.3.5.1. Enabling init containers
Prerequisites
- You have installed OpenShift Serverless Operator and Knative Serving on your cluster.
- You have cluster administrator permissions.
Procedure
Enable the use of init containers by adding the
kubernetes.podspec-init-containers
flag to theKnativeServing
CR:Example KnativeServing CR
apiVersion: operator.knative.dev/v1beta1 kind: KnativeServing metadata: name: knative-serving spec: config: features: kubernetes.podspec-init-containers: enabled ...
4.3.6. Resolving image tags to digests
If the Knative Serving controller has access to the container registry, Knative Serving resolves image tags to a digest when you create a revision of a service. This is known as tag-to-digest resolution, and helps to provide consistency for deployments.
4.3.6.1. Tag-to-digest resolution
To give the controller access to the container registry on OpenShift Container Platform, you must create a secret and then configure controller custom certificates. You can configure controller custom certificates by modifying the controller-custom-certs
spec in the KnativeServing
custom resource (CR). The secret must reside in the same namespace as the KnativeServing
CR.
If a secret is not included in the KnativeServing
CR, this setting defaults to using public key infrastructure (PKI). When using PKI, the cluster-wide certificates are automatically injected into the Knative Serving controller by using the config-service-sa
config map. The OpenShift Serverless Operator populates the config-service-sa
config map with cluster-wide certificates and mounts the config map as a volume to the controller.
4.3.6.1.1. Configuring tag-to-digest resolution by using a secret
If the controller-custom-certs
spec uses the Secret
type, the secret is mounted as a secret volume. Knative components consume the secret directly, assuming that the secret has the required certificates.
Prerequisites
- You have cluster administrator permissions on OpenShift Container Platform.
- You have installed the OpenShift Serverless Operator and Knative Serving on your cluster.
Procedure
Create a secret:
Example command
$ oc -n knative-serving create secret generic custom-secret --from-file=<secret_name>.crt=<path_to_certificate>
Configure the
controller-custom-certs
spec in theKnativeServing
custom resource (CR) to use theSecret
type:Example KnativeServing CR
apiVersion: operator.knative.dev/v1beta1 kind: KnativeServing metadata: name: knative-serving namespace: knative-serving spec: controller-custom-certs: name: custom-secret type: Secret
4.3.7. Configuring TLS authentication
You can use Transport Layer Security (TLS) to encrypt Knative traffic and for authentication.
TLS is the only supported method of traffic encryption for Knative Kafka. Red Hat recommends using both SASL and TLS together for Knative Kafka resources.
If you want to enable internal TLS with a Red Hat OpenShift Service Mesh integration, you must enable Service Mesh with mTLS instead of the internal encryption explained in the following procedure. See the documentation for Enabling Knative Serving metrics when using Service Mesh with mTLS.
4.3.7.1. Enabling TLS authentication for internal traffic
OpenShift Serverless supports TLS edge termination by default, so that HTTPS traffic from end users is encrypted. However, internal traffic behind the OpenShift route is forwarded to applications by using plain data. By enabling TLS for internal traffic, the traffic sent between components is encrypted, which makes this traffic more secure.
If you want to enable internal TLS with a Red Hat OpenShift Service Mesh integration, you must enable Service Mesh with mTLS instead of the internal encryption explained in the following procedure.
Internal TLS encryption support is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.
For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope.
Prerequisites
- You have installed the OpenShift Serverless Operator and Knative Serving.
-
You have installed the OpenShift (
oc
) CLI.
Procedure
Create a Knative service that includes the
internal-encryption: "true"
field in the spec:... spec: config: network: internal-encryption: "true" ...
Restart the activator pods in the
knative-serving
namespace to load the certificates:$ oc delete pod -n knative-serving --selector app=activator
4.3.8. Restrictive network policies
4.3.8.1. Clusters with restrictive network policies
If you are using a cluster that multiple users have access to, your cluster might use network policies to control which pods, services, and namespaces can communicate with each other over the network. If your cluster uses restrictive network policies, it is possible that Knative system pods are not able to access your Knative application. For example, if your namespace has the following network policy, which denies all requests, Knative system pods cannot access your Knative application:
Example NetworkPolicy object that denies all requests to the namespace
kind: NetworkPolicy apiVersion: networking.k8s.io/v1 metadata: name: deny-by-default namespace: example-namespace spec: podSelector: ingress: []
4.3.8.2. Enabling communication with Knative applications on a cluster with restrictive network policies
To allow access to your applications from Knative system pods, you must add a label to each of the Knative system namespaces, and then create a NetworkPolicy
object in your application namespace that allows access to the namespace for other namespaces that have this label.
A network policy that denies requests to non-Knative services on your cluster still prevents access to these services. However, by allowing access from Knative system namespaces to your Knative application, you are allowing access to your Knative application from all namespaces in the cluster.
If you do not want to allow access to your Knative application from all namespaces on the cluster, you might want to use JSON Web Token authentication for Knative services instead. JSON Web Token authentication for Knative services requires Service Mesh.
Prerequisites
-
Install the OpenShift CLI (
oc
). - OpenShift Serverless Operator and Knative Serving are installed on your cluster.
Procedure
Add the
knative.openshift.io/system-namespace=true
label to each Knative system namespace that requires access to your application:Label the
knative-serving
namespace:$ oc label namespace knative-serving knative.openshift.io/system-namespace=true
Label the
knative-serving-ingress
namespace:$ oc label namespace knative-serving-ingress knative.openshift.io/system-namespace=true
Label the
knative-eventing
namespace:$ oc label namespace knative-eventing knative.openshift.io/system-namespace=true
Label the
knative-kafka
namespace:$ oc label namespace knative-kafka knative.openshift.io/system-namespace=true
Create a
NetworkPolicy
object in your application namespace to allow access from namespaces with theknative.openshift.io/system-namespace
label:Example
NetworkPolicy
objectapiVersion: networking.k8s.io/v1 kind: NetworkPolicy metadata: name: <network_policy_name> 1 namespace: <namespace> 2 spec: ingress: - from: - namespaceSelector: matchLabels: knative.openshift.io/system-namespace: "true" podSelector: {} policyTypes: - Ingress
4.4. Traffic splitting
4.4.1. Traffic splitting overview
In a Knative application, traffic can be managed by creating a traffic split. A traffic split is configured as part of a route, which is managed by a Knative service.
Configuring a route allows requests to be sent to different revisions of a service. This routing is determined by the traffic
spec of the Service
object.
A traffic
spec declaration consists of one or more revisions, each responsible for handling a portion of the overall traffic. The percentages of traffic routed to each revision must add up to 100%, which is ensured by a Knative validation.
The revisions specified in a traffic
spec can either be a fixed, named revision, or can point to the “latest” revision, which tracks the head of the list of all revisions for the service. The "latest" revision is a type of floating reference that updates if a new revision is created. Each revision can have a tag attached that creates an additional access URL for that revision.
The traffic
spec can be modified by:
-
Editing the YAML of a
Service
object directly. -
Using the Knative (
kn
) CLI--traffic
flag. - Using the OpenShift Container Platform web console.
When you create a Knative service, it does not have any default traffic
spec settings.
4.4.2. Traffic spec examples
The following example shows a traffic
spec where 100% of traffic is routed to the latest revision of the service. Under status
, you can see the name of the latest revision that latestRevision
resolves to:
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: example-service namespace: default spec: ... traffic: - latestRevision: true percent: 100 status: ... traffic: - percent: 100 revisionName: example-service
The following example shows a traffic
spec where 100% of traffic is routed to the revision tagged as current
, and the name of that revision is specified as example-service
. The revision tagged as latest
is kept available, even though no traffic is routed to it:
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: example-service namespace: default spec: ... traffic: - tag: current revisionName: example-service percent: 100 - tag: latest latestRevision: true percent: 0
The following example shows how the list of revisions in the traffic
spec can be extended so that traffic is split between multiple revisions. This example sends 50% of traffic to the revision tagged as current
, and 50% of traffic to the revision tagged as candidate
. The revision tagged as latest
is kept available, even though no traffic is routed to it:
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: example-service namespace: default spec: ... traffic: - tag: current revisionName: example-service-1 percent: 50 - tag: candidate revisionName: example-service-2 percent: 50 - tag: latest latestRevision: true percent: 0
4.4.3. Traffic splitting using the Knative CLI
Using the Knative (kn
) CLI to create traffic splits provides a more streamlined and intuitive user interface over modifying YAML files directly. You can use the kn service update
command to split traffic between revisions of a service.
4.4.3.1. Creating a traffic split by using the Knative CLI
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on your cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a Knative service.
Procedure
Specify the revision of your service and what percentage of traffic you want to route to it by using the
--traffic
tag with a standardkn service update
command:Example command
$ kn service update <service_name> --traffic <revision>=<percentage>
Where:
-
<service_name>
is the name of the Knative service that you are configuring traffic routing for. -
<revision>
is the revision that you want to configure to receive a percentage of traffic. You can either specify the name of the revision, or a tag that you assigned to the revision by using the--tag
flag. -
<percentage>
is the percentage of traffic that you want to send to the specified revision.
-
Optional: The
--traffic
flag can be specified multiple times in one command. For example, if you have a revision tagged as@latest
and a revision namedstable
, you can specify the percentage of traffic that you want to split to each revision as follows:Example command
$ kn service update example-service --traffic @latest=20,stable=80
If you have multiple revisions and do not specify the percentage of traffic that should be split to the last revision, the
--traffic
flag can calculate this automatically. For example, if you have a third revision namedexample
, and you use the following command:Example command
$ kn service update example-service --traffic @latest=10,stable=60
The remaining 30% of traffic is split to the
example
revision, even though it was not specified.
4.4.4. CLI flags for traffic splitting
The Knative (kn
) CLI supports traffic operations on the traffic block of a service as part of the kn service update
command.
4.4.4.1. Knative CLI traffic splitting flags
The following table displays a summary of traffic splitting flags, value formats, and the operation the flag performs. The Repetition column denotes whether repeating the particular value of flag is allowed in a kn service update
command.
Flag | Value(s) | Operation | Repetition |
---|---|---|---|
|
|
Gives | Yes |
|
|
Gives | Yes |
|
|
Gives | No |
|
|
Gives | Yes |
|
|
Gives | No |
|
|
Removes | Yes |
4.4.4.1.1. Multiple flags and order precedence
All traffic-related flags can be specified using a single kn service update
command. kn
defines the precedence of these flags. The order of the flags specified when using the command is not taken into account.
The precedence of the flags as they are evaluated by kn
are:
-
--untag
: All the referenced revisions with this flag are removed from the traffic block. -
--tag
: Revisions are tagged as specified in the traffic block. -
--traffic
: The referenced revisions are assigned a portion of the traffic split.
You can add tags to revisions and then split traffic according to the tags you have set.
4.4.4.1.2. Custom URLs for revisions
Assigning a --tag
flag to a service by using the kn service update
command creates a custom URL for the revision that is created when you update the service. The custom URL follows the pattern https://<tag>-<service_name>-<namespace>.<domain>
or http://<tag>-<service_name>-<namespace>.<domain>
.
The --tag
and --untag
flags use the following syntax:
- Require one value.
- Denote a unique tag in the traffic block of the service.
- Can be specified multiple times in one command.
4.4.4.1.2.1. Example: Assign a tag to a revision
The following example assigns the tag latest
to a revision named example-revision
:
$ kn service update <service_name> --tag @latest=example-tag
4.4.4.1.2.2. Example: Remove a tag from a revision
You can remove a tag to remove the custom URL, by using the --untag
flag.
If a revision has its tags removed, and it is assigned 0% of the traffic, the revision is removed from the traffic block entirely.
The following command removes all tags from the revision named example-revision
:
$ kn service update <service_name> --untag example-tag
4.4.5. Splitting traffic between revisions
After you create a serverless application, the application is displayed in the Topology view of the Developer perspective in the OpenShift Container Platform web console. The application revision is represented by the node, and the Knative service is indicated by a quadrilateral around the node.
Any new change in the code or the service configuration creates a new revision, which is a snapshot of the code at a given time. For a service, you can manage the traffic between the revisions of the service by splitting and routing it to the different revisions as required.
4.4.5.1. Managing traffic between revisions by using the OpenShift Container Platform web console
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on your cluster.
- You have logged in to the OpenShift Container Platform web console.
Procedure
To split traffic between multiple revisions of an application in the Topology view:
- Click the Knative service to see its overview in the side panel.
Click the Resources tab, to see a list of Revisions and Routes for the service.
Figure 4.1. Serverless application
- Click the service, indicated by the S icon at the top of the side panel, to see an overview of the service details.
-
Click the YAML tab and modify the service configuration in the YAML editor, and click Save. For example, change the
timeoutseconds
from 300 to 301 . This change in the configuration triggers a new revision. In the Topology view, the latest revision is displayed and the Resources tab for the service now displays the two revisions. In the Resources tab, click to see the traffic distribution dialog box:
- Add the split traffic percentage portion for the two revisions in the Splits field.
- Add tags to create custom URLs for the two revisions.
Click Save to see two nodes representing the two revisions in the Topology view.
Figure 4.2. Serverless application revisions
4.4.6. Rerouting traffic using blue-green strategy
You can safely reroute traffic from a production version of an app to a new version, by using a blue-green deployment strategy.
4.4.6.1. Routing and managing traffic by using a blue-green deployment strategy
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
Install the OpenShift CLI (
oc
).
Procedure
- Create and deploy an app as a Knative service.
Find the name of the first revision that was created when you deployed the service, by viewing the output from the following command:
$ oc get ksvc <service_name> -o=jsonpath='{.status.latestCreatedRevisionName}'
Example command
$ oc get ksvc example-service -o=jsonpath='{.status.latestCreatedRevisionName}'
Example output
$ example-service-00001
Add the following YAML to the service
spec
to send inbound traffic to the revision:... spec: traffic: - revisionName: <first_revision_name> percent: 100 # All traffic goes to this revision ...
Verify that you can view your app at the URL output you get from running the following command:
$ oc get ksvc <service_name>
-
Deploy a second revision of your app by modifying at least one field in the
template
spec of the service and redeploying it. For example, you can modify theimage
of the service, or anenv
environment variable. You can redeploy the service by applying the service YAML file, or by using thekn service update
command if you have installed the Knative (kn
) CLI. Find the name of the second, latest revision that was created when you redeployed the service, by running the command:
$ oc get ksvc <service_name> -o=jsonpath='{.status.latestCreatedRevisionName}'
At this point, both the first and second revisions of the service are deployed and running.
Update your existing service to create a new, test endpoint for the second revision, while still sending all other traffic to the first revision:
Example of updated service spec with test endpoint
... spec: traffic: - revisionName: <first_revision_name> percent: 100 # All traffic is still being routed to the first revision - revisionName: <second_revision_name> percent: 0 # No traffic is routed to the second revision tag: v2 # A named route ...
After you redeploy this service by reapplying the YAML resource, the second revision of the app is now staged. No traffic is routed to the second revision at the main URL, and Knative creates a new service named
v2
for testing the newly deployed revision.Get the URL of the new service for the second revision, by running the following command:
$ oc get ksvc <service_name> --output jsonpath="{.status.traffic[*].url}"
You can use this URL to validate that the new version of the app is behaving as expected before you route any traffic to it.
Update your existing service again, so that 50% of traffic is sent to the first revision, and 50% is sent to the second revision:
Example of updated service spec splitting traffic 50/50 between revisions
... spec: traffic: - revisionName: <first_revision_name> percent: 50 - revisionName: <second_revision_name> percent: 50 tag: v2 ...
When you are ready to route all traffic to the new version of the app, update the service again to send 100% of traffic to the second revision:
Example of updated service spec sending all traffic to the second revision
... spec: traffic: - revisionName: <first_revision_name> percent: 0 - revisionName: <second_revision_name> percent: 100 tag: v2 ...
TipYou can remove the first revision instead of setting it to 0% of traffic if you do not plan to roll back the revision. Non-routeable revision objects are then garbage-collected.
- Visit the URL of the first revision to verify that no more traffic is being sent to the old version of the app.
4.5. External and Ingress routing
4.5.1. Routing overview
Knative leverages OpenShift Container Platform TLS termination to provide routing for Knative services. When a Knative service is created, an OpenShift Container Platform route is automatically created for the service. This route is managed by the OpenShift Serverless Operator. The OpenShift Container Platform route exposes the Knative service through the same domain as the OpenShift Container Platform cluster.
You can disable Operator control of OpenShift Container Platform routing so that you can configure a Knative route to directly use your TLS certificates instead.
Knative routes can also be used alongside the OpenShift Container Platform route to provide additional fine-grained routing capabilities, such as traffic splitting.
4.5.1.1. Additional resources
4.5.2. Customizing labels and annotations
OpenShift Container Platform routes support the use of custom labels and annotations, which you can configure by modifying the metadata
spec of a Knative service. Custom labels and annotations are propagated from the service to the Knative route, then to the Knative ingress, and finally to the OpenShift Container Platform route.
4.5.2.1. Customizing labels and annotations for OpenShift Container Platform routes
Prerequisites
- You must have the OpenShift Serverless Operator and Knative Serving installed on your OpenShift Container Platform cluster.
-
Install the OpenShift CLI (
oc
).
Procedure
Create a Knative service that contains the label or annotation that you want to propagate to the OpenShift Container Platform route:
To create a service by using YAML:
Example service created by using YAML
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: <service_name> labels: <label_name>: <label_value> annotations: <annotation_name>: <annotation_value> ...
To create a service by using the Knative (
kn
) CLI, enter:Example service created by using a
kn
command$ kn service create <service_name> \ --image=<image> \ --annotation <annotation_name>=<annotation_value> \ --label <label_value>=<label_value>
Verify that the OpenShift Container Platform route has been created with the annotation or label that you added by inspecting the output from the following command:
Example command for verification
$ oc get routes.route.openshift.io \ -l serving.knative.openshift.io/ingressName=<service_name> \ 1 -l serving.knative.openshift.io/ingressNamespace=<service_namespace> \ 2 -n knative-serving-ingress -o yaml \ | grep -e "<label_name>: \"<label_value>\"" -e "<annotation_name>: <annotation_value>" 3
4.5.3. Configuring routes for Knative services
If you want to configure a Knative service to use your TLS certificate on OpenShift Container Platform, you must disable the automatic creation of a route for the service by the OpenShift Serverless Operator and instead manually create a route for the service.
When you complete the following procedure, the default OpenShift Container Platform route in the knative-serving-ingress
namespace is not created. However, the Knative route for the application is still created in this namespace.
4.5.3.1. Configuring OpenShift Container Platform routes for Knative services
Prerequisites
- The OpenShift Serverless Operator and Knative Serving component must be installed on your OpenShift Container Platform cluster.
-
Install the OpenShift CLI (
oc
).
Procedure
Create a Knative service that includes the
serving.knative.openshift.io/disableRoute=true
annotation:ImportantThe
serving.knative.openshift.io/disableRoute=true
annotation instructs OpenShift Serverless to not automatically create a route for you. However, the service still shows a URL and reaches a status ofReady
. This URL does not work externally until you create your own route with the same hostname as the hostname in the URL.Create a Knative
Service
resource:Example resource
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: <service_name> annotations: serving.knative.openshift.io/disableRoute: "true" spec: template: spec: containers: - image: <image> ...
Apply the
Service
resource:$ oc apply -f <filename>
Optional. Create a Knative service by using the
kn service create
command:Example
kn
command$ kn service create <service_name> \ --image=gcr.io/knative-samples/helloworld-go \ --annotation serving.knative.openshift.io/disableRoute=true
Verify that no OpenShift Container Platform route has been created for the service:
Example command
$ $ oc get routes.route.openshift.io \ -l serving.knative.openshift.io/ingressName=$KSERVICE_NAME \ -l serving.knative.openshift.io/ingressNamespace=$KSERVICE_NAMESPACE \ -n knative-serving-ingress
You will see the following output:
No resources found in knative-serving-ingress namespace.
Create a
Route
resource in theknative-serving-ingress
namespace:apiVersion: route.openshift.io/v1 kind: Route metadata: annotations: haproxy.router.openshift.io/timeout: 600s 1 name: <route_name> 2 namespace: knative-serving-ingress 3 spec: host: <service_host> 4 port: targetPort: http2 to: kind: Service name: kourier weight: 100 tls: insecureEdgeTerminationPolicy: Allow termination: edge 5 key: |- -----BEGIN PRIVATE KEY----- [...] -----END PRIVATE KEY----- certificate: |- -----BEGIN CERTIFICATE----- [...] -----END CERTIFICATE----- caCertificate: |- -----BEGIN CERTIFICATE----- [...] -----END CERTIFICATE---- wildcardPolicy: None
- 1
- The timeout value for the OpenShift Container Platform route. You must set the same value as the
max-revision-timeout-seconds
setting (600s
by default). - 2
- The name of the OpenShift Container Platform route.
- 3
- The namespace for the OpenShift Container Platform route. This must be
knative-serving-ingress
. - 4
- The hostname for external access. You can set this to
<service_name>-<service_namespace>.<domain>
. - 5
- The certificates you want to use. Currently, only
edge
termination is supported.
Apply the
Route
resource:$ oc apply -f <filename>
4.5.4. Global HTTPS redirection
HTTPS redirection provides redirection for incoming HTTP requests. These redirected HTTP requests are encrypted. You can enable HTTPS redirection for all services on the cluster by configuring the httpProtocol
spec for the KnativeServing
custom resource (CR).
4.5.4.1. HTTPS redirection global settings
Example KnativeServing
CR that enables HTTPS redirection
apiVersion: operator.knative.dev/v1beta1 kind: KnativeServing metadata: name: knative-serving spec: config: network: httpProtocol: "redirected" ...
4.5.5. URL scheme for external routes
The URL scheme of external routes defaults to HTTPS for enhanced security. This scheme is determined by the default-external-scheme
key in the KnativeServing
custom resource (CR) spec.
4.5.5.1. Setting the URL scheme for external routes
Default spec
... spec: config: network: default-external-scheme: "https" ...
You can override the default spec to use HTTP by modifying the default-external-scheme
key:
HTTP override spec
... spec: config: network: default-external-scheme: "http" ...
4.5.6. HTTPS redirection per service
You can enable or disable HTTPS redirection for a service by configuring the networking.knative.dev/http-option
annotation.
4.5.6.1. Redirecting HTTPS for a service
The following example shows how you can use this annotation in a Knative Service
YAML object:
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: example namespace: default annotations: networking.knative.dev/http-option: "redirected" spec: ...
4.5.7. Cluster local availability
By default, Knative services are published to a public IP address. Being published to a public IP address means that Knative services are public applications, and have a publicly accessible URL.
Publicly accessible URLs are accessible from outside of the cluster. However, developers may need to build back-end services that are only be accessible from inside the cluster, known as private services. Developers can label individual services in the cluster with the networking.knative.dev/visibility=cluster-local
label to make them private.
For OpenShift Serverless 1.15.0 and newer versions, the serving.knative.dev/visibility
label is no longer available. You must update existing services to use the networking.knative.dev/visibility
label instead.
4.5.7.1. Setting cluster availability to cluster local
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
- You have created a Knative service.
Procedure
Set the visibility for your service by adding the
networking.knative.dev/visibility=cluster-local
label:$ oc label ksvc <service_name> networking.knative.dev/visibility=cluster-local
Verification
Check that the URL for your service is now in the format
http://<service_name>.<namespace>.svc.cluster.local
, by entering the following command and reviewing the output:$ oc get ksvc
Example output
NAME URL LATESTCREATED LATESTREADY READY REASON hello http://hello.default.svc.cluster.local hello-tx2g7 hello-tx2g7 True
4.5.7.2. Enabling TLS authentication for cluster local services
For cluster local services, the Kourier local gateway kourier-internal
is used. If you want to use TLS traffic against the Kourier local gateway, you must configure your own server certificates in the local gateway.
Prerequisites
- You have installed the OpenShift Serverless Operator and Knative Serving.
- You have administrator permissions.
-
You have installed the OpenShift (
oc
) CLI.
Procedure
Deploy server certificates in the
knative-serving-ingress
namespace:$ export san="knative"
NoteSubject Alternative Name (SAN) validation is required so that these certificates can serve the request to
<app_name>.<namespace>.svc.cluster.local
.Generate a root key and certificate:
$ openssl req -x509 -sha256 -nodes -days 365 -newkey rsa:2048 \ -subj '/O=Example/CN=Example' \ -keyout ca.key \ -out ca.crt
Generate a server key that uses SAN validation:
$ openssl req -out tls.csr -newkey rsa:2048 -nodes -keyout tls.key \ -subj "/CN=Example/O=Example" \ -addext "subjectAltName = DNS:$san"
Create server certificates:
$ openssl x509 -req -extfile <(printf "subjectAltName=DNS:$san") \ -days 365 -in tls.csr \ -CA ca.crt -CAkey ca.key -CAcreateserial -out tls.crt
Configure a secret for the Kourier local gateway:
Deploy a secret in
knative-serving-ingress
namespace from the certificates created by the previous steps:$ oc create -n knative-serving-ingress secret tls server-certs \ --key=tls.key \ --cert=tls.crt --dry-run=client -o yaml | oc apply -f -
Update the
KnativeServing
custom resource (CR) spec to use the secret that was created by the Kourier gateway:Example KnativeServing CR
... spec: config: kourier: cluster-cert-secret: server-certs ...
The Kourier controller sets the certificate without restarting the service, so that you do not need to restart the pod.
You can access the Kourier internal service with TLS through port 443
by mounting and using the ca.crt
from the client.
4.5.8. Kourier Gateway service type
The Kourier Gateway is exposed by default as the ClusterIP
service type. This service type is determined by the service-type
ingress spec in the KnativeServing
custom resource (CR).
Default spec
... spec: ingress: kourier: service-type: ClusterIP ...
4.5.8.1. Setting the Kourier Gateway service type
You can override the default service type to use a load balancer service type instead by modifying the service-type
spec:
LoadBalancer override spec
... spec: ingress: kourier: service-type: LoadBalancer ...
4.5.9. Using HTTP2 and gRPC
OpenShift Serverless supports only insecure or edge-terminated routes. Insecure or edge-terminated routes do not support HTTP2 on OpenShift Container Platform. These routes also do not support gRPC because gRPC is transported by HTTP2. If you use these protocols in your application, you must call the application using the ingress gateway directly. To do this you must find the ingress gateway’s public address and the application’s specific host.
4.5.9.1. Interacting with a serverless application using HTTP2 and gRPC
This method applies to OpenShift Container Platform 4.10 and later. For older versions, see the following section.
Prerequisites
- Install OpenShift Serverless Operator and Knative Serving on your cluster.
-
Install the OpenShift CLI (
oc
). - Create a Knative service.
- Upgrade OpenShift Container Platform 4.10 or later.
- Enable HTTP/2 on OpenShift Ingress controller.
Procedure
Add the
serverless.openshift.io/default-enable-http2=true
annotation to theKnativeServing
Custom Resource:$ oc annotate knativeserving <your_knative_CR> -n knative-serving serverless.openshift.io/default-enable-http2=true
After the annotation is added, you can verify that the
appProtocol
value of the Kourier service ish2c
:$ oc get svc -n knative-serving-ingress kourier -o jsonpath="{.spec.ports[0].appProtocol}"
Example output
h2c
Now you can use the gRPC framework over the HTTP/2 protocol for external traffic, for example:
import "google.golang.org/grpc" grpc.Dial( YOUR_URL, 1 grpc.WithTransportCredentials(insecure.NewCredentials())), 2 )
Additional resources
4.5.9.2. Interacting with a serverless application using HTTP2 and gRPC in OpenShift Container Platform 4.9 and older
This method needs to expose Kourier Gateway using the LoadBalancer
service type. You can configure this by adding the following YAML to your KnativeServing
custom resource definition (CRD):
... spec: ingress: kourier: service-type: LoadBalancer ...
Prerequisites
- Install OpenShift Serverless Operator and Knative Serving on your cluster.
-
Install the OpenShift CLI (
oc
). - Create a Knative service.
Procedure
- Find the application host. See the instructions in Verifying your serverless application deployment.
Find the ingress gateway’s public address:
$ oc -n knative-serving-ingress get svc kourier
Example output
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE kourier LoadBalancer 172.30.51.103 a83e86291bcdd11e993af02b7a65e514-33544245.us-east-1.elb.amazonaws.com 80:31380/TCP,443:31390/TCP 67m
The public address is surfaced in the
EXTERNAL-IP
field, and in this case isa83e86291bcdd11e993af02b7a65e514-33544245.us-east-1.elb.amazonaws.com
.Manually set the host header of your HTTP request to the application’s host, but direct the request itself against the public address of the ingress gateway.
$ curl -H "Host: hello-default.example.com" a83e86291bcdd11e993af02b7a65e514-33544245.us-east-1.elb.amazonaws.com
Example output
Hello Serverless!
You can also make a direct gRPC request against the ingress gateway:
import "google.golang.org/grpc" grpc.Dial( "a83e86291bcdd11e993af02b7a65e514-33544245.us-east-1.elb.amazonaws.com:80", grpc.WithAuthority("hello-default.example.com:80"), grpc.WithInsecure(), )
NoteEnsure that you append the respective port, 80 by default, to both hosts as shown in the previous example.
4.6. Configuring access to Knative services
4.6.1. Configuring JSON Web Token authentication for Knative services
OpenShift Serverless does not currently have user-defined authorization features. To add user-defined authorization to your deployment, you must integrate OpenShift Serverless with Red Hat OpenShift Service Mesh, and then configure JSON Web Token (JWT) authentication and sidecar injection for Knative services.
4.6.2. Using JSON Web Token authentication with Service Mesh 2.x
You can use JSON Web Token (JWT) authentication with Knative services by using Service Mesh 2.x and OpenShift Serverless. To do this, you must create authentication requests and policies in the application namespace that is a member of the ServiceMeshMemberRoll
object. You must also enable sidecar injection for the service.
4.6.2.1. Configuring JSON Web Token authentication for Service Mesh 2.x and OpenShift Serverless
Adding sidecar injection to pods in system namespaces, such as knative-serving
and knative-serving-ingress
, is not supported when Kourier is enabled.
If you require sidecar injection for pods in these namespaces, see the OpenShift Serverless documentation on Integrating Service Mesh with OpenShift Serverless natively.
Prerequisites
- You have installed the OpenShift Serverless Operator, Knative Serving, and Red Hat OpenShift Service Mesh on your cluster.
-
Install the OpenShift CLI (
oc
). - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Add the
sidecar.istio.io/inject="true"
annotation to your service:Example service
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: <service_name> spec: template: metadata: annotations: sidecar.istio.io/inject: "true" 1 sidecar.istio.io/rewriteAppHTTPProbers: "true" 2 ...
Apply the
Service
resource:$ oc apply -f <filename>
Create a
RequestAuthentication
resource in each serverless application namespace that is a member in theServiceMeshMemberRoll
object:apiVersion: security.istio.io/v1beta1 kind: RequestAuthentication metadata: name: jwt-example namespace: <namespace> spec: jwtRules: - issuer: testing@secure.istio.io jwksUri: https://raw.githubusercontent.com/istio/istio/release-1.8/security/tools/jwt/samples/jwks.json
Apply the
RequestAuthentication
resource:$ oc apply -f <filename>
Allow access to the
RequestAuthenticaton
resource from system pods for each serverless application namespace that is a member in theServiceMeshMemberRoll
object, by creating the followingAuthorizationPolicy
resource:apiVersion: security.istio.io/v1beta1 kind: AuthorizationPolicy metadata: name: allowlist-by-paths namespace: <namespace> spec: action: ALLOW rules: - to: - operation: paths: - /metrics 1 - /healthz 2
Apply the
AuthorizationPolicy
resource:$ oc apply -f <filename>
For each serverless application namespace that is a member in the
ServiceMeshMemberRoll
object, create the followingAuthorizationPolicy
resource:apiVersion: security.istio.io/v1beta1 kind: AuthorizationPolicy metadata: name: require-jwt namespace: <namespace> spec: action: ALLOW rules: - from: - source: requestPrincipals: ["testing@secure.istio.io/testing@secure.istio.io"]
Apply the
AuthorizationPolicy
resource:$ oc apply -f <filename>
Verification
If you try to use a
curl
request to get the Knative service URL, it is denied:Example command
$ curl http://hello-example-1-default.apps.mycluster.example.com/
Example output
RBAC: access denied
Verify the request with a valid JWT.
Get the valid JWT token:
$ TOKEN=$(curl https://raw.githubusercontent.com/istio/istio/release-1.8/security/tools/jwt/samples/demo.jwt -s) && echo "$TOKEN" | cut -d '.' -f2 - | base64 --decode -
Access the service by using the valid token in the
curl
request header:$ curl -H "Authorization: Bearer $TOKEN" http://hello-example-1-default.apps.example.com
The request is now allowed:
Example output
Hello OpenShift!
4.6.3. Using JSON Web Token authentication with Service Mesh 1.x
You can use JSON Web Token (JWT) authentication with Knative services by using Service Mesh 1.x and OpenShift Serverless. To do this, you must create a policy in the application namespace that is a member of the ServiceMeshMemberRoll
object. You must also enable sidecar injection for the service.
4.6.3.1. Configuring JSON Web Token authentication for Service Mesh 1.x and OpenShift Serverless
Adding sidecar injection to pods in system namespaces, such as knative-serving
and knative-serving-ingress
, is not supported when Kourier is enabled.
If you require sidecar injection for pods in these namespaces, see the OpenShift Serverless documentation on Integrating Service Mesh with OpenShift Serverless natively.
Prerequisites
- You have installed the OpenShift Serverless Operator, Knative Serving, and Red Hat OpenShift Service Mesh on your cluster.
-
Install the OpenShift CLI (
oc
). - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Add the
sidecar.istio.io/inject="true"
annotation to your service:Example service
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: <service_name> spec: template: metadata: annotations: sidecar.istio.io/inject: "true" 1 sidecar.istio.io/rewriteAppHTTPProbers: "true" 2 ...
Apply the
Service
resource:$ oc apply -f <filename>
Create a policy in a serverless application namespace which is a member in the
ServiceMeshMemberRoll
object, that only allows requests with valid JSON Web Tokens (JWT):ImportantThe paths
/metrics
and/healthz
must be included inexcludedPaths
because they are accessed from system pods in theknative-serving
namespace.apiVersion: authentication.istio.io/v1alpha1 kind: Policy metadata: name: default namespace: <namespace> spec: origins: - jwt: issuer: testing@secure.istio.io jwksUri: "https://raw.githubusercontent.com/istio/istio/release-1.6/security/tools/jwt/samples/jwks.json" triggerRules: - excludedPaths: - prefix: /metrics 1 - prefix: /healthz 2 principalBinding: USE_ORIGIN
Apply the
Policy
resource:$ oc apply -f <filename>
Verification
If you try to use a
curl
request to get the Knative service URL, it is denied:$ curl http://hello-example-default.apps.mycluster.example.com/
Example output
Origin authentication failed.
Verify the request with a valid JWT.
Get the valid JWT token:
$ TOKEN=$(curl https://raw.githubusercontent.com/istio/istio/release-1.6/security/tools/jwt/samples/demo.jwt -s) && echo "$TOKEN" | cut -d '.' -f2 - | base64 --decode -
Access the service by using the valid token in the
curl
request header:$ curl http://hello-example-default.apps.mycluster.example.com/ -H "Authorization: Bearer $TOKEN"
The request is now allowed:
Example output
Hello OpenShift!
4.7. Configuring custom domains for Knative services
4.7.1. Configuring a custom domain for a Knative service
Knative services are automatically assigned a default domain name based on your cluster configuration. For example, <service_name>-<namespace>.example.com
. You can customize the domain for your Knative service by mapping a custom domain name that you own to a Knative service.
You can do this by creating a DomainMapping
resource for the service. You can also create multiple DomainMapping
resources to map multiple domains and subdomains to a single service.
4.7.2. Custom domain mapping
You can customize the domain for your Knative service by mapping a custom domain name that you own to a Knative service. To map a custom domain name to a custom resource (CR), you must create a DomainMapping
CR that maps to an Addressable target CR, such as a Knative service or a Knative route.
4.7.2.1. Creating a custom domain mapping
You can customize the domain for your Knative service by mapping a custom domain name that you own to a Knative service. To map a custom domain name to a custom resource (CR), you must create a DomainMapping
CR that maps to an Addressable target CR, such as a Knative service or a Knative route.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on your cluster.
-
Install the OpenShift CLI (
oc
). - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
You have created a Knative service and control a custom domain that you want to map to that service.
NoteYour custom domain must point to the IP address of the OpenShift Container Platform cluster.
Procedure
Create a YAML file containing the
DomainMapping
CR in the same namespace as the target CR you want to map to:apiVersion: serving.knative.dev/v1alpha1 kind: DomainMapping metadata: name: <domain_name> 1 namespace: <namespace> 2 spec: ref: name: <target_name> 3 kind: <target_type> 4 apiVersion: serving.knative.dev/v1
Example service domain mapping
apiVersion: serving.knative.dev/v1alpha1 kind: DomainMapping metadata: name: example-domain namespace: default spec: ref: name: example-service kind: Service apiVersion: serving.knative.dev/v1
Example route domain mapping
apiVersion: serving.knative.dev/v1alpha1 kind: DomainMapping metadata: name: example-domain namespace: default spec: ref: name: example-route kind: Route apiVersion: serving.knative.dev/v1
Apply the
DomainMapping
CR as a YAML file:$ oc apply -f <filename>
4.7.3. Custom domains for Knative services using the Knative CLI
You can customize the domain for your Knative service by mapping a custom domain name that you own to a Knative service. You can use the Knative (kn
) CLI to create a DomainMapping
custom resource (CR) that maps to an Addressable target CR, such as a Knative service or a Knative route.
4.7.3.1. Creating a custom domain mapping by using the Knative CLI
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on your cluster.
You have created a Knative service or route, and control a custom domain that you want to map to that CR.
NoteYour custom domain must point to the DNS of the OpenShift Container Platform cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Map a domain to a CR in the current namespace:
$ kn domain create <domain_mapping_name> --ref <target_name>
Example command
$ kn domain create example-domain-map --ref example-service
The
--ref
flag specifies an Addressable target CR for domain mapping.If a prefix is not provided when using the
--ref
flag, it is assumed that the target is a Knative service in the current namespace.Map a domain to a Knative service in a specified namespace:
$ kn domain create <domain_mapping_name> --ref <ksvc:service_name:service_namespace>
Example command
$ kn domain create example-domain-map --ref ksvc:example-service:example-namespace
Map a domain to a Knative route:
$ kn domain create <domain_mapping_name> --ref <kroute:route_name>
Example command
$ kn domain create example-domain-map --ref kroute:example-route
4.7.4. Domain mapping using the Developer perspective
You can customize the domain for your Knative service by mapping a custom domain name that you own to a Knative service. You can use the Developer perspective of the OpenShift Container Platform web console to map a DomainMapping
custom resource (CR) to a Knative service.
4.7.4.1. Mapping a custom domain to a service by using the Developer perspective
Prerequisites
- You have logged in to the web console.
- You are in the Developer perspective.
- The OpenShift Serverless Operator and Knative Serving are installed on your cluster. This must be completed by a cluster administrator.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
You have created a Knative service and control a custom domain that you want to map to that service.
NoteYour custom domain must point to the IP address of the OpenShift Container Platform cluster.
Procedure
- Navigate to the Topology page.
-
Right-click on the service that you want to map to a domain, and select the Edit option that contains the service name. For example, if the service is named
example-service
, select the Edit example-service option. In the Advanced options section, click Show advanced Routing options.
- If the domain mapping CR that you want to map to the service already exists, you can select it in the Domain mapping list.
-
If you want to create a new domain mapping CR, type the domain name into the box, and select the Create option. For example, if you type in
example.com
, the Create option is Create "example.com".
- Click Save to save the changes to your service.
Verification
- Navigate to the Topology page.
- Click on the service that you have created.
- In the Resources tab of the service information window, you can see the domain you have mapped to the service listed under Domain mappings.
4.7.5. Domain mapping using the Administrator perspective
If you do not want to switch to the Developer perspective in the OpenShift Container Platform web console or use the Knative (kn
) CLI or YAML files, you can use the Administator perspective of the OpenShift Container Platform web console.
4.7.5.1. Mapping a custom domain to a service by using the Administrator perspective
Knative services are automatically assigned a default domain name based on your cluster configuration. For example, <service_name>-<namespace>.example.com
. You can customize the domain for your Knative service by mapping a custom domain name that you own to a Knative service.
You can do this by creating a DomainMapping
resource for the service. You can also create multiple DomainMapping
resources to map multiple domains and subdomains to a single service.
If you have cluster administrator permissions, you can create a DomainMapping
custom resource (CR) by using the Administrator perspective in the OpenShift Container Platform web console.
Prerequisites
- You have logged in to the web console.
- You are in the Administrator perspective.
- You have installed the OpenShift Serverless Operator.
- You have installed Knative Serving.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
You have created a Knative service and control a custom domain that you want to map to that service.
NoteYour custom domain must point to the IP address of the OpenShift Container Platform cluster.
Procedure
- Navigate to CustomResourceDefinitions and use the search box to find the DomainMapping custom resource definition (CRD).
- Click the DomainMapping CRD, then navigate to the Instances tab.
- Click Create DomainMapping.
Modify the YAML for the
DomainMapping
CR so that it includes the following information for your instance:apiVersion: serving.knative.dev/v1alpha1 kind: DomainMapping metadata: name: <domain_name> 1 namespace: <namespace> 2 spec: ref: name: <target_name> 3 kind: <target_type> 4 apiVersion: serving.knative.dev/v1
Example domain mapping to a Knative service
apiVersion: serving.knative.dev/v1alpha1 kind: DomainMapping metadata: name: custom-ksvc-domain.example.com namespace: default spec: ref: name: example-service kind: Service apiVersion: serving.knative.dev/v1
Verification
Access the custom domain by using a
curl
request. For example:Example command
$ curl custom-ksvc-domain.example.com
Example output
Hello OpenShift!
4.7.6. Securing a mapped service using a TLS certificate
4.7.6.1. Securing a service with a custom domain by using a TLS certificate
After you have configured a custom domain for a Knative service, you can use a TLS certificate to secure the mapped service. To do this, you must create a Kubernetes TLS secret, and then update the DomainMapping
CR to use the TLS secret that you have created.
If you use net-istio
for Ingress and enable mTLS via SMCP using security.dataPlane.mtls: true
, Service Mesh deploys DestinationRules
for the *.local
host, which does not allow DomainMapping
for OpenShift Serverless.
To work around this issue, enable mTLS by deploying PeerAuthentication
instead of using security.dataPlane.mtls: true
.
Prerequisites
-
You configured a custom domain for a Knative service and have a working
DomainMapping
CR. - You have a TLS certificate from your Certificate Authority provider or a self-signed certificate.
-
You have obtained the
cert
andkey
files from your Certificate Authority provider, or a self-signed certificate. -
Install the OpenShift CLI (
oc
).
Procedure
Create a Kubernetes TLS secret:
$ oc create secret tls <tls_secret_name> --cert=<path_to_certificate_file> --key=<path_to_key_file>
Add the
networking.internal.knative.dev/certificate-uid: <id>`
label to the Kubernetes TLS secret:$ oc label secret <tls_secret_name> networking.internal.knative.dev/certificate-uid="<id>"
If you are using a third-party secret provider such as cert-manager, you can configure your secret manager to label the Kubernetes TLS secret automatically. Cert-manager users can use the secret template offered to automatically generate secrets with the correct label. In this case, secret filtering is done based on the key only, but this value can carry useful information such as the certificate ID that the secret contains.
NoteThe {cert-manager-operator} is a Technology Preview feature. For more information, see the Installing the {cert-manager-operator} documentation.
Update the
DomainMapping
CR to use the TLS secret that you have created:apiVersion: serving.knative.dev/v1alpha1 kind: DomainMapping metadata: name: <domain_name> namespace: <namespace> spec: ref: name: <service_name> kind: Service apiVersion: serving.knative.dev/v1 # TLS block specifies the secret to be used tls: secretName: <tls_secret_name>
Verification
Verify that the
DomainMapping
CR status isTrue
, and that theURL
column of the output shows the mapped domain with the schemehttps
:$ oc get domainmapping <domain_name>
Example output
NAME URL READY REASON example.com https://example.com True
Optional: If the service is exposed publicly, verify that it is available by running the following command:
$ curl https://<domain_name>
If the certificate is self-signed, skip verification by adding the
-k
flag to thecurl
command.
4.7.6.2. Improving net-kourier memory usage by using secret filtering
By default, the informers implementation for the Kubernetes client-go
library fetches all resources of a particular type. This can lead to a substantial overhead when many resources are available, which can cause the Knative net-kourier
ingress controller to fail on large clusters due to memory leaking. However, a filtering mechanism is available for the Knative net-kourier
ingress controller, which enables the controller to only fetch Knative related secrets. You can enable this mechanism by setting an environment variable to the KnativeServing
custom resource (CR).
If you enable secret filtering, all of your secrets need to be labeled with networking.internal.knative.dev/certificate-uid: "<id>"
. Otherwise, Knative Serving does not detect them, which leads to failures. You must label both new and existing secrets.
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- A project that you created or that you have roles and permissions for to create applications and other workloads in OpenShift Container Platform.
- Install the OpenShift Serverless Operator and Knative Serving.
-
Install the OpenShift CLI (
oc
).
Procedure
Set the
ENABLE_SECRET_INFORMER_FILTERING_BY_CERT_UID
variable totrue
fornet-kourier-controller
in theKnativeServing
CR:Example KnativeServing CR
apiVersion: operator.knative.dev/v1beta1 kind: KnativeServing metadata: name: knative-serving namespace: knative-serving spec: deployments: - env: - container: controller envVars: - name: ENABLE_SECRET_INFORMER_FILTERING_BY_CERT_UID value: 'true' name: net-kourier-controller
4.8. Configuring high availability for Knative services
4.8.1. High availability for Knative services
High availability (HA) is a standard feature of Kubernetes APIs that helps to ensure that APIs stay operational if a disruption occurs. In an HA deployment, if an active controller crashes or is deleted, another controller is readily available. This controller takes over processing of the APIs that were being serviced by the controller that is now unavailable.
HA in OpenShift Serverless is available through leader election, which is enabled by default after the Knative Serving or Eventing control plane is installed. When using a leader election HA pattern, instances of controllers are already scheduled and running inside the cluster before they are required. These controller instances compete to use a shared resource, known as the leader election lock. The instance of the controller that has access to the leader election lock resource at any given time is called the leader.
4.8.2. High availability for Knative services
High availability (HA) is available by default for the Knative Serving activator
, autoscaler
, autoscaler-hpa
, controller
, webhook
, kourier-control
, and kourier-gateway
components, which are configured to have two replicas each by default. You can change the number of replicas for these components by modifying the spec.high-availability.replicas
value in the KnativeServing
custom resource (CR).
4.8.2.1. Configuring high availability replicas for Knative Serving
To specify three minimum replicas for the eligible deployment resources, set the value of the field spec.high-availability.replicas
in the custom resource to 3
.
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- The OpenShift Serverless Operator and Knative Serving are installed on your cluster.
Procedure
- In the OpenShift Container Platform web console Administrator perspective, navigate to OperatorHub → Installed Operators.
-
Select the
knative-serving
namespace. - Click Knative Serving in the list of Provided APIs for the OpenShift Serverless Operator to go to the Knative Serving tab.
Click knative-serving, then go to the YAML tab in the knative-serving page.
Modify the number of replicas in the
KnativeServing
CR:Example YAML
apiVersion: operator.knative.dev/v1beta1 kind: KnativeServing metadata: name: knative-serving namespace: knative-serving spec: high-availability: replicas: 3
Chapter 5. Eventing
5.1. Knative Eventing
Knative Eventing on OpenShift Container Platform enables developers to use an event-driven architecture with serverless applications. An event-driven architecture is based on the concept of decoupled relationships between event producers and event consumers.
Event producers create events, and event sinks, or consumers, receive events. Knative Eventing uses standard HTTP POST requests to send and receive events between event producers and sinks. These events conform to the CloudEvents specifications, which enables creating, parsing, sending, and receiving events in any programming language.
Knative Eventing supports the following use cases:
- Publish an event without creating a consumer
- You can send events to a broker as an HTTP POST, and use binding to decouple the destination configuration from your application that produces events.
- Consume an event without creating a publisher
- You can use a trigger to consume events from a broker based on event attributes. The application receives events as an HTTP POST.
To enable delivery to multiple types of sinks, Knative Eventing defines the following generic interfaces that can be implemented by multiple Kubernetes resources:
- Addressable resources
-
Able to receive and acknowledge an event delivered over HTTP to an address defined in the
status.address.url
field of the event. The KubernetesService
resource also satisfies the addressable interface. - Callable resources
-
Able to receive an event delivered over HTTP and transform it, returning
0
or1
new events in the HTTP response payload. These returned events may be further processed in the same way that events from an external event source are processed.
5.2. Event sources
5.2.1. Event sources
A Knative event source can be any Kubernetes object that generates or imports cloud events, and relays those events to another endpoint, known as a sink. Sourcing events is critical to developing a distributed system that reacts to events.
You can create and manage Knative event sources by using the Developer perspective in the OpenShift Container Platform web console, the Knative (kn
) CLI, or by applying YAML files.
Currently, OpenShift Serverless supports the following event source types:
- API server source
- Brings Kubernetes API server events into Knative. The API server source sends a new event each time a Kubernetes resource is created, updated or deleted.
- Ping source
- Produces events with a fixed payload on a specified cron schedule.
- Kafka event source
- Connects a Kafka cluster to a sink as an event source.
You can also create a custom event source.
5.2.2. Event source in the Administrator perspective
Sourcing events is critical to developing a distributed system that reacts to events.
5.2.2.1. Creating an event source by using the Administrator perspective
A Knative event source can be any Kubernetes object that generates or imports cloud events, and relays those events to another endpoint, known as a sink.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
- You have logged in to the web console and are in the Administrator perspective.
- You have cluster administrator permissions for OpenShift Container Platform.
Procedure
- In the Administrator perspective of the OpenShift Container Platform web console, navigate to Serverless → Eventing.
- In the Create list, select Event Source. You will be directed to the Event Sources page.
- Select the event source type that you want to create.
5.2.3. Creating an API server source
The API server source is an event source that can be used to connect an event sink, such as a Knative service, to the Kubernetes API server. The API server source watches for Kubernetes events and forwards them to the Knative Eventing broker.
5.2.3.1. Creating an API server source by using the web console
After Knative Eventing is installed on your cluster, you can create an API server source by using the web console. Using the OpenShift Container Platform web console provides a streamlined and intuitive user interface to create an event source.
Prerequisites
- You have logged in to the OpenShift Container Platform web console.
- The OpenShift Serverless Operator and Knative Eventing are installed on the cluster.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
You have installed the OpenShift CLI (
oc
).
If you want to re-use an existing service account, you can modify your existing ServiceAccount
resource to include the required permissions instead of creating a new resource.
Create a service account, role, and role binding for the event source as a YAML file:
apiVersion: v1 kind: ServiceAccount metadata: name: events-sa namespace: default 1 --- apiVersion: rbac.authorization.k8s.io/v1 kind: Role metadata: name: event-watcher namespace: default 2 rules: - apiGroups: - "" resources: - events verbs: - get - list - watch --- apiVersion: rbac.authorization.k8s.io/v1 kind: RoleBinding metadata: name: k8s-ra-event-watcher namespace: default 3 roleRef: apiGroup: rbac.authorization.k8s.io kind: Role name: event-watcher subjects: - kind: ServiceAccount name: events-sa namespace: default 4
Apply the YAML file:
$ oc apply -f <filename>
- In the Developer perspective, navigate to +Add → Event Source. The Event Sources page is displayed.
- Optional: If you have multiple providers for your event sources, select the required provider from the Providers list to filter the available event sources from the provider.
- Select ApiServerSource and then click Create Event Source. The Create Event Source page is displayed.
Configure the ApiServerSource settings by using the Form view or YAML view:
NoteYou can switch between the Form view and YAML view. The data is persisted when switching between the views.
-
Enter
v1
as the APIVERSION andEvent
as the KIND. - Select the Service Account Name for the service account that you created.
- Select the Sink for the event source. A Sink can be either a Resource, such as a channel, broker, or service, or a URI.
-
Enter
- Click Create.
Verification
After you have created the API server source, you will see it connected to the service it is sinked to in the Topology view.
If a URI sink is used, modify the URI by right-clicking on URI sink → Edit URI.
Deleting the API server source
- Navigate to the Topology view.
Right-click the API server source and select Delete ApiServerSource.
5.2.3.2. Creating an API server source by using the Knative CLI
You can use the kn source apiserver create
command to create an API server source by using the kn
CLI. Using the kn
CLI to create an API server source provides a more streamlined and intuitive user interface than modifying YAML files directly.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on the cluster.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
You have installed the OpenShift CLI (
oc
). -
You have installed the Knative (
kn
) CLI.
If you want to re-use an existing service account, you can modify your existing ServiceAccount
resource to include the required permissions instead of creating a new resource.
Create a service account, role, and role binding for the event source as a YAML file:
apiVersion: v1 kind: ServiceAccount metadata: name: events-sa namespace: default 1 --- apiVersion: rbac.authorization.k8s.io/v1 kind: Role metadata: name: event-watcher namespace: default 2 rules: - apiGroups: - "" resources: - events verbs: - get - list - watch --- apiVersion: rbac.authorization.k8s.io/v1 kind: RoleBinding metadata: name: k8s-ra-event-watcher namespace: default 3 roleRef: apiGroup: rbac.authorization.k8s.io kind: Role name: event-watcher subjects: - kind: ServiceAccount name: events-sa namespace: default 4
Apply the YAML file:
$ oc apply -f <filename>
Create an API server source that has an event sink. In the following example, the sink is a broker:
$ kn source apiserver create <event_source_name> --sink broker:<broker_name> --resource "event:v1" --service-account <service_account_name> --mode Resource
To check that the API server source is set up correctly, create a Knative service that dumps incoming messages to its log:
$ kn service create <service_name> --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest
If you used a broker as an event sink, create a trigger to filter events from the
default
broker to the service:$ kn trigger create <trigger_name> --sink ksvc:<service_name>
Create events by launching a pod in the default namespace:
$ oc create deployment hello-node --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest
Check that the controller is mapped correctly by inspecting the output generated by the following command:
$ kn source apiserver describe <source_name>
Example output
Name: mysource Namespace: default Annotations: sources.knative.dev/creator=developer, sources.knative.dev/lastModifier=developer Age: 3m ServiceAccountName: events-sa Mode: Resource Sink: Name: default Namespace: default Kind: Broker (eventing.knative.dev/v1) Resources: Kind: event (v1) Controller: false Conditions: OK TYPE AGE REASON ++ Ready 3m ++ Deployed 3m ++ SinkProvided 3m ++ SufficientPermissions 3m ++ EventTypesProvided 3m
Verification
You can verify that the Kubernetes events were sent to Knative by looking at the message dumper function logs.
Get the pods:
$ oc get pods
View the message dumper function logs for the pods:
$ oc logs $(oc get pod -o name | grep event-display) -c user-container
Example output
☁️ cloudevents.Event Validation: valid Context Attributes, specversion: 1.0 type: dev.knative.apiserver.resource.update datacontenttype: application/json ... Data, { "apiVersion": "v1", "involvedObject": { "apiVersion": "v1", "fieldPath": "spec.containers{hello-node}", "kind": "Pod", "name": "hello-node", "namespace": "default", ..... }, "kind": "Event", "message": "Started container", "metadata": { "name": "hello-node.159d7608e3a3572c", "namespace": "default", .... }, "reason": "Started", ... }
Deleting the API server source
Delete the trigger:
$ kn trigger delete <trigger_name>
Delete the event source:
$ kn source apiserver delete <source_name>
Delete the service account, cluster role, and cluster binding:
$ oc delete -f authentication.yaml
5.2.3.2.1. Knative CLI sink flag
When you create an event source by using the Knative (kn
) CLI, you can specify a sink where events are sent to from that resource by using the --sink
flag. The sink can be any addressable or callable resource that can receive incoming events from other resources.
The following example creates a sink binding that uses a service, http://event-display.svc.cluster.local
, as the sink:
Example command using the sink flag
$ kn source binding create bind-heartbeat \
--namespace sinkbinding-example \
--subject "Job:batch/v1:app=heartbeat-cron" \
--sink http://event-display.svc.cluster.local \ 1
--ce-override "sink=bound"
- 1
svc
inhttp://event-display.svc.cluster.local
determines that the sink is a Knative service. Other default sink prefixes includechannel
, andbroker
.
5.2.3.3. Creating an API server source by using YAML files
Creating Knative resources by using YAML files uses a declarative API, which enables you to describe event sources declaratively and in a reproducible manner. To create an API server source by using YAML, you must create a YAML file that defines an ApiServerSource
object, then apply it by using the oc apply
command.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on the cluster.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
You have created the
default
broker in the same namespace as the one defined in the API server source YAML file. -
Install the OpenShift CLI (
oc
).
If you want to re-use an existing service account, you can modify your existing ServiceAccount
resource to include the required permissions instead of creating a new resource.
Create a service account, role, and role binding for the event source as a YAML file:
apiVersion: v1 kind: ServiceAccount metadata: name: events-sa namespace: default 1 --- apiVersion: rbac.authorization.k8s.io/v1 kind: Role metadata: name: event-watcher namespace: default 2 rules: - apiGroups: - "" resources: - events verbs: - get - list - watch --- apiVersion: rbac.authorization.k8s.io/v1 kind: RoleBinding metadata: name: k8s-ra-event-watcher namespace: default 3 roleRef: apiGroup: rbac.authorization.k8s.io kind: Role name: event-watcher subjects: - kind: ServiceAccount name: events-sa namespace: default 4
Apply the YAML file:
$ oc apply -f <filename>
Create an API server source as a YAML file:
apiVersion: sources.knative.dev/v1alpha1 kind: ApiServerSource metadata: name: testevents spec: serviceAccountName: events-sa mode: Resource resources: - apiVersion: v1 kind: Event sink: ref: apiVersion: eventing.knative.dev/v1 kind: Broker name: default
Apply the
ApiServerSource
YAML file:$ oc apply -f <filename>
To check that the API server source is set up correctly, create a Knative service as a YAML file that dumps incoming messages to its log:
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: event-display namespace: default spec: template: spec: containers: - image: quay.io/openshift-knative/knative-eventing-sources-event-display:latest
Apply the
Service
YAML file:$ oc apply -f <filename>
Create a
Trigger
object as a YAML file that filters events from thedefault
broker to the service created in the previous step:apiVersion: eventing.knative.dev/v1 kind: Trigger metadata: name: event-display-trigger namespace: default spec: broker: default subscriber: ref: apiVersion: serving.knative.dev/v1 kind: Service name: event-display
Apply the
Trigger
YAML file:$ oc apply -f <filename>
Create events by launching a pod in the default namespace:
$ oc create deployment hello-node --image=quay.io/openshift-knative/knative-eventing-sources-event-display
Check that the controller is mapped correctly, by entering the following command and inspecting the output:
$ oc get apiserversource.sources.knative.dev testevents -o yaml
Example output
apiVersion: sources.knative.dev/v1alpha1 kind: ApiServerSource metadata: annotations: creationTimestamp: "2020-04-07T17:24:54Z" generation: 1 name: testevents namespace: default resourceVersion: "62868" selfLink: /apis/sources.knative.dev/v1alpha1/namespaces/default/apiserversources/testevents2 uid: 1603d863-bb06-4d1c-b371-f580b4db99fa spec: mode: Resource resources: - apiVersion: v1 controller: false controllerSelector: apiVersion: "" kind: "" name: "" uid: "" kind: Event labelSelector: {} serviceAccountName: events-sa sink: ref: apiVersion: eventing.knative.dev/v1 kind: Broker name: default
Verification
To verify that the Kubernetes events were sent to Knative, you can look at the message dumper function logs.
Get the pods by entering the following command:
$ oc get pods
View the message dumper function logs for the pods by entering the following command:
$ oc logs $(oc get pod -o name | grep event-display) -c user-container
Example output
☁️ cloudevents.Event Validation: valid Context Attributes, specversion: 1.0 type: dev.knative.apiserver.resource.update datacontenttype: application/json ... Data, { "apiVersion": "v1", "involvedObject": { "apiVersion": "v1", "fieldPath": "spec.containers{hello-node}", "kind": "Pod", "name": "hello-node", "namespace": "default", ..... }, "kind": "Event", "message": "Started container", "metadata": { "name": "hello-node.159d7608e3a3572c", "namespace": "default", .... }, "reason": "Started", ... }
Deleting the API server source
Delete the trigger:
$ oc delete -f trigger.yaml
Delete the event source:
$ oc delete -f k8s-events.yaml
Delete the service account, cluster role, and cluster binding:
$ oc delete -f authentication.yaml
5.2.4. Creating a ping source
A ping source is an event source that can be used to periodically send ping events with a constant payload to an event consumer. A ping source can be used to schedule sending events, similar to a timer.
5.2.4.1. Creating a ping source by using the web console
After Knative Eventing is installed on your cluster, you can create a ping source by using the web console. Using the OpenShift Container Platform web console provides a streamlined and intuitive user interface to create an event source.
Prerequisites
- You have logged in to the OpenShift Container Platform web console.
- The OpenShift Serverless Operator, Knative Serving and Knative Eventing are installed on the cluster.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
To verify that the ping source is working, create a simple Knative service that dumps incoming messages to the logs of the service.
- In the Developer perspective, navigate to +Add → YAML.
Copy the example YAML:
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: event-display spec: template: spec: containers: - image: quay.io/openshift-knative/knative-eventing-sources-event-display:latest
- Click Create.
Create a ping source in the same namespace as the service created in the previous step, or any other sink that you want to send events to.
- In the Developer perspective, navigate to +Add → Event Source. The Event Sources page is displayed.
- Optional: If you have multiple providers for your event sources, select the required provider from the Providers list to filter the available event sources from the provider.
Select Ping Source and then click Create Event Source. The Create Event Source page is displayed.
NoteYou can configure the PingSource settings by using the Form view or YAML view and can switch between the views. The data is persisted when switching between the views.
-
Enter a value for Schedule. In this example, the value is
*/2 * * * *
, which creates a PingSource that sends a message every two minutes. - Optional: You can enter a value for Data, which is the message payload.
-
Select a Sink. This can be either a Resource or a URI. In this example, the
event-display
service created in the previous step is used as the Resource sink. - Click Create.
Verification
You can verify that the ping source was created and is connected to the sink by viewing the Topology page.
- In the Developer perspective, navigate to Topology.
View the ping source and sink.
Deleting the ping source
- Navigate to the Topology view.
- Right-click the API server source and select Delete Ping Source.
5.2.4.2. Creating a ping source by using the Knative CLI
You can use the kn source ping create
command to create a ping source by using the Knative (kn
) CLI. Using the Knative CLI to create event sources provides a more streamlined and intuitive user interface than modifying YAML files directly.
Prerequisites
- The OpenShift Serverless Operator, Knative Serving and Knative Eventing are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
Optional: If you want to use the verification steps for this procedure, install the OpenShift CLI (
oc
).
Procedure
To verify that the ping source is working, create a simple Knative service that dumps incoming messages to the service logs:
$ kn service create event-display \ --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest
For each set of ping events that you want to request, create a ping source in the same namespace as the event consumer:
$ kn source ping create test-ping-source \ --schedule "*/2 * * * *" \ --data '{"message": "Hello world!"}' \ --sink ksvc:event-display
Check that the controller is mapped correctly by entering the following command and inspecting the output:
$ kn source ping describe test-ping-source
Example output
Name: test-ping-source Namespace: default Annotations: sources.knative.dev/creator=developer, sources.knative.dev/lastModifier=developer Age: 15s Schedule: */2 * * * * Data: {"message": "Hello world!"} Sink: Name: event-display Namespace: default Resource: Service (serving.knative.dev/v1) Conditions: OK TYPE AGE REASON ++ Ready 8s ++ Deployed 8s ++ SinkProvided 15s ++ ValidSchedule 15s ++ EventTypeProvided 15s ++ ResourcesCorrect 15s
Verification
You can verify that the Kubernetes events were sent to the Knative event sink by looking at the logs of the sink pod.
By default, Knative services terminate their pods if no traffic is received within a 60 second period. The example shown in this guide creates a ping source that sends a message every 2 minutes, so each message should be observed in a newly created pod.
Watch for new pods created:
$ watch oc get pods
Cancel watching the pods using Ctrl+C, then look at the logs of the created pod:
$ oc logs $(oc get pod -o name | grep event-display) -c user-container
Example output
☁️ cloudevents.Event Validation: valid Context Attributes, specversion: 1.0 type: dev.knative.sources.ping source: /apis/v1/namespaces/default/pingsources/test-ping-source id: 99e4f4f6-08ff-4bff-acf1-47f61ded68c9 time: 2020-04-07T16:16:00.000601161Z datacontenttype: application/json Data, { "message": "Hello world!" }
Deleting the ping source
Delete the ping source:
$ kn delete pingsources.sources.knative.dev <ping_source_name>
5.2.4.2.1. Knative CLI sink flag
When you create an event source by using the Knative (kn
) CLI, you can specify a sink where events are sent to from that resource by using the --sink
flag. The sink can be any addressable or callable resource that can receive incoming events from other resources.
The following example creates a sink binding that uses a service, http://event-display.svc.cluster.local
, as the sink:
Example command using the sink flag
$ kn source binding create bind-heartbeat \
--namespace sinkbinding-example \
--subject "Job:batch/v1:app=heartbeat-cron" \
--sink http://event-display.svc.cluster.local \ 1
--ce-override "sink=bound"
- 1
svc
inhttp://event-display.svc.cluster.local
determines that the sink is a Knative service. Other default sink prefixes includechannel
, andbroker
.
5.2.4.3. Creating a ping source by using YAML
Creating Knative resources by using YAML files uses a declarative API, which enables you to describe event sources declaratively and in a reproducible manner. To create a serverless ping source by using YAML, you must create a YAML file that defines a PingSource
object, then apply it by using oc apply
.
Example PingSource
object
apiVersion: sources.knative.dev/v1 kind: PingSource metadata: name: test-ping-source spec: schedule: "*/2 * * * *" 1 data: '{"message": "Hello world!"}' 2 sink: 3 ref: apiVersion: serving.knative.dev/v1 kind: Service name: event-display
- 1
- The schedule of the event specified using CRON expression.
- 2
- The event message body expressed as a JSON encoded data string.
- 3
- These are the details of the event consumer. In this example, we are using a Knative service named
event-display
.
Prerequisites
- The OpenShift Serverless Operator, Knative Serving and Knative Eventing are installed on the cluster.
-
Install the OpenShift CLI (
oc
). - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
To verify that the ping source is working, create a simple Knative service that dumps incoming messages to the service’s logs.
Create a service YAML file:
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: event-display spec: template: spec: containers: - image: quay.io/openshift-knative/knative-eventing-sources-event-display:latest
Create the service:
$ oc apply -f <filename>
For each set of ping events that you want to request, create a ping source in the same namespace as the event consumer.
Create a YAML file for the ping source:
apiVersion: sources.knative.dev/v1 kind: PingSource metadata: name: test-ping-source spec: schedule: "*/2 * * * *" data: '{"message": "Hello world!"}' sink: ref: apiVersion: serving.knative.dev/v1 kind: Service name: event-display
Create the ping source:
$ oc apply -f <filename>
Check that the controller is mapped correctly by entering the following command:
$ oc get pingsource.sources.knative.dev <ping_source_name> -oyaml
Example output
apiVersion: sources.knative.dev/v1 kind: PingSource metadata: annotations: sources.knative.dev/creator: developer sources.knative.dev/lastModifier: developer creationTimestamp: "2020-04-07T16:11:14Z" generation: 1 name: test-ping-source namespace: default resourceVersion: "55257" selfLink: /apis/sources.knative.dev/v1/namespaces/default/pingsources/test-ping-source uid: 3d80d50b-f8c7-4c1b-99f7-3ec00e0a8164 spec: data: '{ value: "hello" }' schedule: '*/2 * * * *' sink: ref: apiVersion: serving.knative.dev/v1 kind: Service name: event-display namespace: default
Verification
You can verify that the Kubernetes events were sent to the Knative event sink by looking at the sink pod’s logs.
By default, Knative services terminate their pods if no traffic is received within a 60 second period. The example shown in this guide creates a PingSource that sends a message every 2 minutes, so each message should be observed in a newly created pod.
Watch for new pods created:
$ watch oc get pods
Cancel watching the pods using Ctrl+C, then look at the logs of the created pod:
$ oc logs $(oc get pod -o name | grep event-display) -c user-container
Example output
☁️ cloudevents.Event Validation: valid Context Attributes, specversion: 1.0 type: dev.knative.sources.ping source: /apis/v1/namespaces/default/pingsources/test-ping-source id: 042ff529-240e-45ee-b40c-3a908129853e time: 2020-04-07T16:22:00.000791674Z datacontenttype: application/json Data, { "message": "Hello world!" }
Deleting the ping source
Delete the ping source:
$ oc delete -f <filename>
Example command
$ oc delete -f ping-source.yaml
5.2.5. Kafka source
You can create a Kafka source that reads events from an Apache Kafka cluster and passes these events to a sink. You can create a Kafka source by using the OpenShift Container Platform web console, the Knative (kn
) CLI, or by creating a KafkaSource
object directly as a YAML file and using the OpenShift CLI (oc
) to apply it.
5.2.5.1. Creating a Kafka event source by using the web console
After Knative Kafka is installed on your cluster, you can create a Kafka source by using the web console. Using the OpenShift Container Platform web console provides a streamlined and intuitive user interface to create a Kafka source.
Prerequisites
-
The OpenShift Serverless Operator, Knative Eventing, and the
KnativeKafka
custom resource are installed on your cluster. - You have logged in to the web console.
- You have access to a Red Hat AMQ Streams (Kafka) cluster that produces the Kafka messages you want to import.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
- In the Developer perspective, navigate to the +Add page and select Event Source.
- In the Event Sources page, select Kafka Source in the Type section.
Configure the Kafka Source settings:
- Add a comma-separated list of Bootstrap Servers.
- Add a comma-separated list of Topics.
- Add a Consumer Group.
- Select the Service Account Name for the service account that you created.
- Select the Sink for the event source. A Sink can be either a Resource, such as a channel, broker, or service, or a URI.
- Enter a Name for the Kafka event source.
- Click Create.
Verification
You can verify that the Kafka event source was created and is connected to the sink by viewing the Topology page.
- In the Developer perspective, navigate to Topology.
View the Kafka event source and sink.
5.2.5.2. Creating a Kafka event source by using the Knative CLI
You can use the kn source kafka create
command to create a Kafka source by using the Knative (kn
) CLI. Using the Knative CLI to create event sources provides a more streamlined and intuitive user interface than modifying YAML files directly.
Prerequisites
-
The OpenShift Serverless Operator, Knative Eventing, Knative Serving, and the
KnativeKafka
custom resource (CR) are installed on your cluster. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
- You have access to a Red Hat AMQ Streams (Kafka) cluster that produces the Kafka messages you want to import.
-
You have installed the Knative (
kn
) CLI. -
Optional: You have installed the OpenShift CLI (
oc
) if you want to use the verification steps in this procedure.
Procedure
To verify that the Kafka event source is working, create a Knative service that dumps incoming events into the service logs:
$ kn service create event-display \ --image quay.io/openshift-knative/knative-eventing-sources-event-display
Create a
KafkaSource
CR:$ kn source kafka create <kafka_source_name> \ --servers <cluster_kafka_bootstrap>.kafka.svc:9092 \ --topics <topic_name> --consumergroup my-consumer-group \ --sink event-display
NoteReplace the placeholder values in this command with values for your source name, bootstrap servers, and topics.
The
--servers
,--topics
, and--consumergroup
options specify the connection parameters to the Kafka cluster. The--consumergroup
option is optional.Optional: View details about the
KafkaSource
CR you created:$ kn source kafka describe <kafka_source_name>
Example output
Name: example-kafka-source Namespace: kafka Age: 1h BootstrapServers: example-cluster-kafka-bootstrap.kafka.svc:9092 Topics: example-topic ConsumerGroup: example-consumer-group Sink: Name: event-display Namespace: default Resource: Service (serving.knative.dev/v1) Conditions: OK TYPE AGE REASON ++ Ready 1h ++ Deployed 1h ++ SinkProvided 1h
Verification steps
Trigger the Kafka instance to send a message to the topic:
$ oc -n kafka run kafka-producer \ -ti --image=quay.io/strimzi/kafka:latest-kafka-2.7.0 --rm=true \ --restart=Never -- bin/kafka-console-producer.sh \ --broker-list <cluster_kafka_bootstrap>:9092 --topic my-topic
Enter the message in the prompt. This command assumes that:
-
The Kafka cluster is installed in the
kafka
namespace. -
The
KafkaSource
object has been configured to use themy-topic
topic.
-
The Kafka cluster is installed in the
Verify that the message arrived by viewing the logs:
$ oc logs $(oc get pod -o name | grep event-display) -c user-container
Example output
☁️ cloudevents.Event Validation: valid Context Attributes, specversion: 1.0 type: dev.knative.kafka.event source: /apis/v1/namespaces/default/kafkasources/example-kafka-source#example-topic subject: partition:46#0 id: partition:46/offset:0 time: 2021-03-10T11:21:49.4Z Extensions, traceparent: 00-161ff3815727d8755848ec01c866d1cd-7ff3916c44334678-00 Data, Hello!
5.2.5.2.1. Knative CLI sink flag
When you create an event source by using the Knative (kn
) CLI, you can specify a sink where events are sent to from that resource by using the --sink
flag. The sink can be any addressable or callable resource that can receive incoming events from other resources.
The following example creates a sink binding that uses a service, http://event-display.svc.cluster.local
, as the sink:
Example command using the sink flag
$ kn source binding create bind-heartbeat \
--namespace sinkbinding-example \
--subject "Job:batch/v1:app=heartbeat-cron" \
--sink http://event-display.svc.cluster.local \ 1
--ce-override "sink=bound"
- 1
svc
inhttp://event-display.svc.cluster.local
determines that the sink is a Knative service. Other default sink prefixes includechannel
, andbroker
.
5.2.5.3. Creating a Kafka event source by using YAML
Creating Knative resources by using YAML files uses a declarative API, which enables you to describe applications declaratively and in a reproducible manner. To create a Kafka source by using YAML, you must create a YAML file that defines a KafkaSource
object, then apply it by using the oc apply
command.
Prerequisites
-
The OpenShift Serverless Operator, Knative Eventing, and the
KnativeKafka
custom resource are installed on your cluster. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
- You have access to a Red Hat AMQ Streams (Kafka) cluster that produces the Kafka messages you want to import.
-
Install the OpenShift CLI (
oc
).
Procedure
Create a
KafkaSource
object as a YAML file:apiVersion: sources.knative.dev/v1beta1 kind: KafkaSource metadata: name: <source_name> spec: consumerGroup: <group_name> 1 bootstrapServers: - <list_of_bootstrap_servers> topics: - <list_of_topics> 2 sink: - <list_of_sinks> 3
ImportantOnly the
v1beta1
version of the API forKafkaSource
objects on OpenShift Serverless is supported. Do not use thev1alpha1
version of this API, as this version is now deprecated.Example
KafkaSource
objectapiVersion: sources.knative.dev/v1beta1 kind: KafkaSource metadata: name: kafka-source spec: consumerGroup: knative-group bootstrapServers: - my-cluster-kafka-bootstrap.kafka:9092 topics: - knative-demo-topic sink: ref: apiVersion: serving.knative.dev/v1 kind: Service name: event-display
Apply the
KafkaSource
YAML file:$ oc apply -f <filename>
Verification
Verify that the Kafka event source was created by entering the following command:
$ oc get pods
Example output
NAME READY STATUS RESTARTS AGE kafkasource-kafka-source-5ca0248f-... 1/1 Running 0 13m
5.2.5.4. Configuring SASL authentication for Kafka sources
Simple Authentication and Security Layer (SASL) is used by Apache Kafka for authentication. If you use SASL authentication on your cluster, users must provide credentials to Knative for communicating with the Kafka cluster; otherwise events cannot be produced or consumed.
Prerequisites
- You have cluster or dedicated administrator permissions on OpenShift Container Platform.
-
The OpenShift Serverless Operator, Knative Eventing, and the
KnativeKafka
CR are installed on your OpenShift Container Platform cluster. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
- You have a username and password for a Kafka cluster.
-
You have chosen the SASL mechanism to use, for example,
PLAIN
,SCRAM-SHA-256
, orSCRAM-SHA-512
. -
If TLS is enabled, you also need the
ca.crt
certificate file for the Kafka cluster. -
You have installed the OpenShift (
oc
) CLI.
Procedure
Create the certificate files as secrets in your chosen namespace:
$ oc create secret -n <namespace> generic <kafka_auth_secret> \ --from-file=ca.crt=caroot.pem \ --from-literal=password="SecretPassword" \ --from-literal=saslType="SCRAM-SHA-512" \ 1 --from-literal=user="my-sasl-user"
- 1
- The SASL type can be
PLAIN
,SCRAM-SHA-256
, orSCRAM-SHA-512
.
Create or modify your Kafka source so that it contains the following
spec
configuration:apiVersion: sources.knative.dev/v1beta1 kind: KafkaSource metadata: name: example-source spec: ... net: sasl: enable: true user: secretKeyRef: name: <kafka_auth_secret> key: user password: secretKeyRef: name: <kafka_auth_secret> key: password type: secretKeyRef: name: <kafka_auth_secret> key: saslType tls: enable: true caCert: 1 secretKeyRef: name: <kafka_auth_secret> key: ca.crt ...
- 1
- The
caCert
spec is not required if you are using a public cloud Kafka service, such as Red Hat OpenShift Streams for Apache Kafka.
5.2.6. Custom event sources
If you need to ingress events from an event producer that is not included in Knative, or from a producer that emits events which are not in the CloudEvent
format, you can do this by creating a custom event source. You can create a custom event source by using one of the following methods:
-
Use a
PodSpecable
object as an event source, by creating a sink binding. - Use a container as an event source, by creating a container source.
5.2.6.1. Sink binding
The SinkBinding
object supports decoupling event production from delivery addressing. Sink binding is used to connect event producers to an event consumer, or sink. An event producer is a Kubernetes resource that embeds a PodSpec
template and produces events. A sink is an addressable Kubernetes object that can receive events.
The SinkBinding
object injects environment variables into the PodTemplateSpec
of the sink, which means that the application code does not need to interact directly with the Kubernetes API to locate the event destination. These environment variables are as follows:
K_SINK
- The URL of the resolved sink.
K_CE_OVERRIDES
- A JSON object that specifies overrides to the outbound event.
The SinkBinding
object currently does not support custom revision names for services.
5.2.6.1.1. Creating a sink binding by using YAML
Creating Knative resources by using YAML files uses a declarative API, which enables you to describe event sources declaratively and in a reproducible manner. To create a sink binding by using YAML, you must create a YAML file that defines an SinkBinding
object, then apply it by using the oc apply
command.
Prerequisites
- The OpenShift Serverless Operator, Knative Serving and Knative Eventing are installed on the cluster.
-
Install the OpenShift CLI (
oc
). - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
To check that sink binding is set up correctly, create a Knative event display service, or event sink, that dumps incoming messages to its log.
Create a service YAML file:
Example service YAML file
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: event-display spec: template: spec: containers: - image: quay.io/openshift-knative/knative-eventing-sources-event-display:latest
Create the service:
$ oc apply -f <filename>
Create a sink binding instance that directs events to the service.
Create a sink binding YAML file:
Example service YAML file
apiVersion: sources.knative.dev/v1alpha1 kind: SinkBinding metadata: name: bind-heartbeat spec: subject: apiVersion: batch/v1 kind: Job 1 selector: matchLabels: app: heartbeat-cron sink: ref: apiVersion: serving.knative.dev/v1 kind: Service name: event-display
- 1
- In this example, any Job with the label
app: heartbeat-cron
will be bound to the event sink.
Create the sink binding:
$ oc apply -f <filename>
Create a
CronJob
object.Create a cron job YAML file:
Example cron job YAML file
apiVersion: batch/v1 kind: CronJob metadata: name: heartbeat-cron spec: # Run every minute schedule: "* * * * *" jobTemplate: metadata: labels: app: heartbeat-cron bindings.knative.dev/include: "true" spec: template: spec: restartPolicy: Never containers: - name: single-heartbeat image: quay.io/openshift-knative/heartbeats:latest args: - --period=1 env: - name: ONE_SHOT value: "true" - name: POD_NAME valueFrom: fieldRef: fieldPath: metadata.name - name: POD_NAMESPACE valueFrom: fieldRef: fieldPath: metadata.namespace
ImportantTo use sink binding, you must manually add a
bindings.knative.dev/include=true
label to your Knative resources.For example, to add this label to a
CronJob
resource, add the following lines to theJob
resource YAML definition:jobTemplate: metadata: labels: app: heartbeat-cron bindings.knative.dev/include: "true"
Create the cron job:
$ oc apply -f <filename>
Check that the controller is mapped correctly by entering the following command and inspecting the output:
$ oc get sinkbindings.sources.knative.dev bind-heartbeat -oyaml
Example output
spec: sink: ref: apiVersion: serving.knative.dev/v1 kind: Service name: event-display namespace: default subject: apiVersion: batch/v1 kind: Job namespace: default selector: matchLabels: app: heartbeat-cron
Verification
You can verify that the Kubernetes events were sent to the Knative event sink by looking at the message dumper function logs.
Enter the command:
$ oc get pods
Enter the command:
$ oc logs $(oc get pod -o name | grep event-display) -c user-container
Example output
☁️ cloudevents.Event Validation: valid Context Attributes, specversion: 1.0 type: dev.knative.eventing.samples.heartbeat source: https://knative.dev/eventing-contrib/cmd/heartbeats/#event-test/mypod id: 2b72d7bf-c38f-4a98-a433-608fbcdd2596 time: 2019-10-18T15:23:20.809775386Z contenttype: application/json Extensions, beats: true heart: yes the: 42 Data, { "id": 1, "label": "" }
5.2.6.1.2. Creating a sink binding by using the Knative CLI
You can use the kn source binding create
command to create a sink binding by using the Knative (kn
) CLI. Using the Knative CLI to create event sources provides a more streamlined and intuitive user interface than modifying YAML files directly.
Prerequisites
- The OpenShift Serverless Operator, Knative Serving and Knative Eventing are installed on the cluster.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
Install the Knative (
kn
) CLI. -
Install the OpenShift CLI (
oc
).
The following procedure requires you to create YAML files.
If you change the names of the YAML files from those used in the examples, you must ensure that you also update the corresponding CLI commands.
Procedure
To check that sink binding is set up correctly, create a Knative event display service, or event sink, that dumps incoming messages to its log:
$ kn service create event-display --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest
Create a sink binding instance that directs events to the service:
$ kn source binding create bind-heartbeat --subject Job:batch/v1:app=heartbeat-cron --sink ksvc:event-display
Create a
CronJob
object.Create a cron job YAML file:
Example cron job YAML file
apiVersion: batch/v1 kind: CronJob metadata: name: heartbeat-cron spec: # Run every minute schedule: "* * * * *" jobTemplate: metadata: labels: app: heartbeat-cron bindings.knative.dev/include: "true" spec: template: spec: restartPolicy: Never containers: - name: single-heartbeat image: quay.io/openshift-knative/heartbeats:latest args: - --period=1 env: - name: ONE_SHOT value: "true" - name: POD_NAME valueFrom: fieldRef: fieldPath: metadata.name - name: POD_NAMESPACE valueFrom: fieldRef: fieldPath: metadata.namespace
ImportantTo use sink binding, you must manually add a
bindings.knative.dev/include=true
label to your Knative CRs.For example, to add this label to a
CronJob
CR, add the following lines to theJob
CR YAML definition:jobTemplate: metadata: labels: app: heartbeat-cron bindings.knative.dev/include: "true"
Create the cron job:
$ oc apply -f <filename>
Check that the controller is mapped correctly by entering the following command and inspecting the output:
$ kn source binding describe bind-heartbeat
Example output
Name: bind-heartbeat Namespace: demo-2 Annotations: sources.knative.dev/creator=minikube-user, sources.knative.dev/lastModifier=minikub ... Age: 2m Subject: Resource: job (batch/v1) Selector: app: heartbeat-cron Sink: Name: event-display Resource: Service (serving.knative.dev/v1) Conditions: OK TYPE AGE REASON ++ Ready 2m
Verification
You can verify that the Kubernetes events were sent to the Knative event sink by looking at the message dumper function logs.
View the message dumper function logs by entering the following commands:
$ oc get pods
$ oc logs $(oc get pod -o name | grep event-display) -c user-container
Example output
☁️ cloudevents.Event Validation: valid Context Attributes, specversion: 1.0 type: dev.knative.eventing.samples.heartbeat source: https://knative.dev/eventing-contrib/cmd/heartbeats/#event-test/mypod id: 2b72d7bf-c38f-4a98-a433-608fbcdd2596 time: 2019-10-18T15:23:20.809775386Z contenttype: application/json Extensions, beats: true heart: yes the: 42 Data, { "id": 1, "label": "" }
5.2.6.1.2.1. Knative CLI sink flag
When you create an event source by using the Knative (kn
) CLI, you can specify a sink where events are sent to from that resource by using the --sink
flag. The sink can be any addressable or callable resource that can receive incoming events from other resources.
The following example creates a sink binding that uses a service, http://event-display.svc.cluster.local
, as the sink:
Example command using the sink flag
$ kn source binding create bind-heartbeat \
--namespace sinkbinding-example \
--subject "Job:batch/v1:app=heartbeat-cron" \
--sink http://event-display.svc.cluster.local \ 1
--ce-override "sink=bound"
- 1
svc
inhttp://event-display.svc.cluster.local
determines that the sink is a Knative service. Other default sink prefixes includechannel
, andbroker
.
5.2.6.1.3. Creating a sink binding by using the web console
After Knative Eventing is installed on your cluster, you can create a sink binding by using the web console. Using the OpenShift Container Platform web console provides a streamlined and intuitive user interface to create an event source.
Prerequisites
- You have logged in to the OpenShift Container Platform web console.
- The OpenShift Serverless Operator, Knative Serving, and Knative Eventing are installed on your OpenShift Container Platform cluster.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Create a Knative service to use as a sink:
- In the Developer perspective, navigate to +Add → YAML.
Copy the example YAML:
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: event-display spec: template: spec: containers: - image: quay.io/openshift-knative/knative-eventing-sources-event-display:latest
- Click Create.
Create a
CronJob
resource that is used as an event source and sends an event every minute.- In the Developer perspective, navigate to +Add → YAML.
Copy the example YAML:
apiVersion: batch/v1 kind: CronJob metadata: name: heartbeat-cron spec: # Run every minute schedule: "*/1 * * * *" jobTemplate: metadata: labels: app: heartbeat-cron bindings.knative.dev/include: true 1 spec: template: spec: restartPolicy: Never containers: - name: single-heartbeat image: quay.io/openshift-knative/heartbeats args: - --period=1 env: - name: ONE_SHOT value: "true" - name: POD_NAME valueFrom: fieldRef: fieldPath: metadata.name - name: POD_NAMESPACE valueFrom: fieldRef: fieldPath: metadata.namespace
- 1
- Ensure that you include the
bindings.knative.dev/include: true
label. The default namespace selection behavior of OpenShift Serverless uses inclusion mode.
- Click Create.
Create a sink binding in the same namespace as the service created in the previous step, or any other sink that you want to send events to.
- In the Developer perspective, navigate to +Add → Event Source. The Event Sources page is displayed.
- Optional: If you have multiple providers for your event sources, select the required provider from the Providers list to filter the available event sources from the provider.
Select Sink Binding and then click Create Event Source. The Create Event Source page is displayed.
NoteYou can configure the Sink Binding settings by using the Form view or YAML view and can switch between the views. The data is persisted when switching between the views.
-
In the apiVersion field enter
batch/v1
. In the Kind field enter
Job
.NoteThe
CronJob
kind is not supported directly by OpenShift Serverless sink binding, so the Kind field must target theJob
objects created by the cron job, rather than the cron job object itself.-
Select a Sink. This can be either a Resource or a URI. In this example, the
event-display
service created in the previous step is used as the Resource sink. In the Match labels section:
-
Enter
app
in the Name field. Enter
heartbeat-cron
in the Value field.NoteThe label selector is required when using cron jobs with sink binding, rather than the resource name. This is because jobs created by a cron job do not have a predictable name, and contain a randomly generated string in their name. For example,
hearthbeat-cron-1cc23f
.
-
Enter
- Click Create.
Verification
You can verify that the sink binding, sink, and cron job have been created and are working correctly by viewing the Topology page and pod logs.
- In the Developer perspective, navigate to Topology.
View the sink binding, sink, and heartbeats cron job.
- Observe that successful jobs are being registered by the cron job once the sink binding is added. This means that the sink binding is successfully reconfiguring the jobs created by the cron job.
-
Browse the logs of the
event-display
service pod to see events produced by the heartbeats cron job.
5.2.6.1.4. Sink binding reference
You can use a PodSpecable
object as an event source by creating a sink binding. You can configure multiple parameters when creating a SinkBinding
object.
SinkBinding
objects support the following parameters:
Field | Description | Required or optional |
---|---|---|
|
Specifies the API version, for example | Required |
|
Identifies this resource object as a | Required |
|
Specifies metadata that uniquely identifies the | Required |
|
Specifies the configuration information for this | Required |
| A reference to an object that resolves to a URI to use as the sink. | Required |
| References the resources for which the runtime contract is augmented by binding implementations. | Required |
| Defines overrides to control the output format and modifications to the event sent to the sink. | Optional |
5.2.6.1.4.1. Subject parameter
The Subject
parameter references the resources for which the runtime contract is augmented by binding implementations. You can configure multiple fields for a Subject
definition.
The Subject
definition supports the following fields:
Field | Description | Required or optional |
---|---|---|
| API version of the referent. | Required |
| Kind of the referent. | Required |
| Namespace of the referent. If omitted, this defaults to the namespace of the object. | Optional |
| Name of the referent. |
Do not use if you configure |
| Selector of the referents. |
Do not use if you configure |
| A list of label selector requirements. |
Only use one of either |
| The label key that the selector applies to. |
Required if using |
|
Represents a key’s relationship to a set of values. Valid operators are |
Required if using |
|
An array of string values. If the |
Required if using |
|
A map of key-value pairs. Each key-value pair in the |
Only use one of either |
Subject parameter examples
Given the following YAML, the Deployment
object named mysubject
in the default
namespace is selected:
apiVersion: sources.knative.dev/v1 kind: SinkBinding metadata: name: bind-heartbeat spec: subject: apiVersion: apps/v1 kind: Deployment namespace: default name: mysubject ...
Given the following YAML, any Job
object with the label working=example
in the default
namespace is selected:
apiVersion: sources.knative.dev/v1 kind: SinkBinding metadata: name: bind-heartbeat spec: subject: apiVersion: batch/v1 kind: Job namespace: default selector: matchLabels: working: example ...
Given the following YAML, any Pod
object with the label working=example
or working=sample
in the default
namespace is selected:
apiVersion: sources.knative.dev/v1 kind: SinkBinding metadata: name: bind-heartbeat spec: subject: apiVersion: v1 kind: Pod namespace: default selector: - matchExpression: key: working operator: In values: - example - sample ...
5.2.6.1.4.2. CloudEvent overrides
A ceOverrides
definition provides overrides that control the CloudEvent’s output format and modifications sent to the sink. You can configure multiple fields for the ceOverrides
definition.
A ceOverrides
definition supports the following fields:
Field | Description | Required or optional |
---|---|---|
|
Specifies which attributes are added or overridden on the outbound event. Each | Optional |
Only valid CloudEvent
attribute names are allowed as extensions. You cannot set the spec defined attributes from the extensions override configuration. For example, you can not modify the type
attribute.
CloudEvent Overrides example
apiVersion: sources.knative.dev/v1 kind: SinkBinding metadata: name: bind-heartbeat spec: ... ceOverrides: extensions: extra: this is an extra attribute additional: 42
This sets the K_CE_OVERRIDES
environment variable on the subject
:
Example output
{ "extensions": { "extra": "this is an extra attribute", "additional": "42" } }
5.2.6.1.4.3. The include label
To use a sink binding, you need to do assign the bindings.knative.dev/include: "true"
label to either the resource or the namespace that the resource is included in. If the resource definition does not include the label, a cluster administrator can attach it to the namespace by running:
$ oc label namespace <namespace> bindings.knative.dev/include=true
5.2.6.2. Container source
Container sources create a container image that generates events and sends events to a sink. You can use a container source to create a custom event source, by creating a container image and a ContainerSource
object that uses your image URI.
5.2.6.2.1. Guidelines for creating a container image
Two environment variables are injected by the container source controller: K_SINK
and K_CE_OVERRIDES
. These variables are resolved from the sink
and ceOverrides
spec, respectively. Events are sent to the sink URI specified in the K_SINK
environment variable. The message must be sent as a POST
using the CloudEvent
HTTP format.
Example container images
The following is an example of a heartbeats container image:
package main import ( "context" "encoding/json" "flag" "fmt" "log" "os" "strconv" "time" duckv1 "knative.dev/pkg/apis/duck/v1" cloudevents "github.com/cloudevents/sdk-go/v2" "github.com/kelseyhightower/envconfig" ) type Heartbeat struct { Sequence int `json:"id"` Label string `json:"label"` } var ( eventSource string eventType string sink string label string periodStr string ) func init() { flag.StringVar(&eventSource, "eventSource", "", "the event-source (CloudEvents)") flag.StringVar(&eventType, "eventType", "dev.knative.eventing.samples.heartbeat", "the event-type (CloudEvents)") flag.StringVar(&sink, "sink", "", "the host url to heartbeat to") flag.StringVar(&label, "label", "", "a special label") flag.StringVar(&periodStr, "period", "5", "the number of seconds between heartbeats") } type envConfig struct { // Sink URL where to send heartbeat cloud events Sink string `envconfig:"K_SINK"` // CEOverrides are the CloudEvents overrides to be applied to the outbound event. CEOverrides string `envconfig:"K_CE_OVERRIDES"` // Name of this pod. Name string `envconfig:"POD_NAME" required:"true"` // Namespace this pod exists in. Namespace string `envconfig:"POD_NAMESPACE" required:"true"` // Whether to run continuously or exit. OneShot bool `envconfig:"ONE_SHOT" default:"false"` } func main() { flag.Parse() var env envConfig if err := envconfig.Process("", &env); err != nil { log.Printf("[ERROR] Failed to process env var: %s", err) os.Exit(1) } if env.Sink != "" { sink = env.Sink } var ceOverrides *duckv1.CloudEventOverrides if len(env.CEOverrides) > 0 { overrides := duckv1.CloudEventOverrides{} err := json.Unmarshal([]byte(env.CEOverrides), &overrides) if err != nil { log.Printf("[ERROR] Unparseable CloudEvents overrides %s: %v", env.CEOverrides, err) os.Exit(1) } ceOverrides = &overrides } p, err := cloudevents.NewHTTP(cloudevents.WithTarget(sink)) if err != nil { log.Fatalf("failed to create http protocol: %s", err.Error()) } c, err := cloudevents.NewClient(p, cloudevents.WithUUIDs(), cloudevents.WithTimeNow()) if err != nil { log.Fatalf("failed to create client: %s", err.Error()) } var period time.Duration if p, err := strconv.Atoi(periodStr); err != nil { period = time.Duration(5) * time.Second } else { period = time.Duration(p) * time.Second } if eventSource == "" { eventSource = fmt.Sprintf("https://knative.dev/eventing-contrib/cmd/heartbeats/#%s/%s", env.Namespace, env.Name) log.Printf("Heartbeats Source: %s", eventSource) } if len(label) > 0 && label[0] == '"' { label, _ = strconv.Unquote(label) } hb := &Heartbeat{ Sequence: 0, Label: label, } ticker := time.NewTicker(period) for { hb.Sequence++ event := cloudevents.NewEvent("1.0") event.SetType(eventType) event.SetSource(eventSource) event.SetExtension("the", 42) event.SetExtension("heart", "yes") event.SetExtension("beats", true) if ceOverrides != nil && ceOverrides.Extensions != nil { for n, v := range ceOverrides.Extensions { event.SetExtension(n, v) } } if err := event.SetData(cloudevents.ApplicationJSON, hb); err != nil { log.Printf("failed to set cloudevents data: %s", err.Error()) } log.Printf("sending cloudevent to %s", sink) if res := c.Send(context.Background(), event); !cloudevents.IsACK(res) { log.Printf("failed to send cloudevent: %v", res) } if env.OneShot { return } // Wait for next tick <-ticker.C } }
The following is an example of a container source that references the previous heartbeats container image:
apiVersion: sources.knative.dev/v1 kind: ContainerSource metadata: name: test-heartbeats spec: template: spec: containers: # This corresponds to a heartbeats image URI that you have built and published - image: gcr.io/knative-releases/knative.dev/eventing/cmd/heartbeats name: heartbeats args: - --period=1 env: - name: POD_NAME value: "example-pod" - name: POD_NAMESPACE value: "event-test" sink: ref: apiVersion: serving.knative.dev/v1 kind: Service name: example-service ...
5.2.6.2.2. Creating and managing container sources by using the Knative CLI
You can use the kn source container
commands to create and manage container sources by using the Knative (kn
) CLI. Using the Knative CLI to create event sources provides a more streamlined and intuitive user interface than modifying YAML files directly.
Create a container source
$ kn source container create <container_source_name> --image <image_uri> --sink <sink>
Delete a container source
$ kn source container delete <container_source_name>
Describe a container source
$ kn source container describe <container_source_name>
List existing container sources
$ kn source container list
List existing container sources in YAML format
$ kn source container list -o yaml
Update a container source
This command updates the image URI for an existing container source:
$ kn source container update <container_source_name> --image <image_uri>
5.2.6.2.3. Creating a container source by using the web console
After Knative Eventing is installed on your cluster, you can create a container source by using the web console. Using the OpenShift Container Platform web console provides a streamlined and intuitive user interface to create an event source.
Prerequisites
- You have logged in to the OpenShift Container Platform web console.
- The OpenShift Serverless Operator, Knative Serving, and Knative Eventing are installed on your OpenShift Container Platform cluster.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
- In the Developer perspective, navigate to +Add → Event Source. The Event Sources page is displayed.
- Select Container Source and then click Create Event Source. The Create Event Source page is displayed.
Configure the Container Source settings by using the Form view or YAML view:
NoteYou can switch between the Form view and YAML view. The data is persisted when switching between the views.
- In the Image field, enter the URI of the image that you want to run in the container created by the container source.
- In the Name field, enter the name of the image.
- Optional: In the Arguments field, enter any arguments to be passed to the container.
- Optional: In the Environment variables field, add any environment variables to set in the container.
In the Sink section, add a sink where events from the container source are routed to. If you are using the Form view, you can choose from the following options:
- Select Resource to use a channel, broker, or service as a sink for the event source.
- Select URI to specify where the events from the container source are routed to.
- After you have finished configuring the container source, click Create.
5.2.6.2.4. Container source reference
You can use a container as an event source, by creating a ContainerSource
object. You can configure multiple parameters when creating a ContainerSource
object.
ContainerSource
objects support the following fields:
Field | Description | Required or optional |
---|---|---|
|
Specifies the API version, for example | Required |
|
Identifies this resource object as a | Required |
|
Specifies metadata that uniquely identifies the | Required |
|
Specifies the configuration information for this | Required |
| A reference to an object that resolves to a URI to use as the sink. | Required |
|
A | Required |
| Defines overrides to control the output format and modifications to the event sent to the sink. | Optional |
Template parameter example
apiVersion: sources.knative.dev/v1 kind: ContainerSource metadata: name: test-heartbeats spec: template: spec: containers: - image: quay.io/openshift-knative/heartbeats:latest name: heartbeats args: - --period=1 env: - name: POD_NAME value: "mypod" - name: POD_NAMESPACE value: "event-test" ...
5.2.6.2.4.1. CloudEvent overrides
A ceOverrides
definition provides overrides that control the CloudEvent’s output format and modifications sent to the sink. You can configure multiple fields for the ceOverrides
definition.
A ceOverrides
definition supports the following fields:
Field | Description | Required or optional |
---|---|---|
|
Specifies which attributes are added or overridden on the outbound event. Each | Optional |
Only valid CloudEvent
attribute names are allowed as extensions. You cannot set the spec defined attributes from the extensions override configuration. For example, you can not modify the type
attribute.
CloudEvent Overrides example
apiVersion: sources.knative.dev/v1 kind: ContainerSource metadata: name: test-heartbeats spec: ... ceOverrides: extensions: extra: this is an extra attribute additional: 42
This sets the K_CE_OVERRIDES
environment variable on the subject
:
Example output
{ "extensions": { "extra": "this is an extra attribute", "additional": "42" } }
5.2.7. Connecting an event source to a sink using the Developer perspective
When you create an event source by using the OpenShift Container Platform web console, you can specify a sink that events are sent to from that source. The sink can be any addressable or callable resource that can receive incoming events from other resources.
5.2.7.1. Connect an event source to a sink using the Developer perspective
Prerequisites
- The OpenShift Serverless Operator, Knative Serving, and Knative Eventing are installed on your OpenShift Container Platform cluster.
- You have logged in to the web console and are in the Developer perspective.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
- You have created a sink, such as a Knative service, channel or broker.
Procedure
- Create an event source of any type, by navigating to +Add → Event Source and selecting the event source type that you want to create.
- In the Sink section of the Create Event Source form view, select your sink in the Resource list.
- Click Create.
Verification
You can verify that the event source was created and is connected to the sink by viewing the Topology page.
- In the Developer perspective, navigate to Topology.
- View the event source and click the connected sink to see the sink details in the right panel.
5.3. Event sinks
5.3.1. Event sinks
When you create an event source, you can specify a sink where events are sent to from the source. A sink is an addressable or a callable resource that can receive incoming events from other resources. Knative services, channels and brokers are all examples of sinks.
Addressable objects receive and acknowledge an event delivered over HTTP to an address defined in their status.address.url
field. As a special case, the core Kubernetes Service
object also fulfills the addressable interface.
Callable objects are able to receive an event delivered over HTTP and transform the event, returning 0
or 1
new events in the HTTP response. These returned events may be further processed in the same way that events from an external event source are processed.
5.3.1.1. Knative CLI sink flag
When you create an event source by using the Knative (kn
) CLI, you can specify a sink where events are sent to from that resource by using the --sink
flag. The sink can be any addressable or callable resource that can receive incoming events from other resources.
The following example creates a sink binding that uses a service, http://event-display.svc.cluster.local
, as the sink:
Example command using the sink flag
$ kn source binding create bind-heartbeat \
--namespace sinkbinding-example \
--subject "Job:batch/v1:app=heartbeat-cron" \
--sink http://event-display.svc.cluster.local \ 1
--ce-override "sink=bound"
- 1
svc
inhttp://event-display.svc.cluster.local
determines that the sink is a Knative service. Other default sink prefixes includechannel
, andbroker
.
You can configure which CRs can be used with the --sink
flag for Knative (kn
) CLI commands by Customizing kn
.
5.3.2. Kafka sink
Kafka sinks are a type of event sink that are available if a cluster administrator has enabled Kafka on your cluster. You can send events directly from an event source to a Kafka topic by using a Kafka sink.
5.3.2.1. Using a Kafka sink
You can create an event sink called a Kafka sink that sends events to a Kafka topic. Creating Knative resources by using YAML files uses a declarative API, which enables you to describe applications declaratively and in a reproducible manner. By default, a Kafka sink uses the binary content mode, which is more efficient than the structured mode. To create a Kafka sink by using YAML, you must create a YAML file that defines a KafkaSink
object, then apply it by using the oc apply
command.
Prerequisites
-
The OpenShift Serverless Operator, Knative Eventing, and the
KnativeKafka
custom resource (CR) are installed on your cluster. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
- You have access to a Red Hat AMQ Streams (Kafka) cluster that produces the Kafka messages you want to import.
-
Install the OpenShift CLI (
oc
).
Procedure
Create a
KafkaSink
object definition as a YAML file:Kafka sink YAML
apiVersion: eventing.knative.dev/v1alpha1 kind: KafkaSink metadata: name: <sink-name> namespace: <namespace> spec: topic: <topic-name> bootstrapServers: - <bootstrap-server>
To create the Kafka sink, apply the
KafkaSink
YAML file:$ oc apply -f <filename>
Configure an event source so that the sink is specified in its spec:
Example of a Kafka sink connected to an API server source
apiVersion: sources.knative.dev/v1alpha2 kind: ApiServerSource metadata: name: <source-name> 1 namespace: <namespace> 2 spec: serviceAccountName: <service-account-name> 3 mode: Resource resources: - apiVersion: v1 kind: Event sink: ref: apiVersion: eventing.knative.dev/v1alpha1 kind: KafkaSink name: <sink-name> 4
5.3.2.2. Configuring security for Kafka sinks
Transport Layer Security (TLS) is used by Apache Kafka clients and servers to encrypt traffic between Knative and Kafka, as well as for authentication. TLS is the only supported method of traffic encryption for Knative Kafka.
Simple Authentication and Security Layer (SASL) is used by Apache Kafka for authentication. If you use SASL authentication on your cluster, users must provide credentials to Knative for communicating with the Kafka cluster; otherwise events cannot be produced or consumed.
Prerequisites
-
The OpenShift Serverless Operator, Knative Eventing, and the
KnativeKafka
custom resources (CRs) are installed on your OpenShift Container Platform cluster. -
Kafka sink is enabled in the
KnativeKafka
CR. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
You have a Kafka cluster CA certificate stored as a
.pem
file. -
You have a Kafka cluster client certificate and a key stored as
.pem
files. -
You have installed the OpenShift (
oc
) CLI. -
You have chosen the SASL mechanism to use, for example,
PLAIN
,SCRAM-SHA-256
, orSCRAM-SHA-512
.
Procedure
Create the certificate files as a secret in the same namespace as your
KafkaSink
object:ImportantCertificates and keys must be in PEM format.
For authentication using SASL without encryption:
$ oc create secret -n <namespace> generic <secret_name> \ --from-literal=protocol=SASL_PLAINTEXT \ --from-literal=sasl.mechanism=<sasl_mechanism> \ --from-literal=user=<username> \ --from-literal=password=<password>
For authentication using SASL and encryption using TLS:
$ oc create secret -n <namespace> generic <secret_name> \ --from-literal=protocol=SASL_SSL \ --from-literal=sasl.mechanism=<sasl_mechanism> \ --from-file=ca.crt=<my_caroot.pem_file_path> \ 1 --from-literal=user=<username> \ --from-literal=password=<password>
- 1
- The
ca.crt
can be omitted to use the system’s root CA set if you are using a public cloud managed Kafka service, such as Red Hat OpenShift Streams for Apache Kafka.
For authentication and encryption using TLS:
$ oc create secret -n <namespace> generic <secret_name> \ --from-literal=protocol=SSL \ --from-file=ca.crt=<my_caroot.pem_file_path> \ 1 --from-file=user.crt=<my_cert.pem_file_path> \ --from-file=user.key=<my_key.pem_file_path>
- 1
- The
ca.crt
can be omitted to use the system’s root CA set if you are using a public cloud managed Kafka service, such as Red Hat OpenShift Streams for Apache Kafka.
Create or modify a
KafkaSink
object and add a reference to your secret in theauth
spec:apiVersion: eventing.knative.dev/v1alpha1 kind: KafkaSink metadata: name: <sink_name> namespace: <namespace> spec: ... auth: secret: ref: name: <secret_name> ...
Apply the
KafkaSink
object:$ oc apply -f <filename>
5.4. Brokers
5.4.1. Brokers
Brokers can be used in combination with triggers to deliver events from an event source to an event sink. Events are sent from an event source to a broker as an HTTP POST
request. After events have entered the broker, they can be filtered by CloudEvent attributes using triggers, and sent as an HTTP POST
request to an event sink.
5.4.2. Broker types
Cluster administrators can set the default broker implementation for a cluster. When you create a broker, the default broker implementation is used, unless you provide set configurations in the Broker
object.
5.4.2.1. Default broker implementation for development purposes
Knative provides a default, channel-based broker implementation. This channel-based broker can be used for development and testing purposes, but does not provide adequate event delivery guarantees for production environments. The default broker is backed by the InMemoryChannel
channel implementation by default.
If you want to use Kafka to reduce network hops, use the Kafka broker implementation. Do not configure the channel-based broker to be backed by the KafkaChannel
channel implementation.
5.4.2.2. Production-ready Kafka broker implementation
For production-ready Knative Eventing deployments, Red Hat recommends using the Knative Kafka broker implementation. The Kafka broker is an Apache Kafka native implementation of the Knative broker, which sends CloudEvents directly to the Kafka instance.
The Kafka broker has a native integration with Kafka for storing and routing events. This allows better integration with Kafka for the broker and trigger model over other broker types, and reduces network hops. Other benefits of the Kafka broker implementation include:
- At-least-once delivery guarantees
- Ordered delivery of events, based on the CloudEvents partitioning extension
- Control plane high availability
- A horizontally scalable data plane
The Knative Kafka broker stores incoming CloudEvents as Kafka records, using the binary content mode. This means that all CloudEvent attributes and extensions are mapped as headers on the Kafka record, while the data
spec of the CloudEvent corresponds to the value of the Kafka record.
5.4.3. Creating brokers
Knative provides a default, channel-based broker implementation. This channel-based broker can be used for development and testing purposes, but does not provide adequate event delivery guarantees for production environments.
If a cluster administrator has configured your OpenShift Serverless deployment to use Kafka as the default broker type, creating a broker by using the default settings creates a Kafka-based broker.
If your OpenShift Serverless deployment is not configured to use Kafka broker as the default broker type, the channel-based broker is created when you use the default settings in the following procedures.
5.4.3.1. Creating a broker by using the Knative CLI
Brokers can be used in combination with triggers to deliver events from an event source to an event sink. Using the Knative (kn
) CLI to create brokers provides a more streamlined and intuitive user interface over modifying YAML files directly. You can use the kn broker create
command to create a broker.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Create a broker:
$ kn broker create <broker_name>
Verification
Use the
kn
command to list all existing brokers:$ kn broker list
Example output
NAME URL AGE CONDITIONS READY REASON default http://broker-ingress.knative-eventing.svc.cluster.local/test/default 45s 5 OK / 5 True
Optional: If you are using the OpenShift Container Platform web console, you can navigate to the Topology view in the Developer perspective, and observe that the broker exists:
5.4.3.2. Creating a broker by annotating a trigger
Brokers can be used in combination with triggers to deliver events from an event source to an event sink. You can create a broker by adding the eventing.knative.dev/injection: enabled
annotation to a Trigger
object.
If you create a broker by using the eventing.knative.dev/injection: enabled
annotation, you cannot delete this broker without cluster administrator permissions. If you delete the broker without having a cluster administrator remove this annotation first, the broker is created again after deletion.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
-
Install the OpenShift CLI (
oc
). - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Create a
Trigger
object as a YAML file that has theeventing.knative.dev/injection: enabled
annotation:apiVersion: eventing.knative.dev/v1 kind: Trigger metadata: annotations: eventing.knative.dev/injection: enabled name: <trigger_name> spec: broker: default subscriber: 1 ref: apiVersion: serving.knative.dev/v1 kind: Service name: <service_name>
- 1
- Specify details about the event sink, or subscriber, that the trigger sends events to.
Apply the
Trigger
YAML file:$ oc apply -f <filename>
Verification
You can verify that the broker has been created successfully by using the oc
CLI, or by observing it in the Topology view in the web console.
Enter the following
oc
command to get the broker:$ oc -n <namespace> get broker default
Example output
NAME READY REASON URL AGE default True http://broker-ingress.knative-eventing.svc.cluster.local/test/default 3m56s
Optional: If you are using the OpenShift Container Platform web console, you can navigate to the Topology view in the Developer perspective, and observe that the broker exists:
5.4.3.3. Creating a broker by labeling a namespace
Brokers can be used in combination with triggers to deliver events from an event source to an event sink. You can create the default
broker automatically by labelling a namespace that you own or have write permissions for.
Brokers created using this method are not removed if you remove the label. You must manually delete them.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
-
Install the OpenShift CLI (
oc
). - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Label a namespace with
eventing.knative.dev/injection=enabled
:$ oc label namespace <namespace> eventing.knative.dev/injection=enabled
Verification
You can verify that the broker has been created successfully by using the oc
CLI, or by observing it in the Topology view in the web console.
Use the
oc
command to get the broker:$ oc -n <namespace> get broker <broker_name>
Example command
$ oc -n default get broker default
Example output
NAME READY REASON URL AGE default True http://broker-ingress.knative-eventing.svc.cluster.local/test/default 3m56s
Optional: If you are using the OpenShift Container Platform web console, you can navigate to the Topology view in the Developer perspective, and observe that the broker exists:
5.4.3.4. Deleting a broker that was created by injection
If you create a broker by injection and later want to delete it, you must delete it manually. Brokers created by using a namespace label or trigger annotation are not deleted permanently if you remove the label or annotation.
Prerequisites
-
Install the OpenShift CLI (
oc
).
Procedure
Remove the
eventing.knative.dev/injection=enabled
label from the namespace:$ oc label namespace <namespace> eventing.knative.dev/injection-
Removing the annotation prevents Knative from recreating the broker after you delete it.
Delete the broker from the selected namespace:
$ oc -n <namespace> delete broker <broker_name>
Verification
Use the
oc
command to get the broker:$ oc -n <namespace> get broker <broker_name>
Example command
$ oc -n default get broker default
Example output
No resources found. Error from server (NotFound): brokers.eventing.knative.dev "default" not found
5.4.3.5. Creating a broker by using the web console
After Knative Eventing is installed on your cluster, you can create a broker by using the web console. Using the OpenShift Container Platform web console provides a streamlined and intuitive user interface to create a broker.
Prerequisites
- You have logged in to the OpenShift Container Platform web console.
- The OpenShift Serverless Operator, Knative Serving and Knative Eventing are installed on the cluster.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
- In the Developer perspective, navigate to +Add → Broker. The Broker page is displayed.
-
Optional. Update the Name of the broker. If you do not update the name, the generated broker is named
default
. - Click Create.
Verification
You can verify that the broker was created by viewing broker components in the Topology page.
- In the Developer perspective, navigate to Topology.
View the
mt-broker-ingress
,mt-broker-filter
, andmt-broker-controller
components.
5.4.3.6. Creating a broker by using the Administrator perspective
Brokers can be used in combination with triggers to deliver events from an event source to an event sink. Events are sent from an event source to a broker as an HTTP POST
request. After events have entered the broker, they can be filtered by CloudEvent attributes using triggers, and sent as an HTTP POST
request to an event sink.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
- You have logged in to the web console and are in the Administrator perspective.
- You have cluster administrator permissions for OpenShift Container Platform.
Procedure
- In the Administrator perspective of the OpenShift Container Platform web console, navigate to Serverless → Eventing.
- In the Create list, select Broker. You will be directed to the Create Broker page.
- Optional: Modify the YAML configuration for the broker.
- Click Create.
5.4.3.7. Next steps
- Configure event delivery parameters that are applied in cases where an event fails to be delivered to an event sink. See Examples of configuring event delivery parameters.
5.4.3.8. Additional resources
5.4.4. Configuring the default broker backing channel
If you are using a channel-based broker, you can set the default backing channel type for the broker to either InMemoryChannel
or KafkaChannel
.
Prerequisites
- You have administrator permissions on OpenShift Container Platform.
- You have installed the OpenShift Serverless Operator and Knative Eventing on your cluster.
-
You have installed the OpenShift (
oc
) CLI. -
If you want to use Kafka channels as the default backing channel type, you must also install the
KnativeKafka
CR on your cluster.
Procedure
Modify the
KnativeEventing
custom resource (CR) to add configuration details for theconfig-br-default-channel
config map:apiVersion: operator.knative.dev/v1beta1 kind: KnativeEventing metadata: name: knative-eventing namespace: knative-eventing spec: config: 1 config-br-default-channel: channel-template-spec: | apiVersion: messaging.knative.dev/v1beta1 kind: KafkaChannel 2 spec: numPartitions: 6 3 replicationFactor: 3 4
- 1
- In
spec.config
, you can specify the config maps that you want to add modified configurations for. - 2
- The default backing channel type configuration. In this example, the default channel implementation for the cluster is
KafkaChannel
. - 3
- The number of partitions for the Kafka channel that backs the broker.
- 4
- The replication factor for the Kafka channel that backs the broker.
Apply the updated
KnativeEventing
CR:$ oc apply -f <filename>
5.4.5. Configuring the default broker class
You can use the config-br-defaults
config map to specify default broker class settings for Knative Eventing. You can specify the default broker class for the entire cluster or for one or more namespaces. Currently the MTChannelBasedBroker
and Kafka
broker types are supported.
Prerequisites
- You have administrator permissions on OpenShift Container Platform.
- You have installed the OpenShift Serverless Operator and Knative Eventing on your cluster.
-
If you want to use Kafka broker as the default broker implementation, you must also install the
KnativeKafka
CR on your cluster.
Procedure
Modify the
KnativeEventing
custom resource to add configuration details for theconfig-br-defaults
config map:apiVersion: operator.knative.dev/v1beta1 kind: KnativeEventing metadata: name: knative-eventing namespace: knative-eventing spec: defaultBrokerClass: Kafka 1 config: 2 config-br-defaults: 3 default-br-config: | clusterDefault: 4 brokerClass: Kafka apiVersion: v1 kind: ConfigMap name: kafka-broker-config 5 namespace: knative-eventing 6 namespaceDefaults: 7 my-namespace: brokerClass: MTChannelBasedBroker apiVersion: v1 kind: ConfigMap name: config-br-default-channel 8 namespace: knative-eventing 9 ...
- 1
- The default broker class for Knative Eventing.
- 2
- In
spec.config
, you can specify the config maps that you want to add modified configurations for. - 3
- The
config-br-defaults
config map specifies the default settings for any broker that does not specifyspec.config
settings or a broker class. - 4
- The cluster-wide default broker class configuration. In this example, the default broker class implementation for the cluster is
Kafka
. - 5
- The
kafka-broker-config
config map specifies default settings for the Kafka broker. See "Configuring Kafka broker settings" in the "Additional resources" section. - 6
- The namespace where the
kafka-broker-config
config map exists. - 7
- The namespace-scoped default broker class configuration. In this example, the default broker class implementation for the
my-namespace
namespace isMTChannelBasedBroker
. You can specify default broker class implementations for multiple namespaces. - 8
- The
config-br-default-channel
config map specifies the default backing channel for the broker. See "Configuring the default broker backing channel" in the "Additional resources" section. - 9
- The namespace where the
config-br-default-channel
config map exists.
ImportantConfiguring a namespace-specific default overrides any cluster-wide settings.
5.4.6. Kafka broker
For production-ready Knative Eventing deployments, Red Hat recommends using the Knative Kafka broker implementation. The Kafka broker is an Apache Kafka native implementation of the Knative broker, which sends CloudEvents directly to the Kafka instance.
The Kafka broker has a native integration with Kafka for storing and routing events. This allows better integration with Kafka for the broker and trigger model over other broker types, and reduces network hops. Other benefits of the Kafka broker implementation include:
- At-least-once delivery guarantees
- Ordered delivery of events, based on the CloudEvents partitioning extension
- Control plane high availability
- A horizontally scalable data plane
The Knative Kafka broker stores incoming CloudEvents as Kafka records, using the binary content mode. This means that all CloudEvent attributes and extensions are mapped as headers on the Kafka record, while the data
spec of the CloudEvent corresponds to the value of the Kafka record.
5.4.6.1. Creating a Kafka broker when it is not configured as the default broker type
If your OpenShift Serverless deployment is not configured to use Kafka broker as the default broker type, you can use one of the following procedures to create a Kafka-based broker.
5.4.6.1.1. Creating a Kafka broker by using YAML
Creating Knative resources by using YAML files uses a declarative API, which enables you to describe applications declaratively and in a reproducible manner. To create a Kafka broker by using YAML, you must create a YAML file that defines a Broker
object, then apply it by using the oc apply
command.
Prerequisites
-
The OpenShift Serverless Operator, Knative Eventing, and the
KnativeKafka
custom resource are installed on your OpenShift Container Platform cluster. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
You have installed the OpenShift CLI (
oc
).
Procedure
Create a Kafka-based broker as a YAML file:
apiVersion: eventing.knative.dev/v1 kind: Broker metadata: annotations: eventing.knative.dev/broker.class: Kafka 1 name: example-kafka-broker spec: config: apiVersion: v1 kind: ConfigMap name: kafka-broker-config 2 namespace: knative-eventing
- 1
- The broker class. If not specified, brokers use the default class as configured by cluster administrators. To use the Kafka broker, this value must be
Kafka
. - 2
- The default config map for Knative Kafka brokers. This config map is created when the Kafka broker functionality is enabled on the cluster by a cluster administrator.
Apply the Kafka-based broker YAML file:
$ oc apply -f <filename>
5.4.6.1.2. Creating a Kafka broker that uses an externally managed Kafka topic
If you want to use a Kafka broker without allowing it to create its own internal topic, you can use an externally managed Kafka topic instead. To do this, you must create a Kafka Broker
object that uses the kafka.eventing.knative.dev/external.topic
annotation.
Prerequisites
-
The OpenShift Serverless Operator, Knative Eventing, and the
KnativeKafka
custom resource are installed on your OpenShift Container Platform cluster. - You have access to a Kafka instance such as Red Hat AMQ Streams, and have created a Kafka topic.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
You have installed the OpenShift CLI (
oc
).
Procedure
Create a Kafka-based broker as a YAML file:
apiVersion: eventing.knative.dev/v1 kind: Broker metadata: annotations: eventing.knative.dev/broker.class: Kafka 1 kafka.eventing.knative.dev/external.topic: <topic_name> 2 ...
Apply the Kafka-based broker YAML file:
$ oc apply -f <filename>
5.4.6.1.3. Knative Broker implementation for Apache Kafka with isolated data plane
The Knative Broker implementation for Apache Kafka with isolated data plane is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.
For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope.
The Knative Broker implementation for Apache Kafka has 2 planes:
- Control plane
- Consists of controllers that talk to the Kubernetes API, watch for custom objects, and manage the data plane.
- Data plane
-
The collection of components that listen for incoming events, talk to Apache Kafka, and send events to the event sinks. The Knative Broker implementation for Apache Kafka data plane is where events flow. The implementation consists of
kafka-broker-receiver
andkafka-broker-dispatcher
deployments.
When you configure a Broker class of Kafka
, the Knative Broker implementation for Apache Kafka uses a shared data plane. This means that the kafka-broker-receiver
and kafka-broker-dispatcher
deployments in the knative-eventing
namespace are used for all Apache Kafka Brokers in the cluster.
However, when you configure a Broker class of KafkaNamespaced
, the Apache Kafka broker controller creates a new data plane for each namespace where a broker exists. This data plane is used by all KafkaNamespaced
brokers in that namespace. This provides isolation between the data planes, so that the kafka-broker-receiver
and kafka-broker-dispatcher
deployments in the user namespace are only used for the broker in that namespace.
As a consequence of having separate data planes, this security feature creates more deployments and uses more resources. Unless you have such isolation requirements, use a regular Broker with a class of Kafka
.
5.4.6.1.4. Creating a Knative broker for Apache Kafka that uses an isolated data plane
The Knative Broker implementation for Apache Kafka with isolated data plane is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.
For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope.
To create a KafkaNamespaced
broker, you must set the eventing.knative.dev/broker.class
annotation to KafkaNamespaced
.
Prerequisites
-
The OpenShift Serverless Operator, Knative Eventing, and the
KnativeKafka
custom resource are installed on your OpenShift Container Platform cluster. - You have access to an Apache Kafka instance, such as Red Hat AMQ Streams, and have created a Kafka topic.
- You have created a project, or have access to a project, with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
You have installed the OpenShift CLI (
oc
).
Procedure
Create an Apache Kafka-based broker by using a YAML file:
apiVersion: eventing.knative.dev/v1 kind: Broker metadata: annotations: eventing.knative.dev/broker.class: KafkaNamespaced 1 name: default namespace: my-namespace 2 spec: config: apiVersion: v1 kind: ConfigMap name: my-config 3 ...
Apply the Apache Kafka-based broker YAML file:
$ oc apply -f <filename>
The ConfigMap
object in spec.config
must be in the same namespace as the Broker
object:
apiVersion: v1 kind: ConfigMap metadata: name: my-config namespace: my-namespace data: ...
After the creation of the first Broker
object with the KafkaNamespaced
class, the kafka-broker-receiver
and kafka-broker-dispatcher
deployments are created in the namespace. Subsequently, all brokers with the KafkaNamespaced
class in the same namespace will use the same data plane. If no brokers with the KafkaNamespaced
class exist in the namespace, the data plane in the namespace is deleted.
5.4.6.2. Configuring Kafka broker settings
You can configure the replication factor, bootstrap servers, and the number of topic partitions for a Kafka broker, by creating a config map and referencing this config map in the Kafka Broker
object.
Prerequisites
- You have cluster or dedicated administrator permissions on OpenShift Container Platform.
-
The OpenShift Serverless Operator, Knative Eventing, and the
KnativeKafka
custom resource (CR) are installed on your OpenShift Container Platform cluster. - You have created a project or have access to a project that has the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
You have installed the OpenShift CLI (
oc
).
Procedure
Modify the
kafka-broker-config
config map, or create your own config map that contains the following configuration:apiVersion: v1 kind: ConfigMap metadata: name: <config_map_name> 1 namespace: <namespace> 2 data: default.topic.partitions: <integer> 3 default.topic.replication.factor: <integer> 4 bootstrap.servers: <list_of_servers> 5
- 1
- The config map name.
- 2
- The namespace where the config map exists.
- 3
- The number of topic partitions for the Kafka broker. This controls how quickly events can be sent to the broker. A higher number of partitions requires greater compute resources.
- 4
- The replication factor of topic messages. This prevents against data loss. A higher replication factor requires greater compute resources and more storage.
- 5
- A comma separated list of bootstrap servers. This can be inside or outside of the OpenShift Container Platform cluster, and is a list of Kafka clusters that the broker receives events from and sends events to.
ImportantThe
default.topic.replication.factor
value must be less than or equal to the number of Kafka broker instances in your cluster. For example, if you only have one Kafka broker, thedefault.topic.replication.factor
value should not be more than"1"
.Example Kafka broker config map
apiVersion: v1 kind: ConfigMap metadata: name: kafka-broker-config namespace: knative-eventing data: default.topic.partitions: "10" default.topic.replication.factor: "3" bootstrap.servers: "my-cluster-kafka-bootstrap.kafka:9092"
Apply the config map:
$ oc apply -f <config_map_filename>
Specify the config map for the Kafka
Broker
object:Example Broker object
apiVersion: eventing.knative.dev/v1 kind: Broker metadata: name: <broker_name> 1 namespace: <namespace> 2 annotations: eventing.knative.dev/broker.class: Kafka 3 spec: config: apiVersion: v1 kind: ConfigMap name: <config_map_name> 4 namespace: <namespace> 5 ...
Apply the broker:
$ oc apply -f <broker_filename>
5.4.6.3. Security configuration for Knative Kafka brokers
Kafka clusters are generally secured by using the TLS or SASL authentication methods. You can configure a Kafka broker or channel to work against a protected Red Hat AMQ Streams cluster by using TLS or SASL.
Red Hat recommends that you enable both SASL and TLS together.
5.4.6.3.1. Configuring TLS authentication for Kafka brokers
Transport Layer Security (TLS) is used by Apache Kafka clients and servers to encrypt traffic between Knative and Kafka, as well as for authentication. TLS is the only supported method of traffic encryption for Knative Kafka.
Prerequisites
- You have cluster or dedicated administrator permissions on OpenShift Container Platform.
-
The OpenShift Serverless Operator, Knative Eventing, and the
KnativeKafka
CR are installed on your OpenShift Container Platform cluster. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
You have a Kafka cluster CA certificate stored as a
.pem
file. -
You have a Kafka cluster client certificate and a key stored as
.pem
files. -
Install the OpenShift CLI (
oc
).
Procedure
Create the certificate files as a secret in the
knative-eventing
namespace:$ oc create secret -n knative-eventing generic <secret_name> \ --from-literal=protocol=SSL \ --from-file=ca.crt=caroot.pem \ --from-file=user.crt=certificate.pem \ --from-file=user.key=key.pem
ImportantUse the key names
ca.crt
,user.crt
, anduser.key
. Do not change them.Edit the
KnativeKafka
CR and add a reference to your secret in thebroker
spec:apiVersion: operator.serverless.openshift.io/v1alpha1 kind: KnativeKafka metadata: namespace: knative-eventing name: knative-kafka spec: broker: enabled: true defaultConfig: authSecretName: <secret_name> ...
5.4.6.3.2. Configuring SASL authentication for Kafka brokers
Simple Authentication and Security Layer (SASL) is used by Apache Kafka for authentication. If you use SASL authentication on your cluster, users must provide credentials to Knative for communicating with the Kafka cluster; otherwise events cannot be produced or consumed.
Prerequisites
- You have cluster or dedicated administrator permissions on OpenShift Container Platform.
-
The OpenShift Serverless Operator, Knative Eventing, and the
KnativeKafka
CR are installed on your OpenShift Container Platform cluster. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
- You have a username and password for a Kafka cluster.
-
You have chosen the SASL mechanism to use, for example,
PLAIN
,SCRAM-SHA-256
, orSCRAM-SHA-512
. -
If TLS is enabled, you also need the
ca.crt
certificate file for the Kafka cluster. -
Install the OpenShift CLI (
oc
).
Procedure
Create the certificate files as a secret in the
knative-eventing
namespace:$ oc create secret -n knative-eventing generic <secret_name> \ --from-literal=protocol=SASL_SSL \ --from-literal=sasl.mechanism=<sasl_mechanism> \ --from-file=ca.crt=caroot.pem \ --from-literal=password="SecretPassword" \ --from-literal=user="my-sasl-user"
-
Use the key names
ca.crt
,password
, andsasl.mechanism
. Do not change them. If you want to use SASL with public CA certificates, you must use the
tls.enabled=true
flag, rather than theca.crt
argument, when creating the secret. For example:$ oc create secret -n <namespace> generic <kafka_auth_secret> \ --from-literal=tls.enabled=true \ --from-literal=password="SecretPassword" \ --from-literal=saslType="SCRAM-SHA-512" \ --from-literal=user="my-sasl-user"
-
Use the key names
Edit the
KnativeKafka
CR and add a reference to your secret in thebroker
spec:apiVersion: operator.serverless.openshift.io/v1alpha1 kind: KnativeKafka metadata: namespace: knative-eventing name: knative-kafka spec: broker: enabled: true defaultConfig: authSecretName: <secret_name> ...
5.4.6.4. Additional resources
5.4.7. Managing brokers
The Knative (kn
) CLI provides commands that can be used to describe and list existing brokers.
5.4.7.1. Listing existing brokers by using the Knative CLI
Using the Knative (kn
) CLI to list brokers provides a streamlined and intuitive user interface. You can use the kn broker list
command to list existing brokers in your cluster by using the Knative CLI.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
-
You have installed the Knative (
kn
) CLI.
Procedure
List all existing brokers:
$ kn broker list
Example output
NAME URL AGE CONDITIONS READY REASON default http://broker-ingress.knative-eventing.svc.cluster.local/test/default 45s 5 OK / 5 True
5.4.7.2. Describing an existing broker by using the Knative CLI
Using the Knative (kn
) CLI to describe brokers provides a streamlined and intuitive user interface. You can use the kn broker describe
command to print information about existing brokers in your cluster by using the Knative CLI.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
-
You have installed the Knative (
kn
) CLI.
Procedure
Describe an existing broker:
$ kn broker describe <broker_name>
Example command using default broker
$ kn broker describe default
Example output
Name: default Namespace: default Annotations: eventing.knative.dev/broker.class=MTChannelBasedBroker, eventing.knative.dev/creato ... Age: 22s Address: URL: http://broker-ingress.knative-eventing.svc.cluster.local/default/default Conditions: OK TYPE AGE REASON ++ Ready 22s ++ Addressable 22s ++ FilterReady 22s ++ IngressReady 22s ++ TriggerChannelReady 22s
5.4.8. Event delivery
You can configure event delivery parameters that are applied in cases where an event fails to be delivered to an event sink. Configuring event delivery parameters, including a dead letter sink, ensures that any events that fail to be delivered to an event sink are retried. Otherwise, undelivered events are dropped.
5.4.8.1. Event delivery behavior patterns for channels and brokers
Different channel and broker types have their own behavior patterns that are followed for event delivery.
5.4.8.1.1. Knative Kafka channels and brokers
If an event is successfully delivered to a Kafka channel or broker receiver, the receiver responds with a 202
status code, which means that the event has been safely stored inside a Kafka topic and is not lost.
If the receiver responds with any other status code, the event is not safely stored, and steps must be taken by the user to resolve the issue.
5.4.8.2. Configurable event delivery parameters
The following parameters can be configured for event delivery:
- Dead letter sink
-
You can configure the
deadLetterSink
delivery parameter so that if an event fails to be delivered, it is stored in the specified event sink. Undelivered events that are not stored in a dead letter sink are dropped. The dead letter sink be any addressable object that conforms to the Knative Eventing sink contract, such as a Knative service, a Kubernetes service, or a URI. - Retries
-
You can set a minimum number of times that the delivery must be retried before the event is sent to the dead letter sink, by configuring the
retry
delivery parameter with an integer value. - Back off delay
-
You can set the
backoffDelay
delivery parameter to specify the time delay before an event delivery retry is attempted after a failure. The duration of thebackoffDelay
parameter is specified using the ISO 8601 format. For example,PT1S
specifies a 1 second delay. - Back off policy
-
The
backoffPolicy
delivery parameter can be used to specify the retry back off policy. The policy can be specified as eitherlinear
orexponential
. When using thelinear
back off policy, the back off delay is equal tobackoffDelay * <numberOfRetries>
. When using theexponential
backoff policy, the back off delay is equal tobackoffDelay*2^<numberOfRetries>
.
5.4.8.3. Examples of configuring event delivery parameters
You can configure event delivery parameters for Broker
, Trigger
, Channel
, and Subscription
objects. If you configure event delivery parameters for a broker or channel, these parameters are propagated to triggers or subscriptions created for those objects. You can also set event delivery parameters for triggers or subscriptions to override the settings for the broker or channel.
Example Broker
object
apiVersion: eventing.knative.dev/v1 kind: Broker metadata: ... spec: delivery: deadLetterSink: ref: apiVersion: eventing.knative.dev/v1alpha1 kind: KafkaSink name: <sink_name> backoffDelay: <duration> backoffPolicy: <policy_type> retry: <integer> ...
Example Trigger
object
apiVersion: eventing.knative.dev/v1 kind: Trigger metadata: ... spec: broker: <broker_name> delivery: deadLetterSink: ref: apiVersion: serving.knative.dev/v1 kind: Service name: <sink_name> backoffDelay: <duration> backoffPolicy: <policy_type> retry: <integer> ...
Example Channel
object
apiVersion: messaging.knative.dev/v1 kind: Channel metadata: ... spec: delivery: deadLetterSink: ref: apiVersion: serving.knative.dev/v1 kind: Service name: <sink_name> backoffDelay: <duration> backoffPolicy: <policy_type> retry: <integer> ...
Example Subscription
object
apiVersion: messaging.knative.dev/v1 kind: Subscription metadata: ... spec: channel: apiVersion: messaging.knative.dev/v1 kind: Channel name: <channel_name> delivery: deadLetterSink: ref: apiVersion: serving.knative.dev/v1 kind: Service name: <sink_name> backoffDelay: <duration> backoffPolicy: <policy_type> retry: <integer> ...
5.4.8.4. Configuring event delivery ordering for triggers
If you are using a Kafka broker, you can configure the delivery order of events from triggers to event sinks.
Prerequisites
- The OpenShift Serverless Operator, Knative Eventing, and Knative Kafka are installed on your OpenShift Container Platform cluster.
- Kafka broker is enabled for use on your cluster, and you have created a Kafka broker.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
You have installed the OpenShift (
oc
) CLI.
Procedure
Create or modify a
Trigger
object and set thekafka.eventing.knative.dev/delivery.order
annotation:apiVersion: eventing.knative.dev/v1 kind: Trigger metadata: name: <trigger_name> annotations: kafka.eventing.knative.dev/delivery.order: ordered ...
The supported consumer delivery guarantees are:
unordered
- An unordered consumer is a non-blocking consumer that delivers messages unordered, while preserving proper offset management.
ordered
An ordered consumer is a per-partition blocking consumer that waits for a successful response from the CloudEvent subscriber before it delivers the next message of the partition.
The default ordering guarantee is
unordered
.
Apply the
Trigger
object:$ oc apply -f <filename>
5.5. Triggers
5.5.1. Triggers overview
Brokers can be used in combination with triggers to deliver events from an event source to an event sink. Events are sent from an event source to a broker as an HTTP POST
request. After events have entered the broker, they can be filtered by CloudEvent attributes using triggers, and sent as an HTTP POST
request to an event sink.
If you are using a Kafka broker, you can configure the delivery order of events from triggers to event sinks. See Configuring event delivery ordering for triggers.
5.5.1.1. Configuring event delivery ordering for triggers
If you are using a Kafka broker, you can configure the delivery order of events from triggers to event sinks.
Prerequisites
- The OpenShift Serverless Operator, Knative Eventing, and Knative Kafka are installed on your OpenShift Container Platform cluster.
- Kafka broker is enabled for use on your cluster, and you have created a Kafka broker.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
You have installed the OpenShift (
oc
) CLI.
Procedure
Create or modify a
Trigger
object and set thekafka.eventing.knative.dev/delivery.order
annotation:apiVersion: eventing.knative.dev/v1 kind: Trigger metadata: name: <trigger_name> annotations: kafka.eventing.knative.dev/delivery.order: ordered ...
The supported consumer delivery guarantees are:
unordered
- An unordered consumer is a non-blocking consumer that delivers messages unordered, while preserving proper offset management.
ordered
An ordered consumer is a per-partition blocking consumer that waits for a successful response from the CloudEvent subscriber before it delivers the next message of the partition.
The default ordering guarantee is
unordered
.
Apply the
Trigger
object:$ oc apply -f <filename>
5.5.1.2. Next steps
- Configure event delivery parameters that are applied in cases where an event fails to be delivered to an event sink. See Examples of configuring event delivery parameters.
5.5.2. Creating triggers
Brokers can be used in combination with triggers to deliver events from an event source to an event sink. Events are sent from an event source to a broker as an HTTP POST
request. After events have entered the broker, they can be filtered by CloudEvent attributes using triggers, and sent as an HTTP POST
request to an event sink.
5.5.2.1. Creating a trigger by using the Administrator perspective
Using the OpenShift Container Platform web console provides a streamlined and intuitive user interface to create a trigger. After Knative Eventing is installed on your cluster and you have created a broker, you can create a trigger by using the web console.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
- You have logged in to the web console and are in the Administrator perspective.
- You have cluster administrator permissions for OpenShift Container Platform.
- You have created a Knative broker.
- You have created a Knative service to use as a subscriber.
Procedure
- In the Administrator perspective of the OpenShift Container Platform web console, navigate to Serverless → Eventing.
- In the Broker tab, select the Options menu for the broker that you want to add a trigger to.
- Click Add Trigger in the list.
- In the Add Trigger dialogue box, select a Subscriber for the trigger. The subscriber is the Knative service that will receive events from the broker.
- Click Add.
5.5.2.2. Creating a trigger by using the Developer perspective
Using the OpenShift Container Platform web console provides a streamlined and intuitive user interface to create a trigger. After Knative Eventing is installed on your cluster and you have created a broker, you can create a trigger by using the web console.
Prerequisites
- The OpenShift Serverless Operator, Knative Serving, and Knative Eventing are installed on your OpenShift Container Platform cluster.
- You have logged in to the web console.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
- You have created a broker and a Knative service or other event sink to connect to the trigger.
Procedure
- In the Developer perspective, navigate to the Topology page.
- Hover over the broker that you want to create a trigger for, and drag the arrow. The Add Trigger option is displayed.
- Click Add Trigger.
- Select your sink in the Subscriber list.
- Click Add.
Verification
- After the subscription has been created, you can view it in the Topology page, where it is represented as a line that connects the broker to the event sink.
Deleting a trigger
- In the Developer perspective, navigate to the Topology page.
- Click on the trigger that you want to delete.
- In the Actions context menu, select Delete Trigger.
5.5.2.3. Creating a trigger by using the Knative CLI
You can use the kn trigger create
command to create a trigger.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Create a trigger:
$ kn trigger create <trigger_name> --broker <broker_name> --filter <key=value> --sink <sink_name>
Alternatively, you can create a trigger and simultaneously create the
default
broker using broker injection:$ kn trigger create <trigger_name> --inject-broker --filter <key=value> --sink <sink_name>
By default, triggers forward all events sent to a broker to sinks that are subscribed to that broker. Using the
--filter
attribute for triggers allows you to filter events from a broker, so that subscribers will only receive a subset of events based on your defined criteria.
5.5.3. List triggers from the command line
Using the Knative (kn
) CLI to list triggers provides a streamlined and intuitive user interface.
5.5.3.1. Listing triggers by using the Knative CLI
You can use the kn trigger list
command to list existing triggers in your cluster.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
-
You have installed the Knative (
kn
) CLI.
Procedure
Print a list of available triggers:
$ kn trigger list
Example output
NAME BROKER SINK AGE CONDITIONS READY REASON email default ksvc:edisplay 4s 5 OK / 5 True ping default ksvc:edisplay 32s 5 OK / 5 True
Optional: Print a list of triggers in JSON format:
$ kn trigger list -o json
5.5.4. Describe triggers from the command line
Using the Knative (kn
) CLI to describe triggers provides a streamlined and intuitive user interface.
5.5.4.1. Describing a trigger by using the Knative CLI
You can use the kn trigger describe
command to print information about existing triggers in your cluster by using the Knative CLI.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a trigger.
Procedure
Enter the command:
$ kn trigger describe <trigger_name>
Example output
Name: ping Namespace: default Labels: eventing.knative.dev/broker=default Annotations: eventing.knative.dev/creator=kube:admin, eventing.knative.dev/lastModifier=kube:admin Age: 2m Broker: default Filter: type: dev.knative.event Sink: Name: edisplay Namespace: default Resource: Service (serving.knative.dev/v1) Conditions: OK TYPE AGE REASON ++ Ready 2m ++ BrokerReady 2m ++ DependencyReady 2m ++ Subscribed 2m ++ SubscriberResolved 2m
5.5.5. Connecting a trigger to a sink
You can connect a trigger to a sink, so that events from a broker are filtered before they are sent to the sink. A sink that is connected to a trigger is configured as a subscriber
in the Trigger
object’s resource spec.
Example of a Trigger
object connected to a Kafka sink
apiVersion: eventing.knative.dev/v1 kind: Trigger metadata: name: <trigger_name> 1 spec: ... subscriber: ref: apiVersion: eventing.knative.dev/v1alpha1 kind: KafkaSink name: <kafka_sink_name> 2
5.5.6. Filtering triggers from the command line
Using the Knative (kn
) CLI to filter events by using triggers provides a streamlined and intuitive user interface. You can use the kn trigger create
command, along with the appropriate flags, to filter events by using triggers.
5.5.6.1. Filtering events with triggers by using the Knative CLI
In the following trigger example, only events with the attribute type: dev.knative.samples.helloworld
are sent to the event sink:
$ kn trigger create <trigger_name> --broker <broker_name> --filter type=dev.knative.samples.helloworld --sink ksvc:<service_name>
You can also filter events by using multiple attributes. The following example shows how to filter events using the type, source, and extension attributes:
$ kn trigger create <trigger_name> --broker <broker_name> --sink ksvc:<service_name> \ --filter type=dev.knative.samples.helloworld \ --filter source=dev.knative.samples/helloworldsource \ --filter myextension=my-extension-value
5.5.7. Updating triggers from the command line
Using the Knative (kn
) CLI to update triggers provides a streamlined and intuitive user interface.
5.5.7.1. Updating a trigger by using the Knative CLI
You can use the kn trigger update
command with certain flags to update attributes for a trigger.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Update a trigger:
$ kn trigger update <trigger_name> --filter <key=value> --sink <sink_name> [flags]
You can update a trigger to filter exact event attributes that match incoming events. For example, using the
type
attribute:$ kn trigger update <trigger_name> --filter type=knative.dev.event
You can remove a filter attribute from a trigger. For example, you can remove the filter attribute with key
type
:$ kn trigger update <trigger_name> --filter type-
You can use the
--sink
parameter to change the event sink of a trigger:$ kn trigger update <trigger_name> --sink ksvc:my-event-sink
5.5.8. Deleting triggers from the command line
Using the Knative (kn
) CLI to delete a trigger provides a streamlined and intuitive user interface.
5.5.8.1. Deleting a trigger by using the Knative CLI
You can use the kn trigger delete
command to delete a trigger.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Delete a trigger:
$ kn trigger delete <trigger_name>
Verification
List existing triggers:
$ kn trigger list
Verify that the trigger no longer exists:
Example output
No triggers found.
5.6. Channels
5.6.1. Channels and subscriptions
Channels are custom resources that define a single event-forwarding and persistence layer. After events have been sent to a channel from an event source or producer, these events can be sent to multiple Knative services or other sinks by using a subscription.
You can create channels by instantiating a supported Channel
object, and configure re-delivery attempts by modifying the delivery
spec in a Subscription
object.
After you create a Channel
object, a mutating admission webhook adds a set of spec.channelTemplate
properties for the Channel
object based on the default channel implementation. For example, for an InMemoryChannel
default implementation, the Channel
object looks as follows:
apiVersion: messaging.knative.dev/v1 kind: Channel metadata: name: example-channel namespace: default spec: channelTemplate: apiVersion: messaging.knative.dev/v1 kind: InMemoryChannel
The channel controller then creates the backing channel instance based on the spec.channelTemplate
configuration.
The spec.channelTemplate
properties cannot be changed after creation, because they are set by the default channel mechanism rather than by the user.
When this mechanism is used with the preceding example, two objects are created: a generic backing channel and an InMemoryChannel
channel. If you are using a different default channel implementation, the InMemoryChannel
is replaced with one that is specific to your implementation. For example, with Knative Kafka, the KafkaChannel
channel is created.
The backing channel acts as a proxy that copies its subscriptions to the user-created channel object, and sets the user-created channel object status to reflect the status of the backing channel.
5.6.1.1. Channel implementation types
InMemoryChannel
and KafkaChannel
channel implementations can be used with OpenShift Serverless for development use.
The following are limitations of InMemoryChannel
type channels:
- No event persistence is available. If a pod goes down, events on that pod are lost.
-
InMemoryChannel
channels do not implement event ordering, so two events that are received in the channel at the same time can be delivered to a subscriber in any order. -
If a subscriber rejects an event, there are no re-delivery attempts by default. You can configure re-delivery attempts by modifying the
delivery
spec in theSubscription
object.
5.6.2. Creating channels
Channels are custom resources that define a single event-forwarding and persistence layer. After events have been sent to a channel from an event source or producer, these events can be sent to multiple Knative services or other sinks by using a subscription.
You can create channels by instantiating a supported Channel
object, and configure re-delivery attempts by modifying the delivery
spec in a Subscription
object.
5.6.2.1. Creating a channel by using the Administrator perspective
After Knative Eventing is installed on your cluster, you can create a channel by using the Administrator perspective.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
- You have logged in to the web console and are in the Administrator perspective.
- You have cluster administrator permissions for OpenShift Container Platform.
Procedure
- In the Administrator perspective of the OpenShift Container Platform web console, navigate to Serverless → Eventing.
- In the Create list, select Channel. You will be directed to the Channel page.
Select the type of
Channel
object that you want to create in the Type list.NoteCurrently only
InMemoryChannel
channel objects are supported by default. Kafka channels are available if you have installed Knative Kafka on OpenShift Serverless.- Click Create.
5.6.2.2. Creating a channel by using the Developer perspective
Using the OpenShift Container Platform web console provides a streamlined and intuitive user interface to create a channel. After Knative Eventing is installed on your cluster, you can create a channel by using the web console.
Prerequisites
- You have logged in to the OpenShift Container Platform web console.
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
- In the Developer perspective, navigate to +Add → Channel.
-
Select the type of
Channel
object that you want to create in the Type list. - Click Create.
Verification
Confirm that the channel now exists by navigating to the Topology page.
5.6.2.3. Creating a channel by using the Knative CLI
Using the Knative (kn
) CLI to create channels provides a more streamlined and intuitive user interface than modifying YAML files directly. You can use the kn channel create
command to create a channel.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Create a channel:
$ kn channel create <channel_name> --type <channel_type>
The channel type is optional, but where specified, must be given in the format
Group:Version:Kind
. For example, you can create anInMemoryChannel
object:$ kn channel create mychannel --type messaging.knative.dev:v1:InMemoryChannel
Example output
Channel 'mychannel' created in namespace 'default'.
Verification
To confirm that the channel now exists, list the existing channels and inspect the output:
$ kn channel list
Example output
kn channel list NAME TYPE URL AGE READY REASON mychannel InMemoryChannel http://mychannel-kn-channel.default.svc.cluster.local 93s True
Deleting a channel
Delete a channel:
$ kn channel delete <channel_name>
5.6.2.4. Creating a default implementation channel by using YAML
Creating Knative resources by using YAML files uses a declarative API, which enables you to describe channels declaratively and in a reproducible manner. To create a serverless channel by using YAML, you must create a YAML file that defines a Channel
object, then apply it by using the oc apply
command.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on the cluster.
-
Install the OpenShift CLI (
oc
). - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Create a
Channel
object as a YAML file:apiVersion: messaging.knative.dev/v1 kind: Channel metadata: name: example-channel namespace: default
Apply the YAML file:
$ oc apply -f <filename>
5.6.2.5. Creating a Kafka channel by using YAML
Creating Knative resources by using YAML files uses a declarative API, which enables you to describe channels declaratively and in a reproducible manner. You can create a Knative Eventing channel that is backed by Kafka topics by creating a Kafka channel. To create a Kafka channel by using YAML, you must create a YAML file that defines a KafkaChannel
object, then apply it by using the oc apply
command.
Prerequisites
-
The OpenShift Serverless Operator, Knative Eventing, and the
KnativeKafka
custom resource are installed on your OpenShift Container Platform cluster. -
Install the OpenShift CLI (
oc
). - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Create a
KafkaChannel
object as a YAML file:apiVersion: messaging.knative.dev/v1beta1 kind: KafkaChannel metadata: name: example-channel namespace: default spec: numPartitions: 3 replicationFactor: 1
ImportantOnly the
v1beta1
version of the API forKafkaChannel
objects on OpenShift Serverless is supported. Do not use thev1alpha1
version of this API, as this version is now deprecated.Apply the
KafkaChannel
YAML file:$ oc apply -f <filename>
5.6.2.6. Next steps
- After you have created a channel, create a subscription that allows event sinks to subscribe to channels and receive events.
- Configure event delivery parameters that are applied in cases where an event fails to be delivered to an event sink. See Examples of configuring event delivery parameters.
5.6.3. Default channel implementation
You can use the default-ch-webhook
config map to specify the default channel implementation of Knative Eventing. You can specify the default channel implementation for the entire cluster or for one or more namespaces. Currently the InMemoryChannel
and KafkaChannel
channel types are supported.
5.6.3.1. Configuring the default channel implementation
Prerequisites
- You have administrator permissions on OpenShift Container Platform.
- You have installed the OpenShift Serverless Operator and Knative Eventing on your cluster.
-
If you want to use Kafka channels as the default channel implementation, you must also install the
KnativeKafka
CR on your cluster.
Procedure
Modify the
KnativeEventing
custom resource to add configuration details for thedefault-ch-webhook
config map:apiVersion: operator.knative.dev/v1beta1 kind: KnativeEventing metadata: name: knative-eventing namespace: knative-eventing spec: config: 1 default-ch-webhook: 2 default-ch-config: | clusterDefault: 3 apiVersion: messaging.knative.dev/v1 kind: InMemoryChannel spec: delivery: backoffDelay: PT0.5S backoffPolicy: exponential retry: 5 namespaceDefaults: 4 my-namespace: apiVersion: messaging.knative.dev/v1beta1 kind: KafkaChannel spec: numPartitions: 1 replicationFactor: 1
- 1
- In
spec.config
, you can specify the config maps that you want to add modified configurations for. - 2
- The
default-ch-webhook
config map can be used to specify the default channel implementation for the cluster or for one or more namespaces. - 3
- The cluster-wide default channel type configuration. In this example, the default channel implementation for the cluster is
InMemoryChannel
. - 4
- The namespace-scoped default channel type configuration. In this example, the default channel implementation for the
my-namespace
namespace isKafkaChannel
.
ImportantConfiguring a namespace-specific default overrides any cluster-wide settings.
5.6.4. Security configuration for Knative Kafka channels
5.6.4.1. Configuring TLS authentication for Kafka channels
Transport Layer Security (TLS) is used by Apache Kafka clients and servers to encrypt traffic between Knative and Kafka, as well as for authentication. TLS is the only supported method of traffic encryption for Knative Kafka.
Prerequisites
- You have cluster or dedicated administrator permissions on OpenShift Container Platform.
-
The OpenShift Serverless Operator, Knative Eventing, and the
KnativeKafka
CR are installed on your OpenShift Container Platform cluster. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
You have a Kafka cluster CA certificate stored as a
.pem
file. -
You have a Kafka cluster client certificate and a key stored as
.pem
files. -
Install the OpenShift CLI (
oc
).
Procedure
Create the certificate files as secrets in your chosen namespace:
$ oc create secret -n <namespace> generic <kafka_auth_secret> \ --from-file=ca.crt=caroot.pem \ --from-file=user.crt=certificate.pem \ --from-file=user.key=key.pem
ImportantUse the key names
ca.crt
,user.crt
, anduser.key
. Do not change them.Start editing the
KnativeKafka
custom resource:$ oc edit knativekafka
Reference your secret and the namespace of the secret:
apiVersion: operator.serverless.openshift.io/v1alpha1 kind: KnativeKafka metadata: namespace: knative-eventing name: knative-kafka spec: channel: authSecretName: <kafka_auth_secret> authSecretNamespace: <kafka_auth_secret_namespace> bootstrapServers: <bootstrap_servers> enabled: true source: enabled: true
NoteMake sure to specify the matching port in the bootstrap server.
For example:
apiVersion: operator.serverless.openshift.io/v1alpha1 kind: KnativeKafka metadata: namespace: knative-eventing name: knative-kafka spec: channel: authSecretName: tls-user authSecretNamespace: kafka bootstrapServers: eventing-kafka-bootstrap.kafka.svc:9094 enabled: true source: enabled: true
5.6.4.2. Configuring SASL authentication for Kafka channels
Simple Authentication and Security Layer (SASL) is used by Apache Kafka for authentication. If you use SASL authentication on your cluster, users must provide credentials to Knative for communicating with the Kafka cluster; otherwise events cannot be produced or consumed.
Prerequisites
- You have cluster or dedicated administrator permissions on OpenShift Container Platform.
-
The OpenShift Serverless Operator, Knative Eventing, and the
KnativeKafka
CR are installed on your OpenShift Container Platform cluster. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
- You have a username and password for a Kafka cluster.
-
You have chosen the SASL mechanism to use, for example,
PLAIN
,SCRAM-SHA-256
, orSCRAM-SHA-512
. -
If TLS is enabled, you also need the
ca.crt
certificate file for the Kafka cluster. -
Install the OpenShift CLI (
oc
).
Procedure
Create the certificate files as secrets in your chosen namespace:
$ oc create secret -n <namespace> generic <kafka_auth_secret> \ --from-file=ca.crt=caroot.pem \ --from-literal=password="SecretPassword" \ --from-literal=saslType="SCRAM-SHA-512" \ --from-literal=user="my-sasl-user"
-
Use the key names
ca.crt
,password
, andsasl.mechanism
. Do not change them. If you want to use SASL with public CA certificates, you must use the
tls.enabled=true
flag, rather than theca.crt
argument, when creating the secret. For example:$ oc create secret -n <namespace> generic <kafka_auth_secret> \ --from-literal=tls.enabled=true \ --from-literal=password="SecretPassword" \ --from-literal=saslType="SCRAM-SHA-512" \ --from-literal=user="my-sasl-user"
-
Use the key names
Start editing the
KnativeKafka
custom resource:$ oc edit knativekafka
Reference your secret and the namespace of the secret:
apiVersion: operator.serverless.openshift.io/v1alpha1 kind: KnativeKafka metadata: namespace: knative-eventing name: knative-kafka spec: channel: authSecretName: <kafka_auth_secret> authSecretNamespace: <kafka_auth_secret_namespace> bootstrapServers: <bootstrap_servers> enabled: true source: enabled: true
NoteMake sure to specify the matching port in the bootstrap server.
For example:
apiVersion: operator.serverless.openshift.io/v1alpha1 kind: KnativeKafka metadata: namespace: knative-eventing name: knative-kafka spec: channel: authSecretName: scram-user authSecretNamespace: kafka bootstrapServers: eventing-kafka-bootstrap.kafka.svc:9093 enabled: true source: enabled: true
5.7. Subscriptions
5.7.1. Creating subscriptions
After you have created a channel and an event sink, you can create a subscription to enable event delivery. Subscriptions are created by configuring a Subscription
object, which specifies the channel and the sink (also known as a subscriber) to deliver events to.
5.7.1.1. Creating a subscription by using the Administrator perspective
After you have created a channel and an event sink, also known as a subscriber, you can create a subscription to enable event delivery. Subscriptions are created by configuring a Subscription
object, which specifies the channel and the subscriber to deliver events to. You can also specify some subscriber-specific options, such as how to handle failures.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
- You have logged in to the web console and are in the Administrator perspective.
- You have cluster administrator permissions for OpenShift Container Platform.
- You have created a Knative channel.
- You have created a Knative service to use as a subscriber.
Procedure
- In the Administrator perspective of the OpenShift Container Platform web console, navigate to Serverless → Eventing.
- In the Channel tab, select the Options menu for the channel that you want to add a subscription to.
- Click Add Subscription in the list.
- In the Add Subscription dialogue box, select a Subscriber for the subscription. The subscriber is the Knative service that receives events from the channel.
- Click Add.
5.7.1.2. Creating a subscription by using the Developer perspective
After you have created a channel and an event sink, you can create a subscription to enable event delivery. Using the OpenShift Container Platform web console provides a streamlined and intuitive user interface to create a subscription.
Prerequisites
- The OpenShift Serverless Operator, Knative Serving, and Knative Eventing are installed on your OpenShift Container Platform cluster.
- You have logged in to the web console.
- You have created an event sink, such as a Knative service, and a channel.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
- In the Developer perspective, navigate to the Topology page.
Create a subscription using one of the following methods:
Hover over the channel that you want to create a subscription for, and drag the arrow. The Add Subscription option is displayed.
- Select your sink in the Subscriber list.
- Click Add.
- If the service is available in the Topology view under the same namespace or project as the channel, click on the channel that you want to create a subscription for, and drag the arrow directly to a service to immediately create a subscription from the channel to that service.
Verification
After the subscription has been created, you can see it represented as a line that connects the channel to the service in the Topology view:
5.7.1.3. Creating a subscription by using YAML
After you have created a channel and an event sink, you can create a subscription to enable event delivery. Creating Knative resources by using YAML files uses a declarative API, which enables you to describe subscriptions declaratively and in a reproducible manner. To create a subscription by using YAML, you must create a YAML file that defines a Subscription
object, then apply it by using the oc apply
command.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on the cluster.
-
Install the OpenShift CLI (
oc
). - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Create a
Subscription
object:Create a YAML file and copy the following sample code into it:
apiVersion: messaging.knative.dev/v1beta1 kind: Subscription metadata: name: my-subscription 1 namespace: default spec: channel: 2 apiVersion: messaging.knative.dev/v1beta1 kind: Channel name: example-channel delivery: 3 deadLetterSink: ref: apiVersion: serving.knative.dev/v1 kind: Service name: error-handler subscriber: 4 ref: apiVersion: serving.knative.dev/v1 kind: Service name: event-display
- 1
- Name of the subscription.
- 2
- Configuration settings for the channel that the subscription connects to.
- 3
- Configuration settings for event delivery. This tells the subscription what happens to events that cannot be delivered to the subscriber. When this is configured, events that failed to be consumed are sent to the
deadLetterSink
. The event is dropped, no re-delivery of the event is attempted, and an error is logged in the system. ThedeadLetterSink
value must be a Destination. - 4
- Configuration settings for the subscriber. This is the event sink that events are delivered to from the channel.
Apply the YAML file:
$ oc apply -f <filename>
5.7.1.4. Creating a subscription by using the Knative CLI
After you have created a channel and an event sink, you can create a subscription to enable event delivery. Using the Knative (kn
) CLI to create subscriptions provides a more streamlined and intuitive user interface than modifying YAML files directly. You can use the kn subscription create
command with the appropriate flags to create a subscription.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Create a subscription to connect a sink to a channel:
$ kn subscription create <subscription_name> \ --channel <group:version:kind>:<channel_name> \ 1 --sink <sink_prefix>:<sink_name> \ 2 --sink-dead-letter <sink_prefix>:<sink_name> 3
- 1
--channel
specifies the source for cloud events that should be processed. You must provide the channel name. If you are not using the defaultInMemoryChannel
channel that is backed by theChannel
custom resource, you must prefix the channel name with the<group:version:kind>
for the specified channel type. For example, this will bemessaging.knative.dev:v1beta1:KafkaChannel
for a Kafka backed channel.- 2
--sink
specifies the target destination to which the event should be delivered. By default, the<sink_name>
is interpreted as a Knative service of this name, in the same namespace as the subscription. You can specify the type of the sink by using one of the following prefixes:ksvc
- A Knative service.
channel
- A channel that should be used as destination. Only default channel types can be referenced here.
broker
- An Eventing broker.
- 3
- Optional:
--sink-dead-letter
is an optional flag that can be used to specify a sink which events should be sent to in cases where events fail to be delivered. For more information, see the OpenShift Serverless Event delivery documentation.Example command
$ kn subscription create mysubscription --channel mychannel --sink ksvc:event-display
Example output
Subscription 'mysubscription' created in namespace 'default'.
Verification
To confirm that the channel is connected to the event sink, or subscriber, by a subscription, list the existing subscriptions and inspect the output:
$ kn subscription list
Example output
NAME CHANNEL SUBSCRIBER REPLY DEAD LETTER SINK READY REASON mysubscription Channel:mychannel ksvc:event-display True
Deleting a subscription
Delete a subscription:
$ kn subscription delete <subscription_name>
5.7.1.5. Next steps
- Configure event delivery parameters that are applied in cases where an event fails to be delivered to an event sink. See Examples of configuring event delivery parameters.
5.7.2. Managing subscriptions
5.7.2.1. Describing subscriptions by using the Knative CLI
You can use the kn subscription describe
command to print information about a subscription in the terminal by using the Knative (kn
) CLI. Using the Knative CLI to describe subscriptions provides a more streamlined and intuitive user interface than viewing YAML files directly.
Prerequisites
-
You have installed the Knative (
kn
) CLI. - You have created a subscription in your cluster.
Procedure
Describe a subscription:
$ kn subscription describe <subscription_name>
Example output
Name: my-subscription Namespace: default Annotations: messaging.knative.dev/creator=openshift-user, messaging.knative.dev/lastModifier=min ... Age: 43s Channel: Channel:my-channel (messaging.knative.dev/v1) Subscriber: URI: http://edisplay.default.example.com Reply: Name: default Resource: Broker (eventing.knative.dev/v1) DeadLetterSink: Name: my-sink Resource: Service (serving.knative.dev/v1) Conditions: OK TYPE AGE REASON ++ Ready 43s ++ AddedToChannel 43s ++ ChannelReady 43s ++ ReferencesResolved 43s
5.7.2.2. Listing subscriptions by using the Knative CLI
You can use the kn subscription list
command to list existing subscriptions on your cluster by using the Knative (kn
) CLI. Using the Knative CLI to list subscriptions provides a streamlined and intuitive user interface.
Prerequisites
-
You have installed the Knative (
kn
) CLI.
Procedure
List subscriptions on your cluster:
$ kn subscription list
Example output
NAME CHANNEL SUBSCRIBER REPLY DEAD LETTER SINK READY REASON mysubscription Channel:mychannel ksvc:event-display True
5.7.2.3. Updating subscriptions by using the Knative CLI
You can use the kn subscription update
command as well as the appropriate flags to update a subscription from the terminal by using the Knative (kn
) CLI. Using the Knative CLI to update subscriptions provides a more streamlined and intuitive user interface than updating YAML files directly.
Prerequisites
-
You have installed the Knative (
kn
) CLI. - You have created a subscription.
Procedure
Update a subscription:
$ kn subscription update <subscription_name> \ --sink <sink_prefix>:<sink_name> \ 1 --sink-dead-letter <sink_prefix>:<sink_name> 2
- 1
--sink
specifies the updated target destination to which the event should be delivered. You can specify the type of the sink by using one of the following prefixes:ksvc
- A Knative service.
channel
- A channel that should be used as destination. Only default channel types can be referenced here.
broker
- An Eventing broker.
- 2
- Optional:
--sink-dead-letter
is an optional flag that can be used to specify a sink which events should be sent to in cases where events fail to be delivered. For more information, see the OpenShift Serverless Event delivery documentation.Example command
$ kn subscription update mysubscription --sink ksvc:event-display
5.8. Event discovery
5.8.1. Listing event sources and event source types
It is possible to view a list of all event sources or event source types that exist or are available for use on your OpenShift Container Platform cluster. You can use the Knative (kn
) CLI or the Developer perspective in the OpenShift Container Platform web console to list available event sources or event source types.
5.8.2. Listing event source types from the command line
Using the Knative (kn
) CLI provides a streamlined and intuitive user interface to view available event source types on your cluster.
5.8.2.1. Listing available event source types by using the Knative CLI
You can list event source types that can be created and used on your cluster by using the kn source list-types
CLI command.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on the cluster.
-
You have installed the Knative (
kn
) CLI.
Procedure
List the available event source types in the terminal:
$ kn source list-types
Example output
TYPE NAME DESCRIPTION ApiServerSource apiserversources.sources.knative.dev Watch and send Kubernetes API events to a sink PingSource pingsources.sources.knative.dev Periodically send ping events to a sink SinkBinding sinkbindings.sources.knative.dev Binding for connecting a PodSpecable to a sink
Optional: You can also list the available event source types in YAML format:
$ kn source list-types -o yaml
5.8.3. Listing event source types from the Developer perspective
It is possible to view a list of all available event source types on your cluster. Using the OpenShift Container Platform web console provides a streamlined and intuitive user interface to view available event source types.
5.8.3.1. Viewing available event source types within the Developer perspective
Prerequisites
- You have logged in to the OpenShift Container Platform web console.
- The OpenShift Serverless Operator and Knative Eventing are installed on your OpenShift Container Platform cluster.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
- Access the Developer perspective.
- Click +Add.
- Click Event Source.
- View the available event source types.
5.8.4. Listing event sources from the command line
Using the Knative (kn
) CLI provides a streamlined and intuitive user interface to view existing event sources on your cluster.
5.8.4.1. Listing available event sources by using the Knative CLI
You can list existing event sources by using the kn source list
command.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on the cluster.
-
You have installed the Knative (
kn
) CLI.
Procedure
List the existing event sources in the terminal:
$ kn source list
Example output
NAME TYPE RESOURCE SINK READY a1 ApiServerSource apiserversources.sources.knative.dev ksvc:eshow2 True b1 SinkBinding sinkbindings.sources.knative.dev ksvc:eshow3 False p1 PingSource pingsources.sources.knative.dev ksvc:eshow1 True
Optional: You can list event sources of a specific type only, by using the
--type
flag:$ kn source list --type <event_source_type>
Example command
$ kn source list --type PingSource
Example output
NAME TYPE RESOURCE SINK READY p1 PingSource pingsources.sources.knative.dev ksvc:eshow1 True
5.9. Tuning eventing configuration
5.9.1. Overriding Knative Eventing system deployment configurations
You can override the default configurations for some specific deployments by modifying the deployments
spec in the KnativeEventing
custom resource (CR). Currently, overriding default configuration settings is supported for the eventing-controller
, eventing-webhook
, and imc-controller
fields, as well as for the readiness
and liveness
fields for probes.
The replicas
spec cannot override the number of replicas for deployments that use the Horizontal Pod Autoscaler (HPA), and does not work for the eventing-webhook
deployment.
You can only override probes that are defined in the deployment by default.
All Knative Serving deployments define a readiness and a liveness probe by default, with these exceptions:
-
net-kourier-controller
and3scale-kourier-gateway
only define a readiness probe. -
net-istio-controller
andnet-istio-webhook
define no probes.
5.9.1.1. Overriding deployment configurations
Currently, overriding default configuration settings is supported for the eventing-controller
, eventing-webhook
, and imc-controller
fields, as well as for the readiness
and liveness
fields for probes.
The replicas
spec cannot override the number of replicas for deployments that use the Horizontal Pod Autoscaler (HPA), and does not work for the eventing-webhook
deployment.
In the following example, a KnativeEventing
CR overrides the eventing-controller
deployment so that:
-
The
readiness
probe timeouteventing-controller
is set to be 10 seconds. - The deployment has specified CPU and memory resource limits.
- The deployment has 3 replicas.
-
The
example-label: label
label is added. -
The
example-annotation: annotation
annotation is added. -
The
nodeSelector
field is set to select nodes with thedisktype: hdd
label.
KnativeEventing CR example
apiVersion: operator.knative.dev/v1beta1
kind: KnativeEventing
metadata:
name: knative-eventing
namespace: knative-eventing
spec:
deployments:
- name: eventing-controller
readinessProbes: 1
- container: controller
timeoutSeconds: 10
resources:
- container: eventing-controller
requests:
cpu: 300m
memory: 100Mi
limits:
cpu: 1000m
memory: 250Mi
replicas: 3
labels:
example-label: label
annotations:
example-annotation: annotation
nodeSelector:
disktype: hdd
- 1
- You can use the
readiness
andliveness
probe overrides to override all fields of a probe in a container of a deployment as specified in the Kubernetes API except for the fields related to the probe handler:exec
,grpc
,httpGet
, andtcpSocket
.
The KnativeEventing
CR label and annotation settings override the deployment’s labels and annotations for both the deployment itself and the resulting pods.
Additional resources
5.9.2. High availability
High availability (HA) is a standard feature of Kubernetes APIs that helps to ensure that APIs stay operational if a disruption occurs. In an HA deployment, if an active controller crashes or is deleted, another controller is readily available. This controller takes over processing of the APIs that were being serviced by the controller that is now unavailable.
HA in OpenShift Serverless is available through leader election, which is enabled by default after the Knative Serving or Eventing control plane is installed. When using a leader election HA pattern, instances of controllers are already scheduled and running inside the cluster before they are required. These controller instances compete to use a shared resource, known as the leader election lock. The instance of the controller that has access to the leader election lock resource at any given time is called the leader.
HA in OpenShift Serverless is available through leader election, which is enabled by default after the Knative Serving or Eventing control plane is installed. When using a leader election HA pattern, instances of controllers are already scheduled and running inside the cluster before they are required. These controller instances compete to use a shared resource, known as the leader election lock. The instance of the controller that has access to the leader election lock resource at any given time is called the leader.
5.9.2.1. Configuring high availability replicas for Knative Eventing
High availability (HA) is available by default for the Knative Eventing eventing-controller
, eventing-webhook
, imc-controller
, imc-dispatcher
, and mt-broker-controller
components, which are configured to have two replicas each by default. You can change the number of replicas for these components by modifying the spec.high-availability.replicas
value in the KnativeEventing
custom resource (CR).
For Knative Eventing, the mt-broker-filter
and mt-broker-ingress
deployments are not scaled by HA. If multiple deployments are needed, scale these components manually.
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- The OpenShift Serverless Operator and Knative Eventing are installed on your cluster.
Procedure
- In the OpenShift Container Platform web console Administrator perspective, navigate to OperatorHub → Installed Operators.
-
Select the
knative-eventing
namespace. - Click Knative Eventing in the list of Provided APIs for the OpenShift Serverless Operator to go to the Knative Eventing tab.
Click knative-eventing, then go to the YAML tab in the knative-eventing page.
Modify the number of replicas in the
KnativeEventing
CR:Example YAML
apiVersion: operator.knative.dev/v1beta1 kind: KnativeEventing metadata: name: knative-eventing namespace: knative-eventing spec: high-availability: replicas: 3
5.9.2.2. Configuring high availability replicas for Knative Kafka
High availability (HA) is available by default for the Knative Kafka kafka-controller
and kafka-webhook-eventing
components, which are configured to have two each replicas by default. You can change the number of replicas for these components by modifying the spec.high-availability.replicas
value in the KnativeKafka
custom resource (CR).
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- The OpenShift Serverless Operator and Knative Kafka are installed on your cluster.
Procedure
- In the OpenShift Container Platform web console Administrator perspective, navigate to OperatorHub → Installed Operators.
-
Select the
knative-eventing
namespace. - Click Knative Kafka in the list of Provided APIs for the OpenShift Serverless Operator to go to the Knative Kafka tab.
Click knative-kafka, then go to the YAML tab in the knative-kafka page.
Modify the number of replicas in the
KnativeKafka
CR:Example YAML
apiVersion: operator.serverless.openshift.io/v1alpha1 kind: KnativeKafka metadata: name: knative-kafka namespace: knative-eventing spec: high-availability: replicas: 3
Chapter 6. Functions
6.1. Setting up OpenShift Serverless Functions
To improve the process of deployment of your application code, you can use OpenShift Serverless to deploy stateless, event-driven functions as a Knative service on OpenShift Container Platform. If you want to develop functions, you must complete the set up steps.
6.1.1. Prerequisites
To enable the use of OpenShift Serverless Functions on your cluster, you must complete the following steps:
The OpenShift Serverless Operator and Knative Serving are installed on your cluster.
NoteFunctions are deployed as a Knative service. If you want to use event-driven architecture with your functions, you must also install Knative Eventing.
-
You have the
oc
CLI installed. -
You have the Knative (
kn
) CLI installed. Installing the Knative CLI enables the use ofkn func
commands which you can use to create and manage functions. - You have installed Docker Container Engine or Podman version 3.4.7 or higher.
- You have access to an available image registry, such as the OpenShift Container Registry.
- If you are using Quay.io as the image registry, you must ensure that either the repository is not private, or that you have followed the OpenShift Container Platform documentation on Allowing pods to reference images from other secured registries.
- If you are using the OpenShift Container Registry, a cluster administrator must expose the registry.
6.1.2. Setting up Podman
To use advanced container management features, you might want to use Podman with OpenShift Serverless Functions. To do so, you need to start the Podman service and configure the Knative (kn
) CLI to connect to it.
Procedure
Start the Podman service that serves the Docker API on a UNIX socket at
${XDG_RUNTIME_DIR}/podman/podman.sock
:$ systemctl start --user podman.socket
NoteOn most systems, this socket is located at
/run/user/$(id -u)/podman/podman.sock
.Establish the environment variable that is used to build a function:
$ export DOCKER_HOST="unix://${XDG_RUNTIME_DIR}/podman/podman.sock"
Run the build command inside your function project directory with the
-v
flag to see verbose output. You should see a connection to your local UNIX socket:$ kn func build -v
6.1.3. Setting up Podman on macOS
To use advanced container management features, you might want to use Podman with OpenShift Serverless Functions. To do so on macOS, you need to start the Podman machine and configure the Knative (kn
) CLI to connect to it.
Procedure
Create the Podman machine:
$ podman machine init --memory=8192 --cpus=2 --disk-size=20
Start the Podman machine, which serves the Docker API on a UNIX socket:
$ podman machine start Starting machine "podman-machine-default" Waiting for VM ... Mounting volume... /Users/myuser:/Users/user [...truncated output...] You can still connect Docker API clients by setting DOCKER_HOST using the following command in your terminal session: export DOCKER_HOST='unix:///Users/myuser/.local/share/containers/podman/machine/podman-machine-default/podman.sock' Machine "podman-machine-default" started successfully
NoteOn most macOS systems, this socket is located at
/Users/myuser/.local/share/containers/podman/machine/podman-machine-default/podman.sock
.Establish the environment variable that is used to build a function:
$ export DOCKER_HOST='unix:///Users/myuser/.local/share/containers/podman/machine/podman-machine-default/podman.sock'
Run the build command inside your function project directory with the
-v
flag to see verbose output. You should see a connection to your local UNIX socket:$ kn func build -v
6.1.4. Next steps
- For more information about Docker Container Engine or Podman, see Container build tool options.
- See Getting started with functions.
6.2. Getting started with functions
Function lifecycle management includes creating, building, and deploying a function. Optionally, you can also test a deployed function by invoking it. You can do all of these operations on OpenShift Serverless using the kn func
tool.
6.2.1. Prerequisites
Before you can complete the following procedures, you must ensure that you have completed all of the prerequisite tasks in Setting up OpenShift Serverless Functions.
6.2.2. Creating functions
Before you can build and deploy a function, you must create it by using the Knative (kn
) CLI. You can specify the path, runtime, template, and image registry as flags on the command line, or use the -c
flag to start the interactive experience in the terminal.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI.
Procedure
Create a function project:
$ kn func create -r <repository> -l <runtime> -t <template> <path>
-
Accepted runtime values include
quarkus
,node
,typescript
,go
,python
,springboot
, andrust
. Accepted template values include
http
andcloudevents
.Example command
$ kn func create -l typescript -t cloudevents examplefunc
Example output
Created typescript function in /home/user/demo/examplefunc
Alternatively, you can specify a repository that contains a custom template.
Example command
$ kn func create -r https://github.com/boson-project/templates/ -l node -t hello-world examplefunc
Example output
Created node function in /home/user/demo/examplefunc
-
Accepted runtime values include
6.2.3. Running a function locally
You can use the kn func run
command to run a function locally in the current directory or in the directory specified by the --path
flag. If the function that you are running has never previously been built, or if the project files have been modified since the last time it was built, the kn func run
command builds the function before running it by default.
Example command to run a function in the current directory
$ kn func run
Example command to run a function in a directory specified as a path
$ kn func run --path=<directory_path>
You can also force a rebuild of an existing image before running the function, even if there have been no changes to the project files, by using the --build
flag:
Example run command using the build flag
$ kn func run --build
If you set the build
flag as false, this disables building of the image, and runs the function using the previously built image:
Example run command using the build flag
$ kn func run --build=false
You can use the help command to learn more about kn func run
command options:
Build help command
$ kn func help run
6.2.4. Building functions
Before you can run a function, you must build the function project. If you are using the kn func run
command, the function is built automatically. However, you can use the kn func build
command to build a function without running it, which can be useful for advanced users or debugging scenarios.
The kn func build
command creates an OCI container image that can be run locally on your computer or on an OpenShift Container Platform cluster. This command uses the function project name and the image registry name to construct a fully qualified image name for your function.
6.2.4.1. Image container types
By default, kn func build
creates a container image by using Red Hat Source-to-Image (S2I) technology.
Example build command using Red Hat Source-to-Image (S2I)
$ kn func build
6.2.4.2. Image registry types
The OpenShift Container Registry is used by default as the image registry for storing function images.
Example build command using OpenShift Container Registry
$ kn func build
Example output
Building function image Function image has been built, image: registry.redhat.io/example/example-function:latest
You can override using OpenShift Container Registry as the default image registry by using the --registry
flag:
Example build command overriding OpenShift Container Registry to use quay.io
$ kn func build --registry quay.io/username
Example output
Building function image Function image has been built, image: quay.io/username/example-function:latest
6.2.4.3. Push flag
You can add the --push
flag to a kn func build
command to automatically push the function image after it is successfully built:
Example build command using OpenShift Container Registry
$ kn func build --push
6.2.4.4. Help command
You can use the help command to learn more about kn func build
command options:
Build help command
$ kn func help build
6.2.5. Deploying functions
You can deploy a function to your cluster as a Knative service by using the kn func deploy
command. If the targeted function is already deployed, it is updated with a new container image that is pushed to a container image registry, and the Knative service is updated.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
- You must have already created and initialized the function that you want to deploy.
Procedure
Deploy a function:
$ kn func deploy [-n <namespace> -p <path> -i <image>]
Example output
Function deployed at: http://func.example.com
-
If no
namespace
is specified, the function is deployed in the current namespace. -
The function is deployed from the current directory, unless a
path
is specified. - The Knative service name is derived from the project name, and cannot be changed using this command.
-
If no
6.2.6. Invoking a deployed function with a test event
You can use the kn func invoke
CLI command to send a test request to invoke a function either locally or on your OpenShift Container Platform cluster. You can use this command to test that a function is working and able to receive events correctly. Invoking a function locally is useful for a quick test during function development. Invoking a function on the cluster is useful for testing that is closer to the production environment.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
- You must have already deployed the function that you want to invoke.
Procedure
Invoke a function:
$ kn func invoke
-
The
kn func invoke
command only works when there is either a local container image currently running, or when there is a function deployed in the cluster. -
The
kn func invoke
command executes on the local directory by default, and assumes that this directory is a function project.
-
The
6.2.7. Deleting a function
You can delete a function by using the kn func delete
command. This is useful when a function is no longer required, and can help to save resources on your cluster.
Procedure
Delete a function:
$ kn func delete [<function_name> -n <namespace> -p <path>]
-
If the name or path of the function to delete is not specified, the current directory is searched for a
func.yaml
file that is used to determine the function to delete. -
If the namespace is not specified, it defaults to the
namespace
value in thefunc.yaml
file.
-
If the name or path of the function to delete is not specified, the current directory is searched for a
6.2.8. Additional resources
6.2.9. Next steps
6.3. On-cluster function building and deploying
Instead of building a function locally, you can build a function directly on the cluster. When using this workflow on a local development machine, you only need to work with the function source code. This is useful, for example, when you cannot install on-cluster function building tools, such as docker or podman.
6.3.1. Building and deploying functions on the cluster
You can use the Knative (kn
) CLI to initiate a function project build and then deploy the function directly on the cluster. To build a function project in this way, the source code for your function project must exist in a Git repository branch that is accessible to your cluster.
Prerequisites
- Red Hat OpenShift Pipelines must be installed on your cluster.
-
You have installed the OpenShift CLI (
oc
). -
You have installed the Knative (
kn
) CLI.
Procedure
In each namespace where you want to run Pipelines and deploy a function, you must create the following resources:
Create the
s2i
Tekton task to be able to use Source-to-Image in the pipeline:$ oc apply -f https://raw.githubusercontent.com/openshift-knative/kn-plugin-func/serverless-1.28.0/pipelines/resources/tekton/task/func-s2i/0.1/func-s2i.yaml
Create the
kn func
deploy Tekton task to be able to deploy the function in the pipeline:$ oc apply -f https://raw.githubusercontent.com/openshift-knative/kn-plugin-func/serverless-1.28.0/pipelines/resources/tekton/task/func-deploy/0.1/func-deploy.yaml
Create a function:
$ kn func create <function_name> -l <runtime>
-
After you have created a new function project, you must add the project to a Git repository and ensure that the repository is available to the cluster. Information about this Git repository is used to update the
func.yaml
file in the next step. Update the configuration in the
func.yaml
file for your function project to enable on-cluster builds for the Git repository:... git: url: <git_repository_url> 1 revision: main 2 contextDir: <directory_path> 3 ...
- Implement the business logic of your function. Then, use Git to commit and push the changes.
Deploy your function:
$ kn func deploy --remote
If you are not logged into the container registry referenced in your function configuration, you are prompted to provide credentials for the remote container registry that hosts the function image:
Example output and prompts
🕕 Creating Pipeline resources Please provide credentials for image registry used by Pipeline. ? Server: https://index.docker.io/v1/ ? Username: my-repo ? Password: ******** Function deployed at URL: http://test-function.default.svc.cluster.local
-
To update your function, commit and push new changes by using Git, then run the
kn func deploy --remote
command again.
6.3.2. Specifying function revision
When building and deploying a function on the cluster, you must specify the location of the function code by specifying the Git repository, branch, and subdirectory within the repository. You do not need to specify the branch if you use the main
branch. Similarly, you do not need to specify the subdirectory if your function is at the root of the repository. You can specify these parameters in the func.yaml
configuration file, or by using flags with the kn func deploy
command.
Prerequisites
- Red Hat OpenShift Pipelines must be installed on your cluster.
-
You have installed the OpenShift (
oc
) CLI. -
You have installed the Knative (
kn
) CLI.
Procedure
Deploy your function:
$ kn func deploy --remote \ 1 --git-url <repo-url> \ 2 [--git-branch <branch>] \ 3 [--git-dir <function-dir>] 4
- 1
- With the
--remote
flag, the build runs remotely. - 2
- Substitute
<repo-url>
with the URL of the Git repository. - 3
- Substitute
<branch>
with the Git branch, tag, or commit. If using the latest commit on themain
branch, you can skip this flag. - 4
- Substitute
<function-dir>
with the directory containing the function if it is different than the repository root directory.
For example:
$ kn func deploy --remote \ --git-url https://example.com/alice/myfunc.git \ --git-branch my-feature \ --git-dir functions/example-func/
6.4. Developing Quarkus functions
After you have created a Quarkus function project, you can modify the template files provided to add business logic to your function. This includes configuring function invocation and the returned headers and status codes.
6.4.1. Prerequisites
- Before you can develop functions, you must complete the setup steps in Setting up OpenShift Serverless Functions.
6.4.2. Quarkus function template structure
When you create a Quarkus function by using the Knative (kn
) CLI, the project directory looks similar to a typical Maven project. Additionally, the project contains the func.yaml
file, which is used for configuring the function.
Both http
and event
trigger functions have the same template structure:
Template structure
. ├── func.yaml 1 ├── mvnw ├── mvnw.cmd ├── pom.xml 2 ├── README.md └── src ├── main │ ├── java │ │ └── functions │ │ ├── Function.java 3 │ │ ├── Input.java │ │ └── Output.java │ └── resources │ └── application.properties └── test └── java └── functions 4 ├── FunctionTest.java └── NativeFunctionIT.java
- 1
- Used to determine the image name and registry.
- 2
- The Project Object Model (POM) file contains project configuration, such as information about dependencies. You can add additional dependencies by modifying this file.
Example of additional dependencies
... <dependencies> <dependency> <groupId>junit</groupId> <artifactId>junit</artifactId> <version>4.11</version> <scope>test</scope> </dependency> <dependency> <groupId>org.assertj</groupId> <artifactId>assertj-core</artifactId> <version>3.8.0</version> <scope>test</scope> </dependency> </dependencies> ...
Dependencies are downloaded during the first compilation.
- 3
- The function project must contain a Java method annotated with
@Funq
. You can place this method in theFunction.java
class. - 4
- Contains simple test cases that can be used to test your function locally.
6.4.3. About invoking Quarkus functions
You can create a Quarkus project that responds to cloud events, or one that responds to simple HTTP requests. Cloud events in Knative are transported over HTTP as a POST request, so either function type can listen and respond to incoming HTTP requests.
When an incoming request is received, Quarkus functions are invoked with an instance of a permitted type.
Invocation method | Data type contained in the instance | Example of data |
---|---|---|
HTTP POST request | JSON object in the body of the request |
|
HTTP GET request | Data in the query string |
|
|
JSON object in the |
|
The following example shows a function that receives and processes the customerId
and productId
purchase data that is listed in the previous table:
Example Quarkus function
public class Functions { @Funq public void processPurchase(Purchase purchase) { // process the purchase } }
The corresponding Purchase
JavaBean class that contains the purchase data looks as follows:
Example class
public class Purchase { private long customerId; private long productId; // getters and setters }
6.4.3.1. Invocation examples
The following example code defines three functions named withBeans
, withCloudEvent
, and withBinary
;
Example
import io.quarkus.funqy.Funq; import io.quarkus.funqy.knative.events.CloudEvent; public class Input { private String message; // getters and setters } public class Output { private String message; // getters and setters } public class Functions { @Funq public Output withBeans(Input in) { // function body } @Funq public CloudEvent<Output> withCloudEvent(CloudEvent<Input> in) { // function body } @Funq public void withBinary(byte[] in) { // function body } }
The withBeans
function of the Functions
class can be invoked by:
An HTTP POST request with a JSON body:
$ curl "http://localhost:8080/withBeans" -X POST \ -H "Content-Type: application/json" \ -d '{"message": "Hello there."}'
An HTTP GET request with query parameters:
$ curl "http://localhost:8080/withBeans?message=Hello%20there." -X GET
A
CloudEvent
object in binary encoding:$ curl "http://localhost:8080/" -X POST \ -H "Content-Type: application/json" \ -H "Ce-SpecVersion: 1.0" \ -H "Ce-Type: withBeans" \ -H "Ce-Source: cURL" \ -H "Ce-Id: 42" \ -d '{"message": "Hello there."}'
A
CloudEvent
object in structured encoding:$ curl http://localhost:8080/ \ -H "Content-Type: application/cloudevents+json" \ -d '{ "data": {"message":"Hello there."}, "datacontenttype": "application/json", "id": "42", "source": "curl", "type": "withBeans", "specversion": "1.0"}'
The withCloudEvent
function of the Functions
class can be invoked by using a CloudEvent
object, similarly to the withBeans
function. However, unlike withBeans
, withCloudEvent
cannot be invoked with a plain HTTP request.
The withBinary
function of the Functions
class can be invoked by:
A
CloudEvent
object in binary encoding:$ curl "http://localhost:8080/" -X POST \ -H "Content-Type: application/octet-stream" \ -H "Ce-SpecVersion: 1.0"\ -H "Ce-Type: withBinary" \ -H "Ce-Source: cURL" \ -H "Ce-Id: 42" \ --data-binary '@img.jpg'
A
CloudEvent
object in structured encoding:$ curl http://localhost:8080/ \ -H "Content-Type: application/cloudevents+json" \ -d "{ \"data_base64\": \"$(base64 --wrap=0 img.jpg)\", \"datacontenttype\": \"application/octet-stream\", \"id\": \"42\", \"source\": \"curl\", \"type\": \"withBinary\", \"specversion\": \"1.0\"}"
6.4.4. CloudEvent attributes
If you need to read or write the attributes of a CloudEvent, such as type
or subject
, you can use the CloudEvent<T>
generic interface and the CloudEventBuilder
builder. The <T>
type parameter must be one of the permitted types.
In the following example, CloudEventBuilder
is used to return success or failure of processing the purchase:
public class Functions { private boolean _processPurchase(Purchase purchase) { // do stuff } public CloudEvent<Void> processPurchase(CloudEvent<Purchase> purchaseEvent) { System.out.println("subject is: " + purchaseEvent.subject()); if (!_processPurchase(purchaseEvent.data())) { return CloudEventBuilder.create() .type("purchase.error") .build(); } return CloudEventBuilder.create() .type("purchase.success") .build(); } }
6.4.5. Quarkus function return values
Functions can return an instance of any type from the list of permitted types. Alternatively, they can return the Uni<T>
type, where the <T>
type parameter can be of any type from the permitted types.
The Uni<T>
type is useful if a function calls asynchronous APIs, because the returned object is serialized in the same format as the received object. For example:
- If a function receives an HTTP request, then the returned object is sent in the body of an HTTP response.
-
If a function receives a
CloudEvent
object in binary encoding, then the returned object is sent in the data property of a binary-encodedCloudEvent
object.
The following example shows a function that fetches a list of purchases:
Example command
public class Functions { @Funq public List<Purchase> getPurchasesByName(String name) { // logic to retrieve purchases } }
- Invoking this function through an HTTP request produces an HTTP response that contains a list of purchases in the body of the response.
-
Invoking this function through an incoming
CloudEvent
object produces aCloudEvent
response with a list of purchases in thedata
property.
6.4.5.1. Permitted types
The input and output of a function can be any of the void
, String
, or byte[]
types. Additionally, they can be primitive types and their wrappers, for example, int
and Integer
. They can also be the following complex objects: Javabeans, maps, lists, arrays, and the special CloudEvents<T>
type.
Maps, lists, arrays, the <T>
type parameter of the CloudEvents<T>
type, and attributes of Javabeans can only be of types listed here.
Example
public class Functions { public List<Integer> getIds(); public Purchase[] getPurchasesByName(String name); public String getNameById(int id); public Map<String,Integer> getNameIdMapping(); public void processImage(byte[] img); }
6.4.6. Testing Quarkus functions
Quarkus functions can be tested locally on your computer. In the default project that is created when you create a function using kn func create
, there is the src/test/
directory, which contains basic Maven tests. These tests can be extended as needed.
Prerequisites
- You have created a Quarkus function.
-
You have installed the Knative (
kn
) CLI.
Procedure
- Navigate to the project folder for your function.
Run the Maven tests:
$ ./mvnw test
6.4.7. Next steps
6.5. Developing Node.js functions
After you have created a Node.js function project, you can modify the template files provided to add business logic to your function. This includes configuring function invocation and the returned headers and status codes.
6.5.1. Prerequisites
- Before you can develop functions, you must complete the steps in Setting up OpenShift Serverless Functions.
6.5.2. Node.js function template structure
When you create a Node.js function using the Knative (kn
) CLI, the project directory looks like a typical Node.js project. The only exception is the additional func.yaml
file, which is used to configure the function.
Both http
and event
trigger functions have the same template structure:
Template structure
. ├── func.yaml 1 ├── index.js 2 ├── package.json 3 ├── README.md └── test 4 ├── integration.js └── unit.js
- 1
- The
func.yaml
configuration file is used to determine the image name and registry. - 2
- Your project must contain an
index.js
file which exports a single function. - 3
- You are not restricted to the dependencies provided in the template
package.json
file. You can add additional dependencies as you would in any other Node.js project.Example of adding npm dependencies
npm install --save opossum
When the project is built for deployment, these dependencies are included in the created runtime container image.
- 4
- Integration and unit test scripts are provided as part of the function template.
6.5.3. About invoking Node.js functions
When using the Knative (kn
) CLI to create a function project, you can generate a project that responds to CloudEvents, or one that responds to simple HTTP requests. CloudEvents in Knative are transported over HTTP as a POST request, so both function types listen for and respond to incoming HTTP events.
Node.js functions can be invoked with a simple HTTP request. When an incoming request is received, functions are invoked with a context
object as the first parameter.
6.5.3.1. Node.js context objects
Functions are invoked by providing a context
object as the first parameter. This object provides access to the incoming HTTP request information.
Example context object
function handle(context, data)
This information includes the HTTP request method, any query strings or headers sent with the request, the HTTP version, and the request body. Incoming requests that contain a CloudEvent
attach the incoming instance of the CloudEvent to the context object so that it can be accessed by using context.cloudevent
.
6.5.3.1.1. Context object methods
The context
object has a single method, cloudEventResponse()
, that accepts a data value and returns a CloudEvent.
In a Knative system, if a function deployed as a service is invoked by an event broker sending a CloudEvent, the broker examines the response. If the response is a CloudEvent, this event is handled by the broker.
Example context object method
// Expects to receive a CloudEvent with customer data function handle(context, customer) { // process the customer const processed = handle(customer); return context.cloudEventResponse(customer) .source('/handle') .type('fn.process.customer') .response(); }
6.5.3.1.2. CloudEvent data
If the incoming request is a CloudEvent, any data associated with the CloudEvent is extracted from the event and provided as a second parameter. For example, if a CloudEvent is received that contains a JSON string in its data property that is similar to the following:
{ "customerId": "0123456", "productId": "6543210" }
When invoked, the second parameter to the function, after the context
object, will be a JavaScript object that has customerId
and productId
properties.
Example signature
function handle(context, data)
The data
parameter in this example is a JavaScript object that contains the customerId
and productId
properties.
6.5.4. Node.js function return values
Functions can return any valid JavaScript type or can have no return value. When a function has no return value specified, and no failure is indicated, the caller receives a 204 No Content
response.
Functions can also return a CloudEvent or a Message
object in order to push events into the Knative Eventing system. In this case, the developer is not required to understand or implement the CloudEvent messaging specification. Headers and other relevant information from the returned values are extracted and sent with the response.
Example
function handle(context, customer) { // process customer and return a new CloudEvent return new CloudEvent({ source: 'customer.processor', type: 'customer.processed' }) }
6.5.4.1. Returning headers
You can set a response header by adding a headers
property to the return
object. These headers are extracted and sent with the response to the caller.
Example response header
function handle(context, customer) { // process customer and return custom headers // the response will be '204 No content' return { headers: { customerid: customer.id } }; }
6.5.4.2. Returning status codes
You can set a status code that is returned to the caller by adding a statusCode
property to the return
object:
Example status code
function handle(context, customer) { // process customer if (customer.restricted) { return { statusCode: 451 } } }
Status codes can also be set for errors that are created and thrown by the function:
Example error status code
function handle(context, customer) { // process customer if (customer.restricted) { const err = new Error(‘Unavailable for legal reasons’); err.statusCode = 451; throw err; } }
6.5.5. Testing Node.js functions
Node.js functions can be tested locally on your computer. In the default project that is created when you create a function by using kn func create
, there is a test folder that contains some simple unit and integration tests.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. -
You have created a function by using
kn func create
.
Procedure
- Navigate to the test folder for your function.
Run the tests:
$ npm test
6.5.6. Next steps
- See the Node.js context object reference documentation.
- Build and deploy a function.
6.6. Developing TypeScript functions
After you have created a TypeScript function project, you can modify the template files provided to add business logic to your function. This includes configuring function invocation and the returned headers and status codes.
6.6.1. Prerequisites
- Before you can develop functions, you must complete the steps in Setting up OpenShift Serverless Functions.
6.6.2. TypeScript function template structure
When you create a TypeScript function using the Knative (kn
) CLI, the project directory looks like a typical TypeScript project. The only exception is the additional func.yaml
file, which is used for configuring the function.
Both http
and event
trigger functions have the same template structure:
Template structure
. ├── func.yaml 1 ├── package.json 2 ├── package-lock.json ├── README.md ├── src │ └── index.ts 3 ├── test 4 │ ├── integration.ts │ └── unit.ts └── tsconfig.json
- 1
- The
func.yaml
configuration file is used to determine the image name and registry. - 2
- You are not restricted to the dependencies provided in the template
package.json
file. You can add additional dependencies as you would in any other TypeScript project.Example of adding npm dependencies
npm install --save opossum
When the project is built for deployment, these dependencies are included in the created runtime container image.
- 3
- Your project must contain an
src/index.js
file which exports a function namedhandle
. - 4
- Integration and unit test scripts are provided as part of the function template.
6.6.3. About invoking TypeScript functions
When using the Knative (kn
) CLI to create a function project, you can generate a project that responds to CloudEvents or one that responds to simple HTTP requests. CloudEvents in Knative are transported over HTTP as a POST request, so both function types listen for and respond to incoming HTTP events.
TypeScript functions can be invoked with a simple HTTP request. When an incoming request is received, functions are invoked with a context
object as the first parameter.
6.6.3.1. TypeScript context objects
To invoke a function, you provide a context
object as the first parameter. Accessing properties of the context
object can provide information about the incoming HTTP request.
Example context object
function handle(context:Context): string
This information includes the HTTP request method, any query strings or headers sent with the request, the HTTP version, and the request body. Incoming requests that contain a CloudEvent
attach the incoming instance of the CloudEvent to the context object so that it can be accessed by using context.cloudevent
.
6.6.3.1.1. Context object methods
The context
object has a single method, cloudEventResponse()
, that accepts a data value and returns a CloudEvent.
In a Knative system, if a function deployed as a service is invoked by an event broker sending a CloudEvent, the broker examines the response. If the response is a CloudEvent, this event is handled by the broker.
Example context object method
// Expects to receive a CloudEvent with customer data export function handle(context: Context, cloudevent?: CloudEvent): CloudEvent { // process the customer const customer = cloudevent.data; const processed = processCustomer(customer); return context.cloudEventResponse(customer) .source('/customer/process') .type('customer.processed') .response(); }
6.6.3.1.2. Context types
The TypeScript type definition files export the following types for use in your functions.
Exported type definitions
// Invokable is the expeted Function signature for user functions export interface Invokable { (context: Context, cloudevent?: CloudEvent): any } // Logger can be used for structural logging to the console export interface Logger { debug: (msg: any) => void, info: (msg: any) => void, warn: (msg: any) => void, error: (msg: any) => void, fatal: (msg: any) => void, trace: (msg: any) => void, } // Context represents the function invocation context, and provides // access to the event itself as well as raw HTTP objects. export interface Context { log: Logger; req: IncomingMessage; query?: Record<string, any>; body?: Record<string, any>|string; method: string; headers: IncomingHttpHeaders; httpVersion: string; httpVersionMajor: number; httpVersionMinor: number; cloudevent: CloudEvent; cloudEventResponse(data: string|object): CloudEventResponse; } // CloudEventResponse is a convenience class used to create // CloudEvents on function returns export interface CloudEventResponse { id(id: string): CloudEventResponse; source(source: string): CloudEventResponse; type(type: string): CloudEventResponse; version(version: string): CloudEventResponse; response(): CloudEvent; }
6.6.3.1.3. CloudEvent data
If the incoming request is a CloudEvent, any data associated with the CloudEvent is extracted from the event and provided as a second parameter. For example, if a CloudEvent is received that contains a JSON string in its data property that is similar to the following:
{ "customerId": "0123456", "productId": "6543210" }
When invoked, the second parameter to the function, after the context
object, will be a JavaScript object that has customerId
and productId
properties.
Example signature
function handle(context: Context, cloudevent?: CloudEvent): CloudEvent
The cloudevent
parameter in this example is a JavaScript object that contains the customerId
and productId
properties.
6.6.4. TypeScript function return values
Functions can return any valid JavaScript type or can have no return value. When a function has no return value specified, and no failure is indicated, the caller receives a 204 No Content
response.
Functions can also return a CloudEvent or a Message
object in order to push events into the Knative Eventing system. In this case, the developer is not required to understand or implement the CloudEvent messaging specification. Headers and other relevant information from the returned values are extracted and sent with the response.
Example
export const handle: Invokable = function ( context: Context, cloudevent?: CloudEvent ): Message { // process customer and return a new CloudEvent const customer = cloudevent.data; return HTTP.binary( new CloudEvent({ source: 'customer.processor', type: 'customer.processed' }) ); };
6.6.4.1. Returning headers
You can set a response header by adding a headers
property to the return
object. These headers are extracted and sent with the response to the caller.
Example response header
export function handle(context: Context, cloudevent?: CloudEvent): Record<string, any> { // process customer and return custom headers const customer = cloudevent.data as Record<string, any>; return { headers: { 'customer-id': customer.id } }; }
6.6.4.2. Returning status codes
You can set a status code that is returned to the caller by adding a statusCode
property to the return
object:
Example status code
export function handle(context: Context, cloudevent?: CloudEvent): Record<string, any> { // process customer const customer = cloudevent.data as Record<string, any>; if (customer.restricted) { return { statusCode: 451 } } // business logic, then return { statusCode: 240 } }
Status codes can also be set for errors that are created and thrown by the function:
Example error status code
export function handle(context: Context, cloudevent?: CloudEvent): Record<string, string> { // process customer const customer = cloudevent.data as Record<string, any>; if (customer.restricted) { const err = new Error(‘Unavailable for legal reasons’); err.statusCode = 451; throw err; } }
6.6.5. Testing TypeScript functions
TypeScript functions can be tested locally on your computer. In the default project that is created when you create a function using kn func create
, there is a test folder that contains some simple unit and integration tests.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. -
You have created a function by using
kn func create
.
Procedure
If you have not previously run tests, install the dependencies first:
$ npm install
- Navigate to the test folder for your function.
Run the tests:
$ npm test
6.6.6. Next steps
- See the TypeScript context object reference documentation.
- Build and deploy a function.
- See the Pino API documentation for more information about logging with functions.
6.7. Developing Python functions
OpenShift Serverless Functions with Python is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.
For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope.
After you have created a Python function project, you can modify the template files provided to add business logic to your function. This includes configuring function invocation and the returned headers and status codes.
6.7.1. Prerequisites
- Before you can develop functions, you must complete the steps in Setting up OpenShift Serverless Functions.
6.7.2. Python function template structure
When you create a Python function by using the Knative (kn
) CLI, the project directory looks similar to a typical Python project. Python functions have very few restrictions. The only requirements are that your project contains a func.py
file that contains a main()
function, and a func.yaml
configuration file.
Developers are not restricted to the dependencies provided in the template requirements.txt
file. Additional dependencies can be added as they would be in any other Python project. When the project is built for deployment, these dependencies will be included in the created runtime container image.
Both http
and event
trigger functions have the same template structure:
Template structure
fn ├── func.py 1 ├── func.yaml 2 ├── requirements.txt 3 └── test_func.py 4
6.7.3. About invoking Python functions
Python functions can be invoked with a simple HTTP request. When an incoming request is received, functions are invoked with a context
object as the first parameter.
The context
object is a Python class with two attributes:
-
The
request
attribute is always present, and contains the Flaskrequest
object. -
The second attribute,
cloud_event
, is populated if the incoming request is aCloudEvent
object.
Developers can access any CloudEvent
data from the context object.
Example context object
def main(context: Context): """ The context parameter contains the Flask request object and any CloudEvent received with the request. """ print(f"Method: {context.request.method}") print(f"Event data {context.cloud_event.data}") # ... business logic here
6.7.4. Python function return values
Functions can return any value supported by Flask. This is because the invocation framework proxies these values directly to the Flask server.
Example
def main(context: Context): body = { "message": "Howdy!" } headers = { "content-type": "application/json" } return body, 200, headers
Functions can set both headers and response codes as secondary and tertiary response values from function invocation.
6.7.4.1. Returning CloudEvents
Developers can use the @event
decorator to tell the invoker that the function return value must be converted to a CloudEvent before sending the response.
Example
@event("event_source"="/my/function", "event_type"="my.type") def main(context): # business logic here data = do_something() # more data processing return data
This example sends a CloudEvent as the response value, with a type of "my.type"
and a source of "/my/function"
. The CloudEvent data
property is set to the returned data
variable. The event_source
and event_type
decorator attributes are both optional.
6.7.5. Testing Python functions
You can test Python functions locally on your computer. The default project contains a test_func.py
file, which provides a simple unit test for functions.
The default test framework for Python functions is unittest
. You can use a different test framework if you prefer.
Prerequisites
To run Python functions tests locally, you must install the required dependencies:
$ pip install -r requirements.txt
Procedure
-
Navigate to the folder for your function that contains the
test_func.py
file. Run the tests:
$ python3 test_func.py
6.7.6. Next steps
6.8. Using functions with Knative Eventing
Functions are deployed as Knative services on an OpenShift Container Platform cluster. You can connect functions to Knative Eventing components so that they can receive incoming events.
6.8.1. Connect an event source to a function using the Developer perspective
Functions are deployed as Knative services on an OpenShift Container Platform cluster. When you create an event source by using the OpenShift Container Platform web console, you can specify a deployed function that events are sent to from that source.
Prerequisites
- The OpenShift Serverless Operator, Knative Serving, and Knative Eventing are installed on your OpenShift Container Platform cluster.
- You have logged in to the web console and are in the Developer perspective.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
- You have created and deployed a function.
Procedure
- Create an event source of any type, by navigating to +Add → Event Source and selecting the event source type that you want to create.
- In the Sink section of the Create Event Source form view, select your function in the Resource list.
- Click Create.
Verification
You can verify that the event source was created and is connected to the function by viewing the Topology page.
- In the Developer perspective, navigate to Topology.
- View the event source and click the connected function to see the function details in the right panel.
6.9. Function project configuration in func.yaml
The func.yaml
file contains the configuration for your function project. Values specified in func.yaml
are used when you execute a kn func
command. For example, when you run the kn func build
command, the value in the build
field is used. In some cases, you can override these values with command line flags or environment variables.
6.9.1. Configurable fields in func.yaml
Many of the fields in func.yaml
are generated automatically when you create, build, and deploy your function. However, there are also fields that you modify manually to change things, such as the function name or the image name.
6.9.1.1. buildEnvs
The buildEnvs
field enables you to set environment variables to be available to the environment that builds your function. Unlike variables set using envs
, a variable set using buildEnv
is not available during function runtime.
You can set a buildEnv
variable directly from a value. In the following example, the buildEnv
variable named EXAMPLE1
is directly assigned the one
value:
buildEnvs: - name: EXAMPLE1 value: one
You can also set a buildEnv
variable from a local environment variable. In the following example, the buildEnv
variable named EXAMPLE2
is assigned the value of the LOCAL_ENV_VAR
local environment variable:
buildEnvs: - name: EXAMPLE1 value: '{{ env:LOCAL_ENV_VAR }}'
6.9.1.2. envs
The envs
field enables you to set environment variables to be available to your function at runtime. You can set an environment variable in several different ways:
- Directly from a value.
- From a value assigned to a local environment variable. See the section "Referencing local environment variables from func.yaml fields" for more information.
- From a key-value pair stored in a secret or config map.
- You can also import all key-value pairs stored in a secret or config map, with keys used as names of the created environment variables.
This examples demonstrates the different ways to set an environment variable:
name: test namespace: "" runtime: go ... envs: - name: EXAMPLE1 1 value: value - name: EXAMPLE2 2 value: '{{ env:LOCAL_ENV_VALUE }}' - name: EXAMPLE3 3 value: '{{ secret:mysecret:key }}' - name: EXAMPLE4 4 value: '{{ configMap:myconfigmap:key }}' - value: '{{ secret:mysecret2 }}' 5 - value: '{{ configMap:myconfigmap2 }}' 6
- 1
- An environment variable set directly from a value.
- 2
- An environment variable set from a value assigned to a local environment variable.
- 3
- An environment variable assigned from a key-value pair stored in a secret.
- 4
- An environment variable assigned from a key-value pair stored in a config map.
- 5
- A set of environment variables imported from key-value pairs of a secret.
- 6
- A set of environment variables imported from key-value pairs of a config map.
6.9.1.3. builder
The builder
field specifies the strategy used by the function to build the image. It accepts values of pack
or s2i
.
6.9.1.4. build
The build
field indicates how the function should be built. The value local
indicates that the function is built locally on your machine. The value git
indicates that the function is built on a cluster by using the values specified in the git
field.
6.9.1.5. volumes
The volumes
field enables you to mount secrets and config maps as a volume accessible to the function at the specified path, as shown in the following example:
name: test namespace: "" runtime: go ... volumes: - secret: mysecret 1 path: /workspace/secret - configMap: myconfigmap 2 path: /workspace/configmap
6.9.1.6. options
The options
field enables you to modify Knative Service properties for the deployed function, such as autoscaling. If these options are not set, the default ones are used.
These options are available:
scale
-
min
: The minimum number of replicas. Must be a non-negative integer. The default is 0. -
max
: The maximum number of replicas. Must be a non-negative integer. The default is 0, which means no limit. -
metric
: Defines which metric type is watched by the Autoscaler. It can be set toconcurrency
, which is the default, orrps
. -
target
: Recommendation for when to scale up based on the number of concurrently incoming requests. Thetarget
option can be a float value greater than 0.01. The default is 100, unless theoptions.resources.limits.concurrency
is set, in which casetarget
defaults to its value. -
utilization
: Percentage of concurrent requests utilization allowed before scaling up. It can be a float value between 1 and 100. The default is 70.
-
resources
requests
-
cpu
: A CPU resource request for the container with deployed function. -
memory
: A memory resource request for the container with deployed function.
-
limits
-
cpu
: A CPU resource limit for the container with deployed function. -
memory
: A memory resource limit for the container with deployed function. -
concurrency
: Hard Limit of concurrent requests to be processed by a single replica. It can be integer value greater than or equal to 0, default is 0 - meaning no limit.
-
This is an example configuration of the scale
options:
name: test namespace: "" runtime: go ... options: scale: min: 0 max: 10 metric: concurrency target: 75 utilization: 75 resources: requests: cpu: 100m memory: 128Mi limits: cpu: 1000m memory: 256Mi concurrency: 100
6.9.1.7. image
The image
field sets the image name for your function after it has been built. You can modify this field. If you do, the next time you run kn func build
or kn func deploy
, the function image will be created with the new name.
6.9.1.8. imageDigest
The imageDigest
field contains the SHA256 hash of the image manifest when the function is deployed. Do not modify this value.
6.9.1.9. labels
The labels
field enables you to set labels on a deployed function.
You can set a label directly from a value. In the following example, the label with the role
key is directly assigned the value of backend
:
labels: - key: role value: backend
You can also set a label from a local environment variable. In the following example, the label with the author
key is assigned the value of the USER
local environment variable:
labels: - key: author value: '{{ env:USER }}'
6.9.1.10. name
The name
field defines the name of your function. This value is used as the name of your Knative service when it is deployed. You can change this field to rename the function on subsequent deployments.
6.9.1.11. namespace
The namespace
field specifies the namespace in which your function is deployed.
6.9.1.12. runtime
The runtime
field specifies the language runtime for your function, for example, python
.
6.9.2. Referencing local environment variables from func.yaml fields
If you want to avoid storing sensitive information such as an API key in the function configuration, you can add a reference to an environment variable available in the local environment. You can do this by modifying the envs
field in the func.yaml
file.
Prerequisites
- You need to have the function project created.
- The local environment needs to contain the variable that you want to reference.
Procedure
To refer to a local environment variable, use the following syntax:
{{ env:ENV_VAR }}
Substitute
ENV_VAR
with the name of the variable in the local environment that you want to use.For example, you might have the
API_KEY
variable available in the local environment. You can assign its value to theMY_API_KEY
variable, which you can then directly use within your function:Example function
name: test namespace: "" runtime: go ... envs: - name: MY_API_KEY value: '{{ env:API_KEY }}' ...
6.9.3. Additional resources
6.10. Accessing secrets and config maps from functions
After your functions have been deployed to the cluster, they can access data stored in secrets and config maps. This data can be mounted as volumes, or assigned to environment variables. You can configure this access interactively by using the Knative CLI, or by manually by editing the function configuration YAML file.
To access secrets and config maps, the function must be deployed on the cluster. This functionality is not available to a function running locally.
If a secret or config map value cannot be accessed, the deployment fails with an error message specifying the inaccessible values.
6.10.1. Modifying function access to secrets and config maps interactively
You can manage the secrets and config maps accessed by your function by using the kn func config
interactive utility. The available operations include listing, adding, and removing values stored in config maps and secrets as environment variables, as well as listing, adding, and removing volumes. This functionality enables you to manage what data stored on the cluster is accessible by your function.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a function.
Procedure
Run the following command in the function project directory:
$ kn func config
Alternatively, you can specify the function project directory using the
--path
or-p
option.Use the interactive interface to perform the necessary operation. For example, using the utility to list configured volumes produces an output similar to this:
$ kn func config ? What do you want to configure? Volumes ? What operation do you want to perform? List Configured Volumes mounts: - Secret "mysecret" mounted at path: "/workspace/secret" - Secret "mysecret2" mounted at path: "/workspace/secret2"
This scheme shows all operations available in the interactive utility and how to navigate to them:
kn func config ├─> Environment variables │ ├─> Add │ │ ├─> ConfigMap: Add all key-value pairs from a config map │ │ ├─> ConfigMap: Add value from a key in a config map │ │ ├─> Secret: Add all key-value pairs from a secret │ │ └─> Secret: Add value from a key in a secret │ ├─> List: List all configured environment variables │ └─> Remove: Remove a configured environment variable └─> Volumes ├─> Add │ ├─> ConfigMap: Mount a config map as a volume │ └─> Secret: Mount a secret as a volume ├─> List: List all configured volumes └─> Remove: Remove a configured volume
Optional. Deploy the function to make the changes take effect:
$ kn func deploy -p test
6.10.2. Modifying function access to secrets and config maps interactively by using specialized commands
Every time you run the kn func config
utility, you need to navigate the entire dialogue to select the operation you need, as shown in the previous section. To save steps, you can directly execute a specific operation by running a more specific form of the kn func config
command:
To list configured environment variables:
$ kn func config envs [-p <function-project-path>]
To add environment variables to the function configuration:
$ kn func config envs add [-p <function-project-path>]
To remove environment variables from the function configuration:
$ kn func config envs remove [-p <function-project-path>]
To list configured volumes:
$ kn func config volumes [-p <function-project-path>]
To add a volume to the function configuration:
$ kn func config volumes add [-p <function-project-path>]
To remove a volume from the function configuration:
$ kn func config volumes remove [-p <function-project-path>]
6.10.3. Adding function access to secrets and config maps manually
You can manually add configuration for accessing secrets and config maps to your function. This might be preferable to using the kn func config
interactive utility and commands, for example when you have an existing configuration snippet.
6.10.3.1. Mounting a secret as a volume
You can mount a secret as a volume. Once a secret is mounted, you can access it from the function as a regular file. This enables you to store on the cluster data needed by the function, for example, a list of URIs that need to be accessed by the function.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a function.
Procedure
-
Open the
func.yaml
file for your function. For each secret you want to mount as a volume, add the following YAML to the
volumes
section:name: test namespace: "" runtime: go ... volumes: - secret: mysecret path: /workspace/secret
-
Substitute
mysecret
with the name of the target secret. Substitute
/workspace/secret
with the path where you want to mount the secret.For example, to mount the
addresses
secret, use the following YAML:name: test namespace: "" runtime: go ... volumes: - configMap: addresses path: /workspace/secret-addresses
-
Substitute
- Save the configuration.
6.10.3.2. Mounting a config map as a volume
You can mount a config map as a volume. Once a config map is mounted, you can access it from the function as a regular file. This enables you to store on the cluster data needed by the function, for example, a list of URIs that need to be accessed by the function.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a function.
Procedure
-
Open the
func.yaml
file for your function. For each config map you want to mount as a volume, add the following YAML to the
volumes
section:name: test namespace: "" runtime: go ... volumes: - configMap: myconfigmap path: /workspace/configmap
-
Substitute
myconfigmap
with the name of the target config map. Substitute
/workspace/configmap
with the path where you want to mount the config map.For example, to mount the
addresses
config map, use the following YAML:name: test namespace: "" runtime: go ... volumes: - configMap: addresses path: /workspace/configmap-addresses
-
Substitute
- Save the configuration.
6.10.3.3. Setting environment variable from a key value defined in a secret
You can set an environment variable from a key value defined as a secret. A value previously stored in a secret can then be accessed as an environment variable by the function at runtime. This can be useful for getting access to a value stored in a secret, such as the ID of a user.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a function.
Procedure
-
Open the
func.yaml
file for your function. For each value from a secret key-value pair that you want to assign to an environment variable, add the following YAML to the
envs
section:name: test namespace: "" runtime: go ... envs: - name: EXAMPLE value: '{{ secret:mysecret:key }}'
-
Substitute
EXAMPLE
with the name of the environment variable. -
Substitute
mysecret
with the name of the target secret. Substitute
key
with the key mapped to the target value.For example, to access the user ID that is stored in
userdetailssecret
, use the following YAML:name: test namespace: "" runtime: go ... envs: - value: '{{ configMap:userdetailssecret:userid }}'
-
Substitute
- Save the configuration.
6.10.3.4. Setting environment variable from a key value defined in a config map
You can set an environment variable from a key value defined as a config map. A value previously stored in a config map can then be accessed as an environment variable by the function at runtime. This can be useful for getting access to a value stored in a config map, such as the ID of a user.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a function.
Procedure
-
Open the
func.yaml
file for your function. For each value from a config map key-value pair that you want to assign to an environment variable, add the following YAML to the
envs
section:name: test namespace: "" runtime: go ... envs: - name: EXAMPLE value: '{{ configMap:myconfigmap:key }}'
-
Substitute
EXAMPLE
with the name of the environment variable. -
Substitute
myconfigmap
with the name of the target config map. Substitute
key
with the key mapped to the target value.For example, to access the user ID that is stored in
userdetailsmap
, use the following YAML:name: test namespace: "" runtime: go ... envs: - value: '{{ configMap:userdetailsmap:userid }}'
-
Substitute
- Save the configuration.
6.10.3.5. Setting environment variables from all values defined in a secret
You can set an environment variable from all values defined in a secret. Values previously stored in a secret can then be accessed as environment variables by the function at runtime. This can be useful for simultaneously getting access to a collection of values stored in a secret, for example, a set of data pertaining to a user.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a function.
Procedure
-
Open the
func.yaml
file for your function. For every secret for which you want to import all key-value pairs as environment variables, add the following YAML to the
envs
section:name: test namespace: "" runtime: go ... envs: - value: '{{ secret:mysecret }}' 1
- 1
- Substitute
mysecret
with the name of the target secret.
For example, to access all user data that is stored in
userdetailssecret
, use the following YAML:name: test namespace: "" runtime: go ... envs: - value: '{{ configMap:userdetailssecret }}'
- Save the configuration.
6.10.3.6. Setting environment variables from all values defined in a config map
You can set an environment variable from all values defined in a config map. Values previously stored in a config map can then be accessed as environment variables by the function at runtime. This can be useful for simultaneously getting access to a collection of values stored in a config map, for example, a set of data pertaining to a user.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a function.
Procedure
-
Open the
func.yaml
file for your function. For every config map for which you want to import all key-value pairs as environment variables, add the following YAML to the
envs
section:name: test namespace: "" runtime: go ... envs: - value: '{{ configMap:myconfigmap }}' 1
- 1
- Substitute
myconfigmap
with the name of the target config map.
For example, to access all user data that is stored in
userdetailsmap
, use the following YAML:name: test namespace: "" runtime: go ... envs: - value: '{{ configMap:userdetailsmap }}'
- Save the file.
6.11. Adding annotations to functions
You can add Kubernetes annotations to a deployed Serverless function. Annotations enable you to attach arbitrary metadata to a function, for example, a note about the function’s purpose. Annotations are added to the annotations
section of the func.yaml
configuration file.
There are two limitations of the function annotation feature:
-
After a function annotation propagates to the corresponding Knative service on the cluster, it cannot be removed from the service by deleting it from the
func.yaml
file. You must remove the annotation from the Knative service by modifying the YAML file of the service directly, or by using the OpenShift Container Platform web console. -
You cannot set annotations that are set by Knative, for example, the
autoscaling
annotations.
6.11.1. Adding annotations to a function
You can add annotations to a function. Similar to a label, an annotation is defined as a key-value map. Annotations are useful, for example, for providing metadata about a function, such as the function’s author.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a function.
Procedure
-
Open the
func.yaml
file for your function. For every annotation that you want to add, add the following YAML to the
annotations
section:name: test namespace: "" runtime: go ... annotations: <annotation_name>: "<annotation_value>" 1
- 1
- Substitute
<annotation_name>: "<annotation_value>"
with your annotation.
For example, to indicate that a function was authored by Alice, you might include the following annotation:
name: test namespace: "" runtime: go ... annotations: author: "alice@example.com"
- Save the configuration.
The next time you deploy your function to the cluster, the annotations are added to the corresponding Knative service.
6.12. Functions development reference guide
OpenShift Serverless Functions provides templates that can be used to create basic functions. A template initiates the function project boilerplate and prepares it for use with the kn func
tool. Each function template is tailored for a specific runtime and follows its conventions. With a template, you can initiate your function project automatically.
Templates for the following runtimes are available:
6.12.1. Node.js context object reference
The context
object has several properties that can be accessed by the function developer. Accessing these properties can provide information about HTTP requests and write output to the cluster logs.
6.12.1.1. log
Provides a logging object that can be used to write output to the cluster logs. The log adheres to the Pino logging API.
Example log
function handle(context) { context.log.info(“Processing customer”); }
You can access the function by using the kn func invoke
command:
Example command
$ kn func invoke --target 'http://example.function.com'
Example output
{"level":30,"time":1604511655265,"pid":3430203,"hostname":"localhost.localdomain","reqId":1,"msg":"Processing customer"}
You can change the log level to one of fatal
, error
, warn
, info
, debug
, trace
, or silent
. To do that, change the value of logLevel
by assigning one of these values to the environment variable FUNC_LOG_LEVEL
using the config
command.
6.12.1.2. query
Returns the query string for the request, if any, as key-value pairs. These attributes are also found on the context object itself.
Example query
function handle(context) { // Log the 'name' query parameter context.log.info(context.query.name); // Query parameters are also attached to the context context.log.info(context.name); }
You can access the function by using the kn func invoke
command:
Example command
$ kn func invoke --target 'http://example.com?name=tiger'
Example output
{"level":30,"time":1604511655265,"pid":3430203,"hostname":"localhost.localdomain","reqId":1,"msg":"tiger"}
6.12.1.3. body
Returns the request body if any. If the request body contains JSON code, this will be parsed so that the attributes are directly available.
Example body
function handle(context) { // log the incoming request body's 'hello' parameter context.log.info(context.body.hello); }
You can access the function by using the curl
command to invoke it:
Example command
$ kn func invoke -d '{"Hello": "world"}'
Example output
{"level":30,"time":1604511655265,"pid":3430203,"hostname":"localhost.localdomain","reqId":1,"msg":"world"}
6.12.1.4. headers
Returns the HTTP request headers as an object.
Example header
function handle(context) { context.log.info(context.headers["custom-header"]); }
You can access the function by using the kn func invoke
command:
Example command
$ kn func invoke --target 'http://example.function.com'
Example output
{"level":30,"time":1604511655265,"pid":3430203,"hostname":"localhost.localdomain","reqId":1,"msg":"some-value"}
6.12.1.5. HTTP requests
- method
- Returns the HTTP request method as a string.
- httpVersion
- Returns the HTTP version as a string.
- httpVersionMajor
- Returns the HTTP major version number as a string.
- httpVersionMinor
- Returns the HTTP minor version number as a string.
6.12.2. TypeScript context object reference
The context
object has several properties that can be accessed by the function developer. Accessing these properties can provide information about incoming HTTP requests and write output to the cluster logs.
6.12.2.1. log
Provides a logging object that can be used to write output to the cluster logs. The log adheres to the Pino logging API.
Example log
export function handle(context: Context): string { // log the incoming request body's 'hello' parameter if (context.body) { context.log.info((context.body as Record<string, string>).hello); } else { context.log.info('No data received'); } return 'OK'; }
You can access the function by using the kn func invoke
command:
Example command
$ kn func invoke --target 'http://example.function.com'
Example output
{"level":30,"time":1604511655265,"pid":3430203,"hostname":"localhost.localdomain","reqId":1,"msg":"Processing customer"}
You can change the log level to one of fatal
, error
, warn
, info
, debug
, trace
, or silent
. To do that, change the value of logLevel
by assigning one of these values to the environment variable FUNC_LOG_LEVEL
using the config
command.
6.12.2.2. query
Returns the query string for the request, if any, as key-value pairs. These attributes are also found on the context object itself.
Example query
export function handle(context: Context): string { // log the 'name' query parameter if (context.query) { context.log.info((context.query as Record<string, string>).name); } else { context.log.info('No data received'); } return 'OK'; }
You can access the function by using the kn func invoke
command:
Example command
$ kn func invoke --target 'http://example.function.com' --data '{"name": "tiger"}'
Example output
{"level":30,"time":1604511655265,"pid":3430203,"hostname":"localhost.localdomain","reqId":1,"msg":"tiger"} {"level":30,"time":1604511655265,"pid":3430203,"hostname":"localhost.localdomain","reqId":1,"msg":"tiger"}
6.12.2.3. body
Returns the request body, if any. If the request body contains JSON code, this will be parsed so that the attributes are directly available.
Example body
export function handle(context: Context): string { // log the incoming request body's 'hello' parameter if (context.body) { context.log.info((context.body as Record<string, string>).hello); } else { context.log.info('No data received'); } return 'OK'; }
You can access the function by using the kn func invoke
command:
Example command
$ kn func invoke --target 'http://example.function.com' --data '{"hello": "world"}'
Example output
{"level":30,"time":1604511655265,"pid":3430203,"hostname":"localhost.localdomain","reqId":1,"msg":"world"}
6.12.2.4. headers
Returns the HTTP request headers as an object.
Example header
export function handle(context: Context): string { // log the incoming request body's 'hello' parameter if (context.body) { context.log.info((context.headers as Record<string, string>)['custom-header']); } else { context.log.info('No data received'); } return 'OK'; }
You can access the function by using the curl
command to invoke it:
Example command
$ curl -H'x-custom-header: some-value’' http://example.function.com
Example output
{"level":30,"time":1604511655265,"pid":3430203,"hostname":"localhost.localdomain","reqId":1,"msg":"some-value"}
6.12.2.5. HTTP requests
- method
- Returns the HTTP request method as a string.
- httpVersion
- Returns the HTTP version as a string.
- httpVersionMajor
- Returns the HTTP major version number as a string.
- httpVersionMinor
- Returns the HTTP minor version number as a string.
Chapter 7. Knative CLI
7.1. Knative Serving CLI commands
7.1.1. kn service commands
You can use the following commands to create and manage Knative services.
7.1.1.1. Creating serverless applications by using the Knative CLI
Using the Knative (kn
) CLI to create serverless applications provides a more streamlined and intuitive user interface over modifying YAML files directly. You can use the kn service create
command to create a basic serverless application.
Prerequisites
- OpenShift Serverless Operator and Knative Serving are installed on your cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Create a Knative service:
$ kn service create <service-name> --image <image> --tag <tag-value>
Where:
-
--image
is the URI of the image for the application. --tag
is an optional flag that can be used to add a tag to the initial revision that is created with the service.Example command
$ kn service create event-display \ --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest
Example output
Creating service 'event-display' in namespace 'default': 0.271s The Route is still working to reflect the latest desired specification. 0.580s Configuration "event-display" is waiting for a Revision to become ready. 3.857s ... 3.861s Ingress has not yet been reconciled. 4.270s Ready to serve. Service 'event-display' created with latest revision 'event-display-bxshg-1' and URL: http://event-display-default.apps-crc.testing
-
7.1.1.2. Updating serverless applications by using the Knative CLI
You can use the kn service update
command for interactive sessions on the command line as you build up a service incrementally. In contrast to the kn service apply
command, when using the kn service update
command you only have to specify the changes that you want to update, rather than the full configuration for the Knative service.
Example commands
Update a service by adding a new environment variable:
$ kn service update <service_name> --env <key>=<value>
Update a service by adding a new port:
$ kn service update <service_name> --port 80
Update a service by adding new request and limit parameters:
$ kn service update <service_name> --request cpu=500m --limit memory=1024Mi --limit cpu=1000m
Assign the
latest
tag to a revision:$ kn service update <service_name> --tag <revision_name>=latest
Update a tag from
testing
tostaging
for the latestREADY
revision of a service:$ kn service update <service_name> --untag testing --tag @latest=staging
Add the
test
tag to a revision that receives 10% of traffic, and send the rest of the traffic to the latestREADY
revision of a service:$ kn service update <service_name> --tag <revision_name>=test --traffic test=10,@latest=90
7.1.1.3. Applying service declarations
You can declaratively configure a Knative service by using the kn service apply
command. If the service does not exist it is created, otherwise the existing service is updated with the options that have been changed.
The kn service apply
command is especially useful for shell scripts or in a continuous integration pipeline, where users typically want to fully specify the state of the service in a single command to declare the target state.
When using kn service apply
you must provide the full configuration for the Knative service. This is different from the kn service update
command, which only requires you to specify in the command the options that you want to update.
Example commands
Create a service:
$ kn service apply <service_name> --image <image>
Add an environment variable to a service:
$ kn service apply <service_name> --image <image> --env <key>=<value>
Read the service declaration from a JSON or YAML file:
$ kn service apply <service_name> -f <filename>
7.1.1.4. Describing serverless applications by using the Knative CLI
You can describe a Knative service by using the kn service describe
command.
Example commands
Describe a service:
$ kn service describe --verbose <service_name>
The
--verbose
flag is optional but can be included to provide a more detailed description. The difference between a regular and verbose output is shown in the following examples:Example output without
--verbose
flagName: hello Namespace: default Age: 2m URL: http://hello-default.apps.ocp.example.com Revisions: 100% @latest (hello-00001) [1] (2m) Image: docker.io/openshift/hello-openshift (pinned to aaea76) Conditions: OK TYPE AGE REASON ++ Ready 1m ++ ConfigurationsReady 1m ++ RoutesReady 1m
Example output with
--verbose
flagName: hello Namespace: default Annotations: serving.knative.dev/creator=system:admin serving.knative.dev/lastModifier=system:admin Age: 3m URL: http://hello-default.apps.ocp.example.com Cluster: http://hello.default.svc.cluster.local Revisions: 100% @latest (hello-00001) [1] (3m) Image: docker.io/openshift/hello-openshift (pinned to aaea76) Env: RESPONSE=Hello Serverless! Conditions: OK TYPE AGE REASON ++ Ready 3m ++ ConfigurationsReady 3m ++ RoutesReady 3m
Describe a service in YAML format:
$ kn service describe <service_name> -o yaml
Describe a service in JSON format:
$ kn service describe <service_name> -o json
Print the service URL only:
$ kn service describe <service_name> -o url
7.1.2. kn service commands in offline mode
7.1.2.1. About the Knative CLI offline mode
When you execute kn service
commands, the changes immediately propagate to the cluster. However, as an alternative, you can execute kn service
commands in offline mode. When you create a service in offline mode, no changes happen on the cluster, and instead the service descriptor file is created on your local machine.
The offline mode of the Knative CLI is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.
For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope.
After the descriptor file is created, you can manually modify it and track it in a version control system. You can also propagate changes to the cluster by using the kn service create -f
, kn service apply -f
, or oc apply -f
commands on the descriptor files.
The offline mode has several uses:
- You can manually modify the descriptor file before using it to make changes on the cluster.
- You can locally track the descriptor file of a service in a version control system. This enables you to reuse the descriptor file in places other than the target cluster, for example in continuous integration (CI) pipelines, development environments, or demos.
-
You can examine the created descriptor files to learn about Knative services. In particular, you can see how the resulting service is influenced by the different arguments passed to the
kn
command.
The offline mode has its advantages: it is fast, and does not require a connection to the cluster. However, offline mode lacks server-side validation. Consequently, you cannot, for example, verify that the service name is unique or that the specified image can be pulled.
7.1.2.2. Creating a service using offline mode
You can execute kn service
commands in offline mode, so that no changes happen on the cluster, and instead the service descriptor file is created on your local machine. After the descriptor file is created, you can modify the file before propagating changes to the cluster.
The offline mode of the Knative CLI is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.
For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope.
Prerequisites
- OpenShift Serverless Operator and Knative Serving are installed on your cluster.
-
You have installed the Knative (
kn
) CLI.
Procedure
In offline mode, create a local Knative service descriptor file:
$ kn service create event-display \ --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest \ --target ./ \ --namespace test
Example output
Service 'event-display' created in namespace 'test'.
The
--target ./
flag enables offline mode and specifies./
as the directory for storing the new directory tree.If you do not specify an existing directory, but use a filename, such as
--target my-service.yaml
, then no directory tree is created. Instead, only the service descriptor filemy-service.yaml
is created in the current directory.The filename can have the
.yaml
,.yml
, or.json
extension. Choosing.json
creates the service descriptor file in the JSON format.The
--namespace test
option places the new service in thetest
namespace.If you do not use
--namespace
, and you are logged in to an OpenShift Container Platform cluster, the descriptor file is created in the current namespace. Otherwise, the descriptor file is created in thedefault
namespace.
Examine the created directory structure:
$ tree ./
Example output
./ └── test └── ksvc └── event-display.yaml 2 directories, 1 file
-
The current
./
directory specified with--target
contains the newtest/
directory that is named after the specified namespace. -
The
test/
directory contains theksvc
directory, named after the resource type. -
The
ksvc
directory contains the descriptor fileevent-display.yaml
, named according to the specified service name.
-
The current
Examine the generated service descriptor file:
$ cat test/ksvc/event-display.yaml
Example output
apiVersion: serving.knative.dev/v1 kind: Service metadata: creationTimestamp: null name: event-display namespace: test spec: template: metadata: annotations: client.knative.dev/user-image: quay.io/openshift-knative/knative-eventing-sources-event-display:latest creationTimestamp: null spec: containers: - image: quay.io/openshift-knative/knative-eventing-sources-event-display:latest name: "" resources: {} status: {}
List information about the new service:
$ kn service describe event-display --target ./ --namespace test
Example output
Name: event-display Namespace: test Age: URL: Revisions: Conditions: OK TYPE AGE REASON
The
--target ./
option specifies the root directory for the directory structure containing namespace subdirectories.Alternatively, you can directly specify a YAML or JSON filename with the
--target
option. The accepted file extensions are.yaml
,.yml
, and.json
.The
--namespace
option specifies the namespace, which communicates tokn
the subdirectory that contains the necessary service descriptor file.If you do not use
--namespace
, and you are logged in to an OpenShift Container Platform cluster,kn
searches for the service in the subdirectory that is named after the current namespace. Otherwise,kn
searches in thedefault/
subdirectory.
Use the service descriptor file to create the service on the cluster:
$ kn service create -f test/ksvc/event-display.yaml
Example output
Creating service 'event-display' in namespace 'test': 0.058s The Route is still working to reflect the latest desired specification. 0.098s ... 0.168s Configuration "event-display" is waiting for a Revision to become ready. 23.377s ... 23.419s Ingress has not yet been reconciled. 23.534s Waiting for load balancer to be ready 23.723s Ready to serve. Service 'event-display' created to latest revision 'event-display-00001' is available at URL: http://event-display-test.apps.example.com
7.1.3. kn container commands
You can use the following commands to create and manage multiple containers in a Knative service spec.
7.1.3.1. Knative client multi-container support
You can use the kn container add
command to print YAML container spec to standard output. This command is useful for multi-container use cases because it can be used along with other standard kn
flags to create definitions.
The kn container add
command accepts all container-related flags that are supported for use with the kn service create
command. The kn container add
command can also be chained by using UNIX pipes (|
) to create multiple container definitions at once.
Example commands
Add a container from an image and print it to standard output:
$ kn container add <container_name> --image <image_uri>
Example command
$ kn container add sidecar --image docker.io/example/sidecar
Example output
containers: - image: docker.io/example/sidecar name: sidecar resources: {}
Chain two
kn container add
commands together, and then pass them to akn service create
command to create a Knative service with two containers:$ kn container add <first_container_name> --image <image_uri> | \ kn container add <second_container_name> --image <image_uri> | \ kn service create <service_name> --image <image_uri> --extra-containers -
--extra-containers -
specifies a special case wherekn
reads the pipe input instead of a YAML file.Example command
$ kn container add sidecar --image docker.io/example/sidecar:first | \ kn container add second --image docker.io/example/sidecar:second | \ kn service create my-service --image docker.io/example/my-app:latest --extra-containers -
The
--extra-containers
flag can also accept a path to a YAML file:$ kn service create <service_name> --image <image_uri> --extra-containers <filename>
Example command
$ kn service create my-service --image docker.io/example/my-app:latest --extra-containers my-extra-containers.yaml
7.1.4. kn domain commands
You can use the following commands to create and manage domain mappings.
7.1.4.1. Creating a custom domain mapping by using the Knative CLI
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on your cluster.
You have created a Knative service or route, and control a custom domain that you want to map to that CR.
NoteYour custom domain must point to the DNS of the OpenShift Container Platform cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Map a domain to a CR in the current namespace:
$ kn domain create <domain_mapping_name> --ref <target_name>
Example command
$ kn domain create example-domain-map --ref example-service
The
--ref
flag specifies an Addressable target CR for domain mapping.If a prefix is not provided when using the
--ref
flag, it is assumed that the target is a Knative service in the current namespace.Map a domain to a Knative service in a specified namespace:
$ kn domain create <domain_mapping_name> --ref <ksvc:service_name:service_namespace>
Example command
$ kn domain create example-domain-map --ref ksvc:example-service:example-namespace
Map a domain to a Knative route:
$ kn domain create <domain_mapping_name> --ref <kroute:route_name>
Example command
$ kn domain create example-domain-map --ref kroute:example-route
7.1.4.2. Managing custom domain mappings by using the Knative CLI
After you have created a DomainMapping
custom resource (CR), you can list existing CRs, view information about an existing CR, update CRs, or delete CRs by using the Knative (kn
) CLI.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on your cluster.
-
You have created at least one
DomainMapping
CR. -
You have installed the Knative (
kn
) CLI tool. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
List existing
DomainMapping
CRs:$ kn domain list -n <domain_mapping_namespace>
View details of an existing
DomainMapping
CR:$ kn domain describe <domain_mapping_name>
Update a
DomainMapping
CR to point to a new target:$ kn domain update --ref <target>
Delete a
DomainMapping
CR:$ kn domain delete <domain_mapping_name>
7.2. Configuring the Knative CLI
You can customize your Knative (kn
) CLI setup by creating a config.yaml
configuration file. You can provide this configuration by using the --config
flag, otherwise the configuration is picked up from a default location. The default configuration location conforms to the XDG Base Directory Specification, and is different for UNIX systems and Windows systems.
For UNIX systems:
-
If the
XDG_CONFIG_HOME
environment variable is set, the default configuration location that the Knative (kn
) CLI looks for is$XDG_CONFIG_HOME/kn
. -
If the
XDG_CONFIG_HOME
environment variable is not set, the Knative (kn
) CLI looks for the configuration in the home directory of the user at$HOME/.config/kn/config.yaml
.
For Windows systems, the default Knative (kn
) CLI configuration location is %APPDATA%\kn
.
Example configuration file
plugins: path-lookup: true 1 directory: ~/.config/kn/plugins 2 eventing: sink-mappings: 3 - prefix: svc 4 group: core 5 version: v1 6 resource: services 7
- 1
- Specifies whether the Knative (
kn
) CLI should look for plugins in thePATH
environment variable. This is a boolean configuration option. The default value isfalse
. - 2
- Specifies the directory where the Knative (
kn
) CLI looks for plugins. The default path depends on the operating system, as described previously. This can be any directory that is visible to the user. - 3
- The
sink-mappings
spec defines the Kubernetes addressable resource that is used when you use the--sink
flag with a Knative (kn
) CLI command. - 4
- The prefix you want to use to describe your sink.
svc
for a service,channel
, andbroker
are predefined prefixes for the Knative (kn
) CLI. - 5
- The API group of the Kubernetes resource.
- 6
- The version of the Kubernetes resource.
- 7
- The plural name of the Kubernetes resource type. For example,
services
orbrokers
.
7.3. Knative CLI plugins
The Knative (kn
) CLI supports the use of plugins, which enable you to extend the functionality of your kn
installation by adding custom commands and other shared commands that are not part of the core distribution. Knative (kn
) CLI plugins are used in the same way as the main kn
functionality.
Currently, Red Hat supports the kn-source-kafka
plugin and the kn-event
plugin.
The kn-event
plugin is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.
For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope.
7.3.1. Building events by using the kn-event plugin
You can use the builder-like interface of the kn event build
command to build an event. You can then send that event at a later time or use it in another context.
Prerequisites
-
You have installed the Knative (
kn
) CLI.
Procedure
Build an event:
$ kn event build --field <field-name>=<value> --type <type-name> --id <id> --output <format>
where:
-
The
--field
flag adds data to the event as a field-value pair. You can use it multiple times. -
The
--type
flag enables you to specify a string that designates the type of the event. -
The
--id
flag specifies the ID of the event. You can use the
json
oryaml
arguments with the--output
flag to change the output format of the event.All of these flags are optional.
Building a simple event
$ kn event build -o yaml
Resultant event in the YAML format
data: {} datacontenttype: application/json id: 81a402a2-9c29-4c27-b8ed-246a253c9e58 source: kn-event/v0.4.0 specversion: "1.0" time: "2021-10-15T10:42:57.713226203Z" type: dev.knative.cli.plugin.event.generic
Building a sample transaction event
$ kn event build \ --field operation.type=local-wire-transfer \ --field operation.amount=2345.40 \ --field operation.from=87656231 \ --field operation.to=2344121 \ --field automated=true \ --field signature='FGzCPLvYWdEgsdpb3qXkaVp7Da0=' \ --type org.example.bank.bar \ --id $(head -c 10 < /dev/urandom | base64 -w 0) \ --output json
Resultant event in the JSON format
{ "specversion": "1.0", "id": "RjtL8UH66X+UJg==", "source": "kn-event/v0.4.0", "type": "org.example.bank.bar", "datacontenttype": "application/json", "time": "2021-10-15T10:43:23.113187943Z", "data": { "automated": true, "operation": { "amount": "2345.40", "from": 87656231, "to": 2344121, "type": "local-wire-transfer" }, "signature": "FGzCPLvYWdEgsdpb3qXkaVp7Da0=" } }
-
The
7.3.2. Sending events by using the kn-event plugin
You can use the kn event send
command to send an event. The events can be sent either to publicly available addresses or to addressable resources inside a cluster, such as Kubernetes services, as well as Knative services, brokers, and channels. The command uses the same builder-like interface as the kn event build
command.
Prerequisites
-
You have installed the Knative (
kn
) CLI.
Procedure
Send an event:
$ kn event send --field <field-name>=<value> --type <type-name> --id <id> --to-url <url> --to <cluster-resource> --namespace <namespace>
where:
-
The
--field
flag adds data to the event as a field-value pair. You can use it multiple times. -
The
--type
flag enables you to specify a string that designates the type of the event. -
The
--id
flag specifies the ID of the event. -
If you are sending the event to a publicly accessible destination, specify the URL using the
--to-url
flag. If you are sending the event to an in-cluster Kubernetes resource, specify the destination using the
--to
flag.-
Specify the Kubernetes resource using the
<Kind>:<ApiVersion>:<name>
format.
-
Specify the Kubernetes resource using the
The
--namespace
flag specifies the namespace. If omitted, the namespace is taken from the current context.All of these flags are optional, except for the destination specification, for which you need to use either
--to-url
or--to
.The following example shows sending an event to a URL:
Example command
$ kn event send \ --field player.id=6354aa60-ddb1-452e-8c13-24893667de20 \ --field player.game=2345 \ --field points=456 \ --type org.example.gaming.foo \ --to-url http://ce-api.foo.example.com/
The following example shows sending an event to an in-cluster resource:
Example command
$ kn event send \ --type org.example.kn.ping \ --id $(uuidgen) \ --field event.type=test \ --field event.data=98765 \ --to Service:serving.knative.dev/v1:event-display
-
The
7.4. Knative Eventing CLI commands
7.4.1. kn source commands
You can use the following commands to list, create, and manage Knative event sources.
7.4.1.1. Listing available event source types by using the Knative CLI
You can list event source types that can be created and used on your cluster by using the kn source list-types
CLI command.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on the cluster.
-
You have installed the Knative (
kn
) CLI.
Procedure
List the available event source types in the terminal:
$ kn source list-types
Example output
TYPE NAME DESCRIPTION ApiServerSource apiserversources.sources.knative.dev Watch and send Kubernetes API events to a sink PingSource pingsources.sources.knative.dev Periodically send ping events to a sink SinkBinding sinkbindings.sources.knative.dev Binding for connecting a PodSpecable to a sink
Optional: You can also list the available event source types in YAML format:
$ kn source list-types -o yaml
7.4.1.2. Knative CLI sink flag
When you create an event source by using the Knative (kn
) CLI, you can specify a sink where events are sent to from that resource by using the --sink
flag. The sink can be any addressable or callable resource that can receive incoming events from other resources.
The following example creates a sink binding that uses a service, http://event-display.svc.cluster.local
, as the sink:
Example command using the sink flag
$ kn source binding create bind-heartbeat \
--namespace sinkbinding-example \
--subject "Job:batch/v1:app=heartbeat-cron" \
--sink http://event-display.svc.cluster.local \ 1
--ce-override "sink=bound"
- 1
svc
inhttp://event-display.svc.cluster.local
determines that the sink is a Knative service. Other default sink prefixes includechannel
, andbroker
.
7.4.1.3. Creating and managing container sources by using the Knative CLI
You can use the kn source container
commands to create and manage container sources by using the Knative (kn
) CLI. Using the Knative CLI to create event sources provides a more streamlined and intuitive user interface than modifying YAML files directly.
Create a container source
$ kn source container create <container_source_name> --image <image_uri> --sink <sink>
Delete a container source
$ kn source container delete <container_source_name>
Describe a container source
$ kn source container describe <container_source_name>
List existing container sources
$ kn source container list
List existing container sources in YAML format
$ kn source container list -o yaml
Update a container source
This command updates the image URI for an existing container source:
$ kn source container update <container_source_name> --image <image_uri>
7.4.1.4. Creating an API server source by using the Knative CLI
You can use the kn source apiserver create
command to create an API server source by using the kn
CLI. Using the kn
CLI to create an API server source provides a more streamlined and intuitive user interface than modifying YAML files directly.
Prerequisites
- The OpenShift Serverless Operator and Knative Eventing are installed on the cluster.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
You have installed the OpenShift CLI (
oc
). -
You have installed the Knative (
kn
) CLI.
If you want to re-use an existing service account, you can modify your existing ServiceAccount
resource to include the required permissions instead of creating a new resource.
Create a service account, role, and role binding for the event source as a YAML file:
apiVersion: v1 kind: ServiceAccount metadata: name: events-sa namespace: default 1 --- apiVersion: rbac.authorization.k8s.io/v1 kind: Role metadata: name: event-watcher namespace: default 2 rules: - apiGroups: - "" resources: - events verbs: - get - list - watch --- apiVersion: rbac.authorization.k8s.io/v1 kind: RoleBinding metadata: name: k8s-ra-event-watcher namespace: default 3 roleRef: apiGroup: rbac.authorization.k8s.io kind: Role name: event-watcher subjects: - kind: ServiceAccount name: events-sa namespace: default 4
Apply the YAML file:
$ oc apply -f <filename>
Create an API server source that has an event sink. In the following example, the sink is a broker:
$ kn source apiserver create <event_source_name> --sink broker:<broker_name> --resource "event:v1" --service-account <service_account_name> --mode Resource
To check that the API server source is set up correctly, create a Knative service that dumps incoming messages to its log:
$ kn service create <service_name> --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest
If you used a broker as an event sink, create a trigger to filter events from the
default
broker to the service:$ kn trigger create <trigger_name> --sink ksvc:<service_name>
Create events by launching a pod in the default namespace:
$ oc create deployment hello-node --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest
Check that the controller is mapped correctly by inspecting the output generated by the following command:
$ kn source apiserver describe <source_name>
Example output
Name: mysource Namespace: default Annotations: sources.knative.dev/creator=developer, sources.knative.dev/lastModifier=developer Age: 3m ServiceAccountName: events-sa Mode: Resource Sink: Name: default Namespace: default Kind: Broker (eventing.knative.dev/v1) Resources: Kind: event (v1) Controller: false Conditions: OK TYPE AGE REASON ++ Ready 3m ++ Deployed 3m ++ SinkProvided 3m ++ SufficientPermissions 3m ++ EventTypesProvided 3m
Verification
You can verify that the Kubernetes events were sent to Knative by looking at the message dumper function logs.
Get the pods:
$ oc get pods
View the message dumper function logs for the pods:
$ oc logs $(oc get pod -o name | grep event-display) -c user-container
Example output
☁️ cloudevents.Event Validation: valid Context Attributes, specversion: 1.0 type: dev.knative.apiserver.resource.update datacontenttype: application/json ... Data, { "apiVersion": "v1", "involvedObject": { "apiVersion": "v1", "fieldPath": "spec.containers{hello-node}", "kind": "Pod", "name": "hello-node", "namespace": "default", ..... }, "kind": "Event", "message": "Started container", "metadata": { "name": "hello-node.159d7608e3a3572c", "namespace": "default", .... }, "reason": "Started", ... }
Deleting the API server source
Delete the trigger:
$ kn trigger delete <trigger_name>
Delete the event source:
$ kn source apiserver delete <source_name>
Delete the service account, cluster role, and cluster binding:
$ oc delete -f authentication.yaml
7.4.1.5. Creating a ping source by using the Knative CLI
You can use the kn source ping create
command to create a ping source by using the Knative (kn
) CLI. Using the Knative CLI to create event sources provides a more streamlined and intuitive user interface than modifying YAML files directly.
Prerequisites
- The OpenShift Serverless Operator, Knative Serving and Knative Eventing are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
Optional: If you want to use the verification steps for this procedure, install the OpenShift CLI (
oc
).
Procedure
To verify that the ping source is working, create a simple Knative service that dumps incoming messages to the service logs:
$ kn service create event-display \ --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest
For each set of ping events that you want to request, create a ping source in the same namespace as the event consumer:
$ kn source ping create test-ping-source \ --schedule "*/2 * * * *" \ --data '{"message": "Hello world!"}' \ --sink ksvc:event-display
Check that the controller is mapped correctly by entering the following command and inspecting the output:
$ kn source ping describe test-ping-source
Example output
Name: test-ping-source Namespace: default Annotations: sources.knative.dev/creator=developer, sources.knative.dev/lastModifier=developer Age: 15s Schedule: */2 * * * * Data: {"message": "Hello world!"} Sink: Name: event-display Namespace: default Resource: Service (serving.knative.dev/v1) Conditions: OK TYPE AGE REASON ++ Ready 8s ++ Deployed 8s ++ SinkProvided 15s ++ ValidSchedule 15s ++ EventTypeProvided 15s ++ ResourcesCorrect 15s
Verification
You can verify that the Kubernetes events were sent to the Knative event sink by looking at the logs of the sink pod.
By default, Knative services terminate their pods if no traffic is received within a 60 second period. The example shown in this guide creates a ping source that sends a message every 2 minutes, so each message should be observed in a newly created pod.
Watch for new pods created:
$ watch oc get pods
Cancel watching the pods using Ctrl+C, then look at the logs of the created pod:
$ oc logs $(oc get pod -o name | grep event-display) -c user-container
Example output
☁️ cloudevents.Event Validation: valid Context Attributes, specversion: 1.0 type: dev.knative.sources.ping source: /apis/v1/namespaces/default/pingsources/test-ping-source id: 99e4f4f6-08ff-4bff-acf1-47f61ded68c9 time: 2020-04-07T16:16:00.000601161Z datacontenttype: application/json Data, { "message": "Hello world!" }
Deleting the ping source
Delete the ping source:
$ kn delete pingsources.sources.knative.dev <ping_source_name>
7.4.1.6. Creating a Kafka event source by using the Knative CLI
You can use the kn source kafka create
command to create a Kafka source by using the Knative (kn
) CLI. Using the Knative CLI to create event sources provides a more streamlined and intuitive user interface than modifying YAML files directly.
Prerequisites
-
The OpenShift Serverless Operator, Knative Eventing, Knative Serving, and the
KnativeKafka
custom resource (CR) are installed on your cluster. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
- You have access to a Red Hat AMQ Streams (Kafka) cluster that produces the Kafka messages you want to import.
-
You have installed the Knative (
kn
) CLI. -
Optional: You have installed the OpenShift CLI (
oc
) if you want to use the verification steps in this procedure.
Procedure
To verify that the Kafka event source is working, create a Knative service that dumps incoming events into the service logs:
$ kn service create event-display \ --image quay.io/openshift-knative/knative-eventing-sources-event-display
Create a
KafkaSource
CR:$ kn source kafka create <kafka_source_name> \ --servers <cluster_kafka_bootstrap>.kafka.svc:9092 \ --topics <topic_name> --consumergroup my-consumer-group \ --sink event-display
NoteReplace the placeholder values in this command with values for your source name, bootstrap servers, and topics.
The
--servers
,--topics
, and--consumergroup
options specify the connection parameters to the Kafka cluster. The--consumergroup
option is optional.Optional: View details about the
KafkaSource
CR you created:$ kn source kafka describe <kafka_source_name>
Example output
Name: example-kafka-source Namespace: kafka Age: 1h BootstrapServers: example-cluster-kafka-bootstrap.kafka.svc:9092 Topics: example-topic ConsumerGroup: example-consumer-group Sink: Name: event-display Namespace: default Resource: Service (serving.knative.dev/v1) Conditions: OK TYPE AGE REASON ++ Ready 1h ++ Deployed 1h ++ SinkProvided 1h
Verification steps
Trigger the Kafka instance to send a message to the topic:
$ oc -n kafka run kafka-producer \ -ti --image=quay.io/strimzi/kafka:latest-kafka-2.7.0 --rm=true \ --restart=Never -- bin/kafka-console-producer.sh \ --broker-list <cluster_kafka_bootstrap>:9092 --topic my-topic
Enter the message in the prompt. This command assumes that:
-
The Kafka cluster is installed in the
kafka
namespace. -
The
KafkaSource
object has been configured to use themy-topic
topic.
-
The Kafka cluster is installed in the
Verify that the message arrived by viewing the logs:
$ oc logs $(oc get pod -o name | grep event-display) -c user-container
Example output
☁️ cloudevents.Event Validation: valid Context Attributes, specversion: 1.0 type: dev.knative.kafka.event source: /apis/v1/namespaces/default/kafkasources/example-kafka-source#example-topic subject: partition:46#0 id: partition:46/offset:0 time: 2021-03-10T11:21:49.4Z Extensions, traceparent: 00-161ff3815727d8755848ec01c866d1cd-7ff3916c44334678-00 Data, Hello!
7.5. Knative Functions CLI commands
7.5.1. kn functions commands
7.5.1.1. Creating functions
Before you can build and deploy a function, you must create it by using the Knative (kn
) CLI. You can specify the path, runtime, template, and image registry as flags on the command line, or use the -c
flag to start the interactive experience in the terminal.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI.
Procedure
Create a function project:
$ kn func create -r <repository> -l <runtime> -t <template> <path>
-
Accepted runtime values include
quarkus
,node
,typescript
,go
,python
,springboot
, andrust
. Accepted template values include
http
andcloudevents
.Example command
$ kn func create -l typescript -t cloudevents examplefunc
Example output
Created typescript function in /home/user/demo/examplefunc
Alternatively, you can specify a repository that contains a custom template.
Example command
$ kn func create -r https://github.com/boson-project/templates/ -l node -t hello-world examplefunc
Example output
Created node function in /home/user/demo/examplefunc
-
Accepted runtime values include
7.5.1.2. Running a function locally
You can use the kn func run
command to run a function locally in the current directory or in the directory specified by the --path
flag. If the function that you are running has never previously been built, or if the project files have been modified since the last time it was built, the kn func run
command builds the function before running it by default.
Example command to run a function in the current directory
$ kn func run
Example command to run a function in a directory specified as a path
$ kn func run --path=<directory_path>
You can also force a rebuild of an existing image before running the function, even if there have been no changes to the project files, by using the --build
flag:
Example run command using the build flag
$ kn func run --build
If you set the build
flag as false, this disables building of the image, and runs the function using the previously built image:
Example run command using the build flag
$ kn func run --build=false
You can use the help command to learn more about kn func run
command options:
Build help command
$ kn func help run
7.5.1.3. Building functions
Before you can run a function, you must build the function project. If you are using the kn func run
command, the function is built automatically. However, you can use the kn func build
command to build a function without running it, which can be useful for advanced users or debugging scenarios.
The kn func build
command creates an OCI container image that can be run locally on your computer or on an OpenShift Container Platform cluster. This command uses the function project name and the image registry name to construct a fully qualified image name for your function.
7.5.1.3.1. Image container types
By default, kn func build
creates a container image by using Red Hat Source-to-Image (S2I) technology.
Example build command using Red Hat Source-to-Image (S2I)
$ kn func build
7.5.1.3.2. Image registry types
The OpenShift Container Registry is used by default as the image registry for storing function images.
Example build command using OpenShift Container Registry
$ kn func build
Example output
Building function image Function image has been built, image: registry.redhat.io/example/example-function:latest
You can override using OpenShift Container Registry as the default image registry by using the --registry
flag:
Example build command overriding OpenShift Container Registry to use quay.io
$ kn func build --registry quay.io/username
Example output
Building function image Function image has been built, image: quay.io/username/example-function:latest
7.5.1.3.3. Push flag
You can add the --push
flag to a kn func build
command to automatically push the function image after it is successfully built:
Example build command using OpenShift Container Registry
$ kn func build --push
7.5.1.3.4. Help command
You can use the help command to learn more about kn func build
command options:
Build help command
$ kn func help build
7.5.1.4. Deploying functions
You can deploy a function to your cluster as a Knative service by using the kn func deploy
command. If the targeted function is already deployed, it is updated with a new container image that is pushed to a container image registry, and the Knative service is updated.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
- You must have already created and initialized the function that you want to deploy.
Procedure
Deploy a function:
$ kn func deploy [-n <namespace> -p <path> -i <image>]
Example output
Function deployed at: http://func.example.com
-
If no
namespace
is specified, the function is deployed in the current namespace. -
The function is deployed from the current directory, unless a
path
is specified. - The Knative service name is derived from the project name, and cannot be changed using this command.
-
If no
7.5.1.5. Listing existing functions
You can list existing functions by using kn func list
. If you want to list functions that have been deployed as Knative services, you can also use kn service list
.
Procedure
List existing functions:
$ kn func list [-n <namespace> -p <path>]
Example output
NAME NAMESPACE RUNTIME URL READY example-function default node http://example-function.default.apps.ci-ln-g9f36hb-d5d6b.origin-ci-int-aws.dev.rhcloud.com True
List functions deployed as Knative services:
$ kn service list -n <namespace>
Example output
NAME URL LATEST AGE CONDITIONS READY REASON example-function http://example-function.default.apps.ci-ln-g9f36hb-d5d6b.origin-ci-int-aws.dev.rhcloud.com example-function-gzl4c 16m 3 OK / 3 True
7.5.1.6. Describing a function
The kn func info
command prints information about a deployed function, such as the function name, image, namespace, Knative service information, route information, and event subscriptions.
Procedure
Describe a function:
$ kn func info [-f <format> -n <namespace> -p <path>]
Example command
$ kn func info -p function/example-function
Example output
Function name: example-function Function is built in image: docker.io/user/example-function:latest Function is deployed as Knative Service: example-function Function is deployed in namespace: default Routes: http://example-function.default.apps.ci-ln-g9f36hb-d5d6b.origin-ci-int-aws.dev.rhcloud.com
7.5.1.7. Invoking a deployed function with a test event
You can use the kn func invoke
CLI command to send a test request to invoke a function either locally or on your OpenShift Container Platform cluster. You can use this command to test that a function is working and able to receive events correctly. Invoking a function locally is useful for a quick test during function development. Invoking a function on the cluster is useful for testing that is closer to the production environment.
Prerequisites
- The OpenShift Serverless Operator and Knative Serving are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
- You must have already deployed the function that you want to invoke.
Procedure
Invoke a function:
$ kn func invoke
-
The
kn func invoke
command only works when there is either a local container image currently running, or when there is a function deployed in the cluster. -
The
kn func invoke
command executes on the local directory by default, and assumes that this directory is a function project.
-
The
7.5.1.7.1. kn func invoke optional parameters
You can specify optional parameters for the request by using the following kn func invoke
CLI command flags.
Flags | Description |
---|---|
|
Specifies the target instance of the invoked function, for example, |
|
Specifies the format of the message, for example, |
| Specifies a unique string identifier for the request. |
| Specifies the namespace on the cluster. |
|
Specifies sender name for the request. This corresponds to the CloudEvent |
|
Specifies the type of request, for example, |
|
Specifies content for the request. For CloudEvent requests, this is the CloudEvent |
| Specifies path to a local file containing data to be sent. |
| Specifies the MIME content type for the request. |
| Specifies path to the project directory. |
| Enables prompting to interactively confirm all options. |
| Enables printing verbose output. |
|
Prints information on usage of |
7.5.1.7.1.1. Main parameters
The following parameters define the main properties of the kn func invoke
command:
- Event target (
-t
,--target
) -
The target instance of the invoked function. Accepts the
local
value for a locally deployed function, theremote
value for a remotely deployed function, or a URL for a function deployed to an arbitrary endpoint. If a target is not specified, it defaults tolocal
. - Event message format (
-f
,--format
) -
The message format for the event, such as
http
orcloudevent
. This defaults to the format of the template that was used when creating the function. - Event type (
--type
) -
The type of event that is sent. You can find information about the
type
parameter that is set in the documentation for each event producer. For example, the API server source might set thetype
parameter of produced events asdev.knative.apiserver.resource.update
. - Event source (
--source
) -
The unique event source that produced the event. This might be a URI for the event source, for example
https://10.96.0.1/
, or the name of the event source. - Event ID (
--id
) - A random, unique ID that is created by the event producer.
- Event data (
--data
) Allows you to specify a
data
value for the event sent by thekn func invoke
command. For example, you can specify a--data
value such as"Hello World"
so that the event contains this data string. By default, no data is included in the events created bykn func invoke
.NoteFunctions that have been deployed to a cluster can respond to events from an existing event source that provides values for properties such as
source
andtype
. These events often have adata
value in JSON format, which captures the domain specific context of the event. By using the CLI flags noted in this document, developers can simulate those events for local testing.You can also send event data using the
--file
flag to provide a local file containing data for the event. In this case, specify the content type using--content-type
.- Data content type (
--content-type
) -
If you are using the
--data
flag to add data for events, you can use the--content-type
flag to specify what type of data is carried by the event. In the previous example, the data is plain text, so you might specifykn func invoke --data "Hello world!" --content-type "text/plain"
.
7.5.1.7.1.2. Example commands
This is the general invocation of the kn func invoke
command:
$ kn func invoke --type <event_type> --source <event_source> --data <event_data> --content-type <content_type> --id <event_ID> --format <format> --namespace <namespace>
For example, to send a "Hello world!" event, you can run:
$ kn func invoke --type ping --source example-ping --data "Hello world!" --content-type "text/plain" --id example-ID --format http --namespace my-ns
7.5.1.7.1.2.1. Specifying the file with data
To specify the file on disk that contains the event data, use the --file
and --content-type
flags:
$ kn func invoke --file <path> --content-type <content-type>
For example, to send JSON data stored in the test.json
file, use this command:
$ kn func invoke --file ./test.json --content-type application/json
7.5.1.7.1.2.2. Specifying the function project
You can specify a path to the function project by using the --path
flag:
$ kn func invoke --path <path_to_function>
For example, to use the function project located in the ./example/example-function
directory, use this command:
$ kn func invoke --path ./example/example-function
7.5.1.7.1.2.3. Specifying where the target function is deployed
By default, kn func invoke
targets the local deployment of the function:
$ kn func invoke
To use a different deployment, use the --target
flag:
$ kn func invoke --target <target>
For example, to use the function deployed on the cluster, use the --target remote
flag:
$ kn func invoke --target remote
To use the function deployed at an arbitrary URL, use the --target <URL>
flag:
$ kn func invoke --target "https://my-event-broker.example.com"
You can explicitly target the local deployment. In this case, if the function is not running locally, the command fails:
$ kn func invoke --target local
7.5.1.8. Deleting a function
You can delete a function by using the kn func delete
command. This is useful when a function is no longer required, and can help to save resources on your cluster.
Procedure
Delete a function:
$ kn func delete [<function_name> -n <namespace> -p <path>]
-
If the name or path of the function to delete is not specified, the current directory is searched for a
func.yaml
file that is used to determine the function to delete. -
If the namespace is not specified, it defaults to the
namespace
value in thefunc.yaml
file.
-
If the name or path of the function to delete is not specified, the current directory is searched for a
Chapter 8. Observability
8.1. Administrator metrics
8.1.1. Serverless administrator metrics
Metrics enable cluster administrators to monitor how OpenShift Serverless cluster components and workloads are performing.
You can view different metrics for OpenShift Serverless by navigating to Dashboards in the OpenShift Container Platform web console Administrator perspective.
8.1.1.1. Prerequisites
- See the OpenShift Container Platform documentation on Managing metrics for information about enabling metrics for your cluster.
- You have access to an OpenShift Container Platform account with cluster administrator access.
- You have access to the Administrator perspective in the OpenShift Container Platform web console.
If Service Mesh is enabled with mTLS, metrics for Knative Serving are disabled by default because Service Mesh prevents Prometheus from scraping metrics.
For information about resolving this issue, see Enabling Knative Serving metrics when using Service Mesh with mTLS.
Scraping the metrics does not affect autoscaling of a Knative service, because scraping requests do not go through the activator. Consequently, no scraping takes place if no pods are running.
8.1.2. Serverless controller metrics
The following metrics are emitted by any component that implements a controller logic. These metrics show details about reconciliation operations and the work queue behavior upon which reconciliation requests are added to the work queue.
Metric name | Description | Type | Tags | Unit |
---|---|---|---|---|
| The depth of the work queue. | Gauge |
| Integer (no units) |
| The number of reconcile operations. | Counter |
| Integer (no units) |
| The latency of reconcile operations. | Histogram |
| Milliseconds |
| The total number of add actions handled by the work queue. | Counter |
| Integer (no units) |
| The length of time an item stays in the work queue before being requested. | Histogram |
| Seconds |
| The total number of retries that have been handled by the work queue. | Counter |
| Integer (no units) |
| The length of time it takes to process and item from the work queue. | Histogram |
| Seconds |
| The length of time that outstanding work queue items have been in progress. | Histogram |
| Seconds |
| The length of time that the longest outstanding work queue items has been in progress. | Histogram |
| Seconds |
8.1.3. Webhook metrics
Webhook metrics report useful information about operations. For example, if a large number of operations fail, this might indicate an issue with a user-created resource.
Metric name | Description | Type | Tags | Unit |
---|---|---|---|---|
| The number of requests that are routed to the webhook. | Counter |
| Integer (no units) |
| The response time for a webhook request. | Histogram |
| Milliseconds |
8.1.4. Knative Eventing metrics
Cluster administrators can view the following metrics for Knative Eventing components.
By aggregating the metrics from HTTP code, events can be separated into two categories; successful events (2xx) and failed events (5xx).
8.1.4.1. Broker ingress metrics
You can use the following metrics to debug the broker ingress, see how it is performing, and see which events are being dispatched by the ingress component.
Metric name | Description | Type | Tags | Unit |
---|---|---|---|---|
| Number of events received by a broker. | Counter |
| Integer (no units) |
| The time taken to dispatch an event to a channel. | Histogram |
| Milliseconds |
8.1.4.2. Broker filter metrics
You can use the following metrics to debug broker filters, see how they are performing, and see which events are being dispatched by the filters. You can also measure the latency of the filtering action on an event.
Metric name | Description | Type | Tags | Unit |
---|---|---|---|---|
| Number of events received by a broker. | Counter |
| Integer (no units) |
| The time taken to dispatch an event to a channel. | Histogram |
| Milliseconds |
| The time it takes to process an event before it is dispatched to a trigger subscriber. | Histogram |
| Milliseconds |
8.1.4.3. InMemoryChannel dispatcher metrics
You can use the following metrics to debug InMemoryChannel
channels, see how they are performing, and see which events are being dispatched by the channels.
Metric name | Description | Type | Tags | Unit |
---|---|---|---|---|
|
Number of events dispatched by | Counter |
| Integer (no units) |
|
The time taken to dispatch an event from an | Histogram |
| Milliseconds |
8.1.4.4. Event source metrics
You can use the following metrics to verify that events have been delivered from the event source to the connected event sink.
Metric name | Description | Type | Tags | Unit |
---|---|---|---|---|
| Number of events sent by the event source. | Counter |
| Integer (no units) |
| Number of retried events sent by the event source after initially failing to be delivered. | Counter |
| Integer (no units) |
8.1.5. Knative Serving metrics
Cluster administrators can view the following metrics for Knative Serving components.
8.1.5.1. Activator metrics
You can use the following metrics to understand how applications respond when traffic passes through the activator.
Metric name | Description | Type | Tags | Unit |
---|---|---|---|---|
| The number of concurrent requests that are routed to the activator, or average concurrency over a reporting period. | Gauge |
| Integer (no units) |
| The number of requests that are routed to activator. These are requests that have been fulfilled from the activator handler. | Counter |
| Integer (no units) |
| The response time in milliseconds for a fulfilled, routed request. | Histogram |
| Milliseconds |
8.1.5.2. Autoscaler metrics
The autoscaler component exposes a number of metrics related to autoscaler behavior for each revision. For example, at any given time, you can monitor the targeted number of pods the autoscaler tries to allocate for a service, the average number of requests per second during the stable window, or whether the autoscaler is in panic mode if you are using the Knative pod autoscaler (KPA).
Metric name | Description | Type | Tags | Unit |
---|---|---|---|---|
| The number of pods the autoscaler tries to allocate for a service. | Gauge |
| Integer (no units) |
| The excess burst capacity served over the stable window. | Gauge |
| Integer (no units) |
| The average number of requests for each observed pod over the stable window. | Gauge |
| Integer (no units) |
| The average number of requests for each observed pod over the panic window. | Gauge |
| Integer (no units) |
| The number of concurrent requests that the autoscaler tries to send to each pod. | Gauge |
| Integer (no units) |
| The average number of requests-per-second for each observed pod over the stable window. | Gauge |
| Integer (no units) |
| The average number of requests-per-second for each observed pod over the panic window. | Gauge |
| Integer (no units) |
| The number of requests-per-second that the autoscaler targets for each pod. | Gauge |
| Integer (no units) |
|
This value is | Gauge |
| Integer (no units) |
| The number of pods that the autoscaler has requested from the Kubernetes cluster. | Gauge |
| Integer (no units) |
| The number of pods that are allocated and currently have a ready state. | Gauge |
| Integer (no units) |
| The number of pods that have a not ready state. | Gauge |
| Integer (no units) |
| The number of pods that are currently pending. | Gauge |
| Integer (no units) |
| The number of pods that are currently terminating. | Gauge |
| Integer (no units) |
8.1.5.3. Go runtime metrics
Each Knative Serving control plane process emits a number of Go runtime memory statistics (MemStats).
The name
tag for each metric is an empty tag.
Metric name | Description | Type | Tags | Unit |
---|---|---|---|---|
|
The number of bytes of allocated heap objects. This metric is the same as | Gauge |
| Integer (no units) |
| The cumulative bytes allocated for heap objects. | Gauge |
| Integer (no units) |
| The total bytes of memory obtained from the operating system. | Gauge |
| Integer (no units) |
| The number of pointer lookups performed by the runtime. | Gauge |
| Integer (no units) |
| The cumulative count of heap objects allocated. | Gauge |
| Integer (no units) |
| The cumulative count of heap objects that have been freed. | Gauge |
| Integer (no units) |
| The number of bytes of allocated heap objects. | Gauge |
| Integer (no units) |
| The number of bytes of heap memory obtained from the operating system. | Gauge |
| Integer (no units) |
| The number of bytes in idle, unused spans. | Gauge |
| Integer (no units) |
| The number of bytes in spans that are currently in use. | Gauge |
| Integer (no units) |
| The number of bytes of physical memory returned to the operating system. | Gauge |
| Integer (no units) |
| The number of allocated heap objects. | Gauge |
| Integer (no units) |
| The number of bytes in stack spans that are currently in use. | Gauge |
| Integer (no units) |
| The number of bytes of stack memory obtained from the operating system. | Gauge |
| Integer (no units) |
|
The number of bytes of allocated | Gauge |
| Integer (no units) |
|
The number of bytes of memory obtained from the operating system for | Gauge |
| Integer (no units) |
|
The number of bytes of allocated | Gauge |
| Integer (no units) |
|
The number of bytes of memory obtained from the operating system for | Gauge |
| Integer (no units) |
| The number of bytes of memory in profiling bucket hash tables. | Gauge |
| Integer (no units) |
| The number of bytes of memory in garbage collection metadata. | Gauge |
| Integer (no units) |
| The number of bytes of memory in miscellaneous, off-heap runtime allocations. | Gauge |
| Integer (no units) |
| The target heap size of the next garbage collection cycle. | Gauge |
| Integer (no units) |
| The time that the last garbage collection was completed in Epoch or Unix time. | Gauge |
| Nanoseconds |
| The cumulative time in garbage collection stop-the-world pauses since the program started. | Gauge |
| Nanoseconds |
| The number of completed garbage collection cycles. | Gauge |
| Integer (no units) |
| The number of garbage collection cycles that were forced due to an application calling the garbage collection function. | Gauge |
| Integer (no units) |
| The fraction of the available CPU time of the program that has been used by the garbage collector since the program started. | Gauge |
| Integer (no units) |
8.2. Developer metrics
8.2.1. Serverless developer metrics overview
Metrics enable developers to monitor how Knative services are performing. You can use the OpenShift Container Platform monitoring stack to record and view health checks and metrics for your Knative services.
You can view different metrics for OpenShift Serverless by navigating to Dashboards in the OpenShift Container Platform web console Developer perspective.
If Service Mesh is enabled with mTLS, metrics for Knative Serving are disabled by default because Service Mesh prevents Prometheus from scraping metrics.
For information about resolving this issue, see Enabling Knative Serving metrics when using Service Mesh with mTLS.
Scraping the metrics does not affect autoscaling of a Knative service, because scraping requests do not go through the activator. Consequently, no scraping takes place if no pods are running.
8.2.1.1. Additional resources
8.2.2. Knative service metrics exposed by default
Metric name, unit, and type | Description | Metric tags |
---|---|---|
Metric unit: dimensionless Metric type: gauge | Number of requests per second that hit the queue proxy.
Formula:
| destination_configuration="event-display", destination_namespace="pingsource1", destination_pod="event-display-00001-deployment-6b455479cb-75p6w", destination_revision="event-display-00001" |
Metric unit: dimensionless Metric type: gauge | Number of proxied requests per second.
Formula:
| |
Metric unit: dimensionless Metric type: gauge | Number of requests currently being handled by this pod.
Average concurrency is calculated at the networking
| destination_configuration="event-display", destination_namespace="pingsource1", destination_pod="event-display-00001-deployment-6b455479cb-75p6w", destination_revision="event-display-00001" |
Metric unit: dimensionless Metric type: gauge | Number of proxied requests currently being handled by this pod:
| destination_configuration="event-display", destination_namespace="pingsource1", destination_pod="event-display-00001-deployment-6b455479cb-75p6w", destination_revision="event-display-00001" |
Metric unit: seconds Metric type: gauge | The number of seconds that the process has been up. | destination_configuration="event-display", destination_namespace="pingsource1", destination_pod="event-display-00001-deployment-6b455479cb-75p6w", destination_revision="event-display-00001" |
Metric name, unit, and type | Description | Metric tags |
---|---|---|
Metric unit: dimensionless Metric type: counter |
The number of requests that are routed to | configuration_name="event-display", container_name="queue-proxy", namespace_name="apiserversource1", pod_name="event-display-00001-deployment-658fd4f9cf-qcnr5", response_code="200", response_code_class="2xx", revision_name="event-display-00001", service_name="event-display" |
Metric unit: milliseconds Metric type: histogram | The response time in milliseconds. | configuration_name="event-display", container_name="queue-proxy", namespace_name="apiserversource1", pod_name="event-display-00001-deployment-658fd4f9cf-qcnr5", response_code="200", response_code_class="2xx", revision_name="event-display-00001", service_name="event-display" |
Metric unit: dimensionless Metric type: counter |
The number of requests that are routed to | configuration_name="event-display", container_name="queue-proxy", namespace_name="apiserversource1", pod_name="event-display-00001-deployment-658fd4f9cf-qcnr5", response_code="200", response_code_class="2xx", revision_name="event-display-00001", service_name="event-display" |
Metric unit: milliseconds Metric type: histogram | The response time in milliseconds. | configuration_name="event-display", container_name="queue-proxy", namespace_name="apiserversource1", pod_name="event-display-00001-deployment-658fd4f9cf-qcnr5", response_code="200", response_code_class="2xx", revision_name="event-display-00001", service_name="event-display" |
Metric unit: dimensionless Metric type: gauge |
The current number of items in the serving and waiting queue, or not reported if unlimited concurrency. | configuration_name="event-display", container_name="queue-proxy", namespace_name="apiserversource1", pod_name="event-display-00001-deployment-658fd4f9cf-qcnr5", response_code="200", response_code_class="2xx", revision_name="event-display-00001", service_name="event-display" |
8.2.3. Knative service with custom application metrics
You can extend the set of metrics exported by a Knative service. The exact implementation depends on your application and the language used.
The following listing implements a sample Go application that exports the count of processed events custom metric.
package main import ( "fmt" "log" "net/http" "os" "github.com/prometheus/client_golang/prometheus" 1 "github.com/prometheus/client_golang/prometheus/promauto" "github.com/prometheus/client_golang/prometheus/promhttp" ) var ( opsProcessed = promauto.NewCounter(prometheus.CounterOpts{ 2 Name: "myapp_processed_ops_total", Help: "The total number of processed events", }) ) func handler(w http.ResponseWriter, r *http.Request) { log.Print("helloworld: received a request") target := os.Getenv("TARGET") if target == "" { target = "World" } fmt.Fprintf(w, "Hello %s!\n", target) opsProcessed.Inc() 3 } func main() { log.Print("helloworld: starting server...") port := os.Getenv("PORT") if port == "" { port = "8080" } http.HandleFunc("/", handler) // Separate server for metrics requests go func() { 4 mux := http.NewServeMux() server := &http.Server{ Addr: fmt.Sprintf(":%s", "9095"), Handler: mux, } mux.Handle("/metrics", promhttp.Handler()) log.Printf("prometheus: listening on port %s", 9095) log.Fatal(server.ListenAndServe()) }() // Use same port as normal requests for metrics //http.Handle("/metrics", promhttp.Handler()) 5 log.Printf("helloworld: listening on port %s", port) log.Fatal(http.ListenAndServe(fmt.Sprintf(":%s", port), nil)) }
8.2.4. Configuration for scraping custom metrics
Custom metrics scraping is performed by an instance of Prometheus purposed for user workload monitoring. After you enable user workload monitoring and create the application, you need a configuration that defines how the monitoring stack will scrape the metrics.
The following sample configuration defines the ksvc
for your application and configures the service monitor. The exact configuration depends on your application and how it exports the metrics.
apiVersion: serving.knative.dev/v1 1 kind: Service metadata: name: helloworld-go spec: template: metadata: labels: app: helloworld-go annotations: spec: containers: - image: docker.io/skonto/helloworld-go:metrics resources: requests: cpu: "200m" env: - name: TARGET value: "Go Sample v1" --- apiVersion: monitoring.coreos.com/v1 2 kind: ServiceMonitor metadata: labels: name: helloworld-go-sm spec: endpoints: - port: queue-proxy-metrics scheme: http - port: app-metrics scheme: http namespaceSelector: {} selector: matchLabels: name: helloworld-go-sm --- apiVersion: v1 3 kind: Service metadata: labels: name: helloworld-go-sm name: helloworld-go-sm spec: ports: - name: queue-proxy-metrics port: 9091 protocol: TCP targetPort: 9091 - name: app-metrics port: 9095 protocol: TCP targetPort: 9095 selector: serving.knative.dev/service: helloworld-go type: ClusterIP
8.2.5. Examining metrics of a service
After you have configured the application to export the metrics and the monitoring stack to scrape them, you can examine the metrics in the web console.
Prerequisites
- You have logged in to the OpenShift Container Platform web console.
- You have installed the OpenShift Serverless Operator and Knative Serving.
Procedure
Optional: Run requests against your application that you will be able to see in the metrics:
$ hello_route=$(oc get ksvc helloworld-go -n ns1 -o jsonpath='{.status.url}') && \ curl $hello_route
Example output
Hello Go Sample v1!
- In the web console, navigate to the Observe → Metrics interface.
In the input field, enter the query for the metric you want to observe, for example:
revision_app_request_count{namespace="ns1", job="helloworld-go-sm"}
Another example:
myapp_processed_ops_total{namespace="ns1", job="helloworld-go-sm"}
Observe the visualized metrics:
8.2.5.1. Queue proxy metrics
Each Knative service has a proxy container that proxies the connections to the application container. A number of metrics are reported for the queue proxy performance.
You can use the following metrics to measure if requests are queued at the proxy side and the actual delay in serving requests at the application side.
Metric name | Description | Type | Tags | Unit |
---|---|---|---|---|
|
The number of requests that are routed to | Counter |
| Integer (no units) |
| The response time of revision requests. | Histogram |
| Milliseconds |
|
The number of requests that are routed to the | Counter |
| Integer (no units) |
| The response time of revision app requests. | Histogram |
| Milliseconds |
|
The current number of items in the | Gauge |
| Integer (no units) |
8.2.6. Dashboard for service metrics
You can examine the metrics using a dedicated dashboard that aggregates queue proxy metrics by namespace.
8.2.6.1. Examining metrics of a service in the dashboard
Prerequisites
- You have logged in to the OpenShift Container Platform web console.
- You have installed the OpenShift Serverless Operator and Knative Serving.
Procedure
- In the web console, navigate to the Observe → Metrics interface.
-
Select the
Knative User Services (Queue Proxy metrics)
dashboard. - Select the Namespace, Configuration, and Revision that correspond to your application.
Observe the visualized metrics:
8.3. Cluster logging
8.3.1. Using OpenShift Logging with OpenShift Serverless
8.3.1.1. About deploying the logging subsystem for Red Hat OpenShift
OpenShift Container Platform cluster administrators can deploy the logging subsystem using the OpenShift Container Platform web console or CLI to install the OpenShift Elasticsearch Operator and Red Hat OpenShift Logging Operator. When the Operators are installed, you create a ClusterLogging
custom resource (CR) to schedule logging subsystem pods and other resources necessary to support the logging subsystem. The Operators are responsible for deploying, upgrading, and maintaining the logging subsystem.
The ClusterLogging
CR defines a complete logging subsystem environment that includes all the components of the logging stack to collect, store and visualize logs. The Red Hat OpenShift Logging Operator watches the logging subsystem CR and adjusts the logging deployment accordingly.
Administrators and application developers can view the logs of the projects for which they have view access.
8.3.1.2. About deploying and configuring the logging subsystem for Red Hat OpenShift
The logging subsystem is designed to be used with the default configuration, which is tuned for small to medium sized OpenShift Container Platform clusters.
The installation instructions that follow include a sample ClusterLogging
custom resource (CR), which you can use to create a logging subsystem instance and configure your logging subsystem environment.
If you want to use the default logging subsystem install, you can use the sample CR directly.
If you want to customize your deployment, make changes to the sample CR as needed. The following describes the configurations you can make when installing your OpenShift Logging instance or modify after installation. See the Configuring sections for more information on working with each component, including modifications you can make outside of the ClusterLogging
custom resource.
8.3.1.2.1. Configuring and Tuning the logging subsystem
You can configure your logging subsystem by modifying the ClusterLogging
custom resource deployed in the openshift-logging
project.
You can modify any of the following components upon install or after install:
- Memory and CPU
-
You can adjust both the CPU and memory limits for each component by modifying the
resources
block with valid memory and CPU values:
spec: logStore: elasticsearch: resources: limits: cpu: memory: 16Gi requests: cpu: 500m memory: 16Gi type: "elasticsearch" collection: logs: fluentd: resources: limits: cpu: memory: requests: cpu: memory: type: "fluentd" visualization: kibana: resources: limits: cpu: memory: requests: cpu: memory: type: kibana
- Elasticsearch storage
-
You can configure a persistent storage class and size for the Elasticsearch cluster using the
storageClass
name
andsize
parameters. The Red Hat OpenShift Logging Operator creates a persistent volume claim (PVC) for each data node in the Elasticsearch cluster based on these parameters.
spec: logStore: type: "elasticsearch" elasticsearch: nodeCount: 3 storage: storageClassName: "gp2" size: "200G"
This example specifies each data node in the cluster will be bound to a PVC that requests "200G" of "gp2" storage. Each primary shard will be backed by a single replica.
Omitting the storage
block results in a deployment that includes ephemeral storage only.
spec: logStore: type: "elasticsearch" elasticsearch: nodeCount: 3 storage: {}
- Elasticsearch replication policy
You can set the policy that defines how Elasticsearch shards are replicated across data nodes in the cluster:
-
FullRedundancy
. The shards for each index are fully replicated to every data node. -
MultipleRedundancy
. The shards for each index are spread over half of the data nodes. -
SingleRedundancy
. A single copy of each shard. Logs are always available and recoverable as long as at least two data nodes exist. -
ZeroRedundancy
. No copies of any shards. Logs may be unavailable (or lost) in the event a node is down or fails.
-
8.3.1.2.2. Sample modified ClusterLogging custom resource
The following is an example of a ClusterLogging
custom resource modified using the options previously described.
Sample modified ClusterLogging
custom resource
apiVersion: "logging.openshift.io/v1" kind: "ClusterLogging" metadata: name: "instance" namespace: "openshift-logging" spec: managementState: "Managed" logStore: type: "elasticsearch" retentionPolicy: application: maxAge: 1d infra: maxAge: 7d audit: maxAge: 7d elasticsearch: nodeCount: 3 resources: limits: memory: 32Gi requests: cpu: 3 memory: 32Gi storage: storageClassName: "gp2" size: "200G" redundancyPolicy: "SingleRedundancy" visualization: type: "kibana" kibana: resources: limits: memory: 1Gi requests: cpu: 500m memory: 1Gi replicas: 1 collection: logs: type: "fluentd" fluentd: resources: limits: memory: 1Gi requests: cpu: 200m memory: 1Gi
8.3.2. Finding logs for Knative Serving components
You can find the logs for Knative Serving components using the following procedure.
8.3.2.1. Using OpenShift Logging to find logs for Knative Serving components
Prerequisites
-
Install the OpenShift CLI (
oc
).
Procedure
Get the Kibana route:
$ oc -n openshift-logging get route kibana
- Use the route’s URL to navigate to the Kibana dashboard and log in.
- Check that the index is set to .all. If the index is not set to .all, only the OpenShift Container Platform system logs will be listed.
-
Filter the logs by using the
knative-serving
namespace. Enterkubernetes.namespace_name:knative-serving
in the search box to filter results.
Knative Serving uses structured logging by default. You can enable the parsing of these logs by customizing the OpenShift Logging Fluentd settings. This makes the logs more searchable and enables filtering on the log level to quickly identify issues.
8.3.3. Finding logs for Knative Serving services
You can find the logs for Knative Serving services using the following procedure.
8.3.3.1. Using OpenShift Logging to find logs for services deployed with Knative Serving
With OpenShift Logging, the logs that your applications write to the console are collected in Elasticsearch. The following procedure outlines how to apply these capabilities to applications deployed by using Knative Serving.
Prerequisites
-
Install the OpenShift CLI (
oc
).
Procedure
Get the Kibana route:
$ oc -n openshift-logging get route kibana
- Use the route’s URL to navigate to the Kibana dashboard and log in.
- Check that the index is set to .all. If the index is not set to .all, only the OpenShift system logs will be listed.
Filter the logs by using the
knative-serving
namespace. Enter a filter for the service in the search box to filter results.Example filter
kubernetes.namespace_name:default AND kubernetes.labels.serving_knative_dev\/service:{service_name}
You can also filter by using
/configuration
or/revision
.-
Narrow your search by using
kubernetes.container_name:<user_container>
to only display the logs generated by your application. Otherwise, you will see logs from the queue-proxy.
Use JSON-based structured logging in your application to allow for the quick filtering of these logs in production environments.
8.4. Tracing
8.4.1. Tracing requests
Distributed tracing records the path of a request through the various services that make up an application. It is used to tie information about different units of work together, to understand a whole chain of events in a distributed transaction. The units of work might be executed in different processes or hosts.
8.4.1.1. Distributed tracing overview
As a service owner, you can use distributed tracing to instrument your services to gather insights into your service architecture. You can use distributed tracing for monitoring, network profiling, and troubleshooting the interaction between components in modern, cloud-native, microservices-based applications.
With distributed tracing you can perform the following functions:
- Monitor distributed transactions
- Optimize performance and latency
- Perform root cause analysis
Red Hat OpenShift distributed tracing consists of two main components:
- Red Hat OpenShift distributed tracing platform - This component is based on the open source Jaeger project.
- Red Hat OpenShift distributed tracing data collection - This component is based on the open source OpenTelemetry project.
Both of these components are based on the vendor-neutral OpenTracing APIs and instrumentation.
8.4.1.2. Additional resources
8.4.2. Using Red Hat OpenShift distributed tracing
You can use Red Hat OpenShift distributed tracing with OpenShift Serverless to monitor and troubleshoot serverless applications.
8.4.2.1. Using Red Hat OpenShift distributed tracing to enable distributed tracing
Red Hat OpenShift distributed tracing is made up of several components that work together to collect, store, and display tracing data.
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- You have not yet installed the OpenShift Serverless Operator, Knative Serving, and Knative Eventing. These must be installed after the Red Hat OpenShift distributed tracing installation.
- You have installed Red Hat OpenShift distributed tracing by following the OpenShift Container Platform "Installing distributed tracing" documentation.
-
You have installed the OpenShift CLI (
oc
). - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Create an
OpenTelemetryCollector
custom resource (CR):Example OpenTelemetryCollector CR
apiVersion: opentelemetry.io/v1alpha1 kind: OpenTelemetryCollector metadata: name: cluster-collector namespace: <namespace> spec: mode: deployment config: | receivers: zipkin: processors: exporters: jaeger: endpoint: jaeger-all-in-one-inmemory-collector-headless.tracing-system.svc:14250 tls: ca_file: "/var/run/secrets/kubernetes.io/serviceaccount/service-ca.crt" logging: service: pipelines: traces: receivers: [zipkin] processors: [] exporters: [jaeger, logging]
Verify that you have two pods running in the namespace where Red Hat OpenShift distributed tracing is installed:
$ oc get pods -n <namespace>
Example output
NAME READY STATUS RESTARTS AGE cluster-collector-collector-85c766b5c-b5g99 1/1 Running 0 5m56s jaeger-all-in-one-inmemory-ccbc9df4b-ndkl5 2/2 Running 0 15m
Verify that the following headless services have been created:
$ oc get svc -n <namespace> | grep headless
Example output
cluster-collector-collector-headless ClusterIP None <none> 9411/TCP 7m28s jaeger-all-in-one-inmemory-collector-headless ClusterIP None <none> 9411/TCP,14250/TCP,14267/TCP,14268/TCP 16m
These services are used to configure Jaeger, Knative Serving, and Knative Eventing. The name of the Jaeger service may vary.
- Install the OpenShift Serverless Operator by following the "Installing the OpenShift Serverless Operator" documentation.
Install Knative Serving by creating the following
KnativeServing
CR:Example KnativeServing CR
apiVersion: operator.knative.dev/v1beta1 kind: KnativeServing metadata: name: knative-serving namespace: knative-serving spec: config: tracing: backend: "zipkin" zipkin-endpoint: "http://cluster-collector-collector-headless.tracing-system.svc:9411/api/v2/spans" debug: "false" sample-rate: "0.1" 1
- 1
- The
sample-rate
defines sampling probability. Usingsample-rate: "0.1"
means that 1 in 10 traces are sampled.
Install Knative Eventing by creating the following
KnativeEventing
CR:Example KnativeEventing CR
apiVersion: operator.knative.dev/v1beta1 kind: KnativeEventing metadata: name: knative-eventing namespace: knative-eventing spec: config: tracing: backend: "zipkin" zipkin-endpoint: "http://cluster-collector-collector-headless.tracing-system.svc:9411/api/v2/spans" debug: "false" sample-rate: "0.1" 1
- 1
- The
sample-rate
defines sampling probability. Usingsample-rate: "0.1"
means that 1 in 10 traces are sampled.
Create a Knative service:
Example service
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: helloworld-go spec: template: metadata: labels: app: helloworld-go annotations: autoscaling.knative.dev/minScale: "1" autoscaling.knative.dev/target: "1" spec: containers: - image: quay.io/openshift-knative/helloworld:v1.2 imagePullPolicy: Always resources: requests: cpu: "200m" env: - name: TARGET value: "Go Sample v1"
Make some requests to the service:
Example HTTPS request
$ curl https://helloworld-go.example.com
Get the URL for the Jaeger web console:
Example command
$ oc get route jaeger-all-in-one-inmemory -o jsonpath='{.spec.host}' -n <namespace>
You can now examine traces by using the Jaeger console.
8.4.3. Using Jaeger distributed tracing
If you do not want to install all of the components of Red Hat OpenShift distributed tracing, you can still use distributed tracing on OpenShift Container Platform with OpenShift Serverless.
8.4.3.1. Configuring Jaeger to enable distributed tracing
To enable distributed tracing using Jaeger, you must install and configure Jaeger as a standalone integration.
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- You have installed the OpenShift Serverless Operator, Knative Serving, and Knative Eventing.
- You have installed the Red Hat OpenShift distributed tracing platform Operator.
-
You have installed the OpenShift CLI (
oc
). - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Create and apply a
Jaeger
custom resource (CR) that contains the following:Jaeger CR
apiVersion: jaegertracing.io/v1 kind: Jaeger metadata: name: jaeger namespace: default
Enable tracing for Knative Serving, by editing the
KnativeServing
CR and adding a YAML configuration for tracing:Tracing YAML example for Serving
apiVersion: operator.knative.dev/v1beta1 kind: KnativeServing metadata: name: knative-serving namespace: knative-serving spec: config: tracing: sample-rate: "0.1" 1 backend: zipkin 2 zipkin-endpoint: "http://jaeger-collector.default.svc.cluster.local:9411/api/v2/spans" 3 debug: "false" 4
- 1
- The
sample-rate
defines sampling probability. Usingsample-rate: "0.1"
means that 1 in 10 traces are sampled. - 2
backend
must be set tozipkin
.- 3
- The
zipkin-endpoint
must point to yourjaeger-collector
service endpoint. To get this endpoint, substitute the namespace where the Jaeger CR is applied. - 4
- Debugging should be set to
false
. Enabling debug mode by settingdebug: "true"
allows all spans to be sent to the server, bypassing sampling.
Enable tracing for Knative Eventing by editing the
KnativeEventing
CR:Tracing YAML example for Eventing
apiVersion: operator.knative.dev/v1beta1 kind: KnativeEventing metadata: name: knative-eventing namespace: knative-eventing spec: config: tracing: sample-rate: "0.1" 1 backend: zipkin 2 zipkin-endpoint: "http://jaeger-collector.default.svc.cluster.local:9411/api/v2/spans" 3 debug: "false" 4
- 1
- The
sample-rate
defines sampling probability. Usingsample-rate: "0.1"
means that 1 in 10 traces are sampled. - 2
- Set
backend
tozipkin
. - 3
- Point the
zipkin-endpoint
to yourjaeger-collector
service endpoint. To get this endpoint, substitute the namespace where the Jaeger CR is applied. - 4
- Debugging should be set to
false
. Enabling debug mode by settingdebug: "true"
allows all spans to be sent to the server, bypassing sampling.
Verification
You can access the Jaeger web console to see tracing data, by using the jaeger
route.
Get the
jaeger
route’s hostname by entering the following command:$ oc get route jaeger -n default
Example output
NAME HOST/PORT PATH SERVICES PORT TERMINATION WILDCARD jaeger jaeger-default.apps.example.com jaeger-query <all> reencrypt None
- Open the endpoint address in your browser to view the console.
Chapter 9. Integrations
9.1. Integrating Service Mesh with OpenShift Serverless
The OpenShift Serverless Operator provides Kourier as the default ingress for Knative. However, you can use Service Mesh with OpenShift Serverless whether Kourier is enabled or not. Integrating with Kourier disabled allows you to configure additional networking and routing options that the Kourier ingress does not support, such as mTLS functionality.
OpenShift Serverless only supports the use of Red Hat OpenShift Service Mesh functionality that is explicitly documented in this guide, and does not support other undocumented features.
9.1.1. Prerequisites
The examples in the following procedures use the domain
example.com
. The example certificate for this domain is used as a certificate authority (CA) that signs the subdomain certificate.To complete and verify these procedures in your deployment, you need either a certificate signed by a widely trusted public CA or a CA provided by your organization. Example commands must be adjusted according to your domain, subdomain, and CA.
-
You must configure the wildcard certificate to match the domain of your OpenShift Container Platform cluster. For example, if your OpenShift Container Platform console address is
https://console-openshift-console.apps.openshift.example.com
, you must configure the wildcard certificate so that the domain is*.apps.openshift.example.com
. For more information about configuring wildcard certificates, see the following topic about Creating a certificate to encrypt incoming external traffic. - If you want to use any domain name, including those which are not subdomains of the default OpenShift Container Platform cluster domain, you must set up domain mapping for those domains. For more information, see the OpenShift Serverless documentation about Creating a custom domain mapping.
9.1.2. Creating a certificate to encrypt incoming external traffic
By default, the Service Mesh mTLS feature only secures traffic inside of the Service Mesh itself, between the ingress gateway and individual pods that have sidecars. To encrypt traffic as it flows into the OpenShift Container Platform cluster, you must generate a certificate before you enable the OpenShift Serverless and Service Mesh integration.
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- You have installed the OpenShift Serverless Operator and Knative Serving.
-
Install the OpenShift CLI (
oc
). - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Create a root certificate and private key that signs the certificates for your Knative services:
$ openssl req -x509 -sha256 -nodes -days 365 -newkey rsa:2048 \ -subj '/O=Example Inc./CN=example.com' \ -keyout root.key \ -out root.crt
Create a wildcard certificate:
$ openssl req -nodes -newkey rsa:2048 \ -subj "/CN=*.apps.openshift.example.com/O=Example Inc." \ -keyout wildcard.key \ -out wildcard.csr
Sign the wildcard certificate:
$ openssl x509 -req -days 365 -set_serial 0 \ -CA root.crt \ -CAkey root.key \ -in wildcard.csr \ -out wildcard.crt
Create a secret by using the wildcard certificate:
$ oc create -n istio-system secret tls wildcard-certs \ --key=wildcard.key \ --cert=wildcard.crt
This certificate is picked up by the gateways created when you integrate OpenShift Serverless with Service Mesh, so that the ingress gateway serves traffic with this certificate.
9.1.3. Integrating Service Mesh with OpenShift Serverless
You can integrate Service Mesh with OpenShift Serverless without using Kourier as the default ingress. To do this, do not install the Knative Serving component before completing the following procedure. There are additional steps required when creating the KnativeServing
custom resource definition (CRD) to integrate Knative Serving with Service Mesh, which are not covered in the general Knative Serving installation procedure. This procedure might be useful if you want to integrate Service Mesh as the default and only ingress for your OpenShift Serverless installation.
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Install the Red Hat OpenShift Service Mesh Operator and create a
ServiceMeshControlPlane
resource in theistio-system
namespace. If you want to use mTLS functionality, you must also set thespec.security.dataPlane.mtls
field for theServiceMeshControlPlane
resource totrue
.ImportantUsing OpenShift Serverless with Service Mesh is only supported with Red Hat OpenShift Service Mesh version 2.0.5 or later.
- Install the OpenShift Serverless Operator.
-
Install the OpenShift CLI (
oc
).
Procedure
Add the namespaces that you would like to integrate with Service Mesh to the
ServiceMeshMemberRoll
object as members:apiVersion: maistra.io/v1 kind: ServiceMeshMemberRoll metadata: name: default namespace: istio-system spec: members: 1 - knative-serving - <namespace>
- 1
- A list of namespaces to be integrated with Service Mesh.
ImportantThis list of namespaces must include the
knative-serving
namespace.Apply the
ServiceMeshMemberRoll
resource:$ oc apply -f <filename>
Create the necessary gateways so that Service Mesh can accept traffic:
Example
knative-local-gateway
object using HTTPapiVersion: networking.istio.io/v1alpha3 kind: Gateway metadata: name: knative-ingress-gateway namespace: knative-serving spec: selector: istio: ingressgateway servers: - port: number: 443 name: https protocol: HTTPS hosts: - "*" tls: mode: SIMPLE credentialName: <wildcard_certs> 1 --- apiVersion: networking.istio.io/v1alpha3 kind: Gateway metadata: name: knative-local-gateway namespace: knative-serving spec: selector: istio: ingressgateway servers: - port: number: 8081 name: http protocol: HTTP 2 hosts: - "*" --- apiVersion: v1 kind: Service metadata: name: knative-local-gateway namespace: istio-system labels: experimental.istio.io/disable-gateway-port-translation: "true" spec: type: ClusterIP selector: istio: ingressgateway ports: - name: http2 port: 80 targetPort: 8081
- 1
- Add the name of the secret that contains the wildcard certificate.
- 2
- The
knative-local-gateway
serves HTTP traffic. Using HTTP means that traffic coming from outside of Service Mesh, but using an internal hostname, such asexample.default.svc.cluster.local
, is not encrypted. You can set up encryption for this path by creating another wildcard certificate and an additional gateway that uses a differentprotocol
spec.
Example
knative-local-gateway
object using HTTPSapiVersion: networking.istio.io/v1alpha3 kind: Gateway metadata: name: knative-local-gateway namespace: knative-serving spec: selector: istio: ingressgateway servers: - port: number: 443 name: https protocol: HTTPS hosts: - "*" tls: mode: SIMPLE credentialName: <wildcard_certs>
Apply the
Gateway
resources:$ oc apply -f <filename>
Install Knative Serving by creating the following
KnativeServing
custom resource definition (CRD), which also enables the Istio integration:apiVersion: operator.knative.dev/v1beta1 kind: KnativeServing metadata: name: knative-serving namespace: knative-serving spec: ingress: istio: enabled: true 1 deployments: 2 - name: activator annotations: "sidecar.istio.io/inject": "true" "sidecar.istio.io/rewriteAppHTTPProbers": "true" - name: autoscaler annotations: "sidecar.istio.io/inject": "true" "sidecar.istio.io/rewriteAppHTTPProbers": "true"
Apply the
KnativeServing
resource:$ oc apply -f <filename>
Create a Knative Service that has sidecar injection enabled and uses a pass-through route:
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: <service_name> namespace: <namespace> 1 annotations: serving.knative.openshift.io/enablePassthrough: "true" 2 spec: template: metadata: annotations: sidecar.istio.io/inject: "true" 3 sidecar.istio.io/rewriteAppHTTPProbers: "true" spec: containers: - image: <image_url>
- 1
- A namespace that is part of the Service Mesh member roll.
- 2
- Instructs Knative Serving to generate an OpenShift Container Platform pass-through enabled route, so that the certificates you have generated are served through the ingress gateway directly.
- 3
- Injects Service Mesh sidecars into the Knative service pods.
Apply the
Service
resource:$ oc apply -f <filename>
Verification
Access your serverless application by using a secure connection that is now trusted by the CA:
$ curl --cacert root.crt <service_url>
Example command
$ curl --cacert root.crt https://hello-default.apps.openshift.example.com
Example output
Hello Openshift!
9.1.4. Enabling Knative Serving metrics when using Service Mesh with mTLS
If Service Mesh is enabled with mTLS, metrics for Knative Serving are disabled by default, because Service Mesh prevents Prometheus from scraping metrics. This section shows how to enable Knative Serving metrics when using Service Mesh and mTLS.
Prerequisites
- You have installed the OpenShift Serverless Operator and Knative Serving on your cluster.
- You have installed Red Hat OpenShift Service Mesh with the mTLS functionality enabled.
- You have access to an OpenShift Container Platform account with cluster administrator access.
-
Install the OpenShift CLI (
oc
). - You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Procedure
Specify
prometheus
as themetrics.backend-destination
in theobservability
spec of the Knative Serving custom resource (CR):apiVersion: operator.knative.dev/v1beta1 kind: KnativeServing metadata: name: knative-serving spec: config: observability: metrics.backend-destination: "prometheus" ...
This step prevents metrics from being disabled by default.
Apply the following network policy to allow traffic from the Prometheus namespace:
apiVersion: networking.k8s.io/v1 kind: NetworkPolicy metadata: name: allow-from-openshift-monitoring-ns namespace: knative-serving spec: ingress: - from: - namespaceSelector: matchLabels: name: "openshift-monitoring" podSelector: {} ...
Modify and reapply the default Service Mesh control plane in the
istio-system
namespace, so that it includes the following spec:... spec: proxy: networking: trafficControl: inbound: excludedPorts: - 8444 ...
9.1.5. Integrating Service Mesh with OpenShift Serverless when Kourier is enabled
You can use Service Mesh with OpenShift Serverless even if Kourier is already enabled. This procedure might be useful if you have already installed Knative Serving with Kourier enabled, but decide to add a Service Mesh integration later.
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
-
Install the OpenShift CLI (
oc
). - Install the OpenShift Serverless Operator and Knative Serving on your cluster.
- Install Red Hat OpenShift Service Mesh. OpenShift Serverless with Service Mesh and Kourier is supported for use with both Red Hat OpenShift Service Mesh versions 1.x and 2.x.
Procedure
Add the namespaces that you would like to integrate with Service Mesh to the
ServiceMeshMemberRoll
object as members:apiVersion: maistra.io/v1 kind: ServiceMeshMemberRoll metadata: name: default namespace: istio-system spec: members: - <namespace> 1 ...
- 1
- A list of namespaces to be integrated with Service Mesh.
Apply the
ServiceMeshMemberRoll
resource:$ oc apply -f <filename>
Create a network policy that permits traffic flow from Knative system pods to Knative services:
For each namespace that you want to integrate with Service Mesh, create a
NetworkPolicy
resource:apiVersion: networking.k8s.io/v1 kind: NetworkPolicy metadata: name: allow-from-serving-system-namespace namespace: <namespace> 1 spec: ingress: - from: - namespaceSelector: matchLabels: knative.openshift.io/part-of: "openshift-serverless" podSelector: {} policyTypes: - Ingress ...
- 1
- Add the namespace that you want to integrate with Service Mesh.
NoteThe
knative.openshift.io/part-of: "openshift-serverless"
label was added in OpenShift Serverless 1.22.0. If you are using OpenShift Serverless 1.21.1 or earlier, add theknative.openshift.io/part-of
label to theknative-serving
andknative-serving-ingress
namespaces.Add the label to the
knative-serving
namespace:$ oc label namespace knative-serving knative.openshift.io/part-of=openshift-serverless
Add the label to the
knative-serving-ingress
namespace:$ oc label namespace knative-serving-ingress knative.openshift.io/part-of=openshift-serverless
Apply the
NetworkPolicy
resource:$ oc apply -f <filename>
9.1.6. Improving net-istio memory usage by using secret filtering for Service Mesh
By default, the informers implementation for the Kubernetes client-go
library fetches all resources of a particular type. This can lead to a substantial overhead when many resources are available, which can cause the Knative net-istio
ingress controller to fail on large clusters due to memory leaking. However, a filtering mechanism is available for the Knative net-istio
ingress controller, which enables the controller to only fetch Knative related secrets. You can enable this mechanism by adding an annotation to the KnativeServing
custom resource (CR).
If you enable secret filtering, all of your secrets need to be labeled with networking.internal.knative.dev/certificate-uid: "<id>"
. Otherwise, Knative Serving does not detect them, which leads to failures. You must label both new and existing secrets.
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
- Install Red Hat OpenShift Service Mesh. OpenShift Serverless with Service Mesh only is supported for use with Red Hat OpenShift Service Mesh version 2.0.5 or later.
- Install the OpenShift Serverless Operator and Knative Serving.
-
Install the OpenShift CLI (
oc
).
Procedure
Add the
serverless.openshift.io/enable-secret-informer-filtering
annotation to theKnativeServing
CR:Example KnativeServing CR
apiVersion: operator.knative.dev/v1beta1 kind: KnativeServing metadata: name: knative-serving namespace: knative-serving annotations: serverless.openshift.io/enable-secret-informer-filtering: "true" 1 spec: ingress: istio: enabled: true deployments: - annotations: sidecar.istio.io/inject: "true" sidecar.istio.io/rewriteAppHTTPProbers: "true" name: activator - annotations: sidecar.istio.io/inject: "true" sidecar.istio.io/rewriteAppHTTPProbers: "true" name: autoscaler
- 1
- Adding this annotation injects an environment variable,
ENABLE_SECRET_INFORMER_FILTERING_BY_CERT_UID=true
, to thenet-istio
controller pod.
NoteThis annotation is ignored if you set a different value by overriding deployments.
9.2. Integrating Serverless with the cost management service
Cost management is an OpenShift Container Platform service that enables you to better understand and track costs for clouds and containers. It is based on the open source Koku project.
9.2.1. Prerequisites
- You have cluster administrator permissions.
- You have set up cost management and added an OpenShift Container Platform source.
9.2.2. Using labels for cost management queries
Labels, also known as tags in cost management, can be applied for nodes, namespaces or pods. Each label is a key and value pair. You can use a combination of multiple labels to generate reports. You can access reports about costs by using the Red Hat hybrid console.
Labels are inherited from nodes to namespaces, and from namespaces to pods. However, labels are not overridden if they already exist on a resource. For example, Knative services have a default app=<revision_name>
label:
Example Knative service default label
apiVersion: serving.knative.dev/v1 kind: Service metadata: name: example-service spec: ... labels: app: <revision_name> ...
If you define a label for a namespace, such as app=my-domain
, the cost management service does not take into account costs coming from a Knative service with the tag app=<revision_name>
when querying the application using the app=my-domain
tag. Costs for Knative services that have this tag must be queried under the app=<revision_name>
tag.
9.2.3. Additional resources
9.3. Using NVIDIA GPU resources with serverless applications
NVIDIA supports using GPU resources on OpenShift Container Platform. See GPU Operator on OpenShift for more information about setting up GPU resources on OpenShift Container Platform.
9.3.1. Specifying GPU requirements for a service
After GPU resources are enabled for your OpenShift Container Platform cluster, you can specify GPU requirements for a Knative service using the Knative (kn
) CLI.
Prerequisites
- The OpenShift Serverless Operator, Knative Serving and Knative Eventing are installed on the cluster.
-
You have installed the Knative (
kn
) CLI. - GPU resources are enabled for your OpenShift Container Platform cluster.
- You have created a project or have access to a project with the appropriate roles and permissions to create applications and other workloads in OpenShift Container Platform.
Using NVIDIA GPU resources is not supported for IBM Z and IBM Power.
Procedure
Create a Knative service and set the GPU resource requirement limit to
1
by using the--limit nvidia.com/gpu=1
flag:$ kn service create hello --image <service-image> --limit nvidia.com/gpu=1
A GPU resource requirement limit of
1
means that the service has 1 GPU resource dedicated. Services do not share GPU resources. Any other services that require GPU resources must wait until the GPU resource is no longer in use.A limit of 1 GPU also means that applications exceeding usage of 1 GPU resource are restricted. If a service requests more than 1 GPU resource, it is deployed on a node where the GPU resource requirements can be met.
Optional. For an existing service, you can change the GPU resource requirement limit to
3
by using the--limit nvidia.com/gpu=3
flag:$ kn service update hello --limit nvidia.com/gpu=3
9.3.2. Additional resources
Chapter 10. Removing Serverless
10.1. Removing OpenShift Serverless overview
If you need to remove OpenShift Serverless from your cluster, you can do so by manually removing the OpenShift Serverless Operator and other OpenShift Serverless components. Before you can remove the OpenShift Serverless Operator, you must remove Knative Serving and Knative Eventing.
After uninstalling the OpenShift Serverless, you can remove the Operator and API custom resource definitions (CRDs) that remain on the cluster.
The steps for fully removing OpenShift Serverless are detailed in the following procedures:
10.2. Uninstalling OpenShift Serverless Knative Eventing
Before you can remove the OpenShift Serverless Operator, you must remove Knative Eventing. To uninstall Knative Eventing, you must remove the KnativeEventing
custom resource (CR) and delete the knative-eventing
namespace.
10.2.1. Uninstalling Knative Eventing
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
-
Install the OpenShift CLI (
oc
).
Procedure
Delete the
KnativeEventing
CR:$ oc delete knativeeventings.operator.knative.dev knative-eventing -n knative-eventing
After the command has completed and all pods have been removed from the
knative-eventing
namespace, delete the namespace:$ oc delete namespace knative-eventing
10.3. Uninstalling OpenShift Serverless Knative Serving
Before you can remove the OpenShift Serverless Operator, you must remove Knative Serving. To uninstall Knative Serving, you must remove the KnativeServing
custom resource (CR) and delete the knative-serving
namespace.
10.3.1. Uninstalling Knative Serving
Prerequisites
- You have access to an OpenShift Container Platform account with cluster administrator access.
-
Install the OpenShift CLI (
oc
).
Procedure
Delete the
KnativeServing
CR:$ oc delete knativeservings.operator.knative.dev knative-serving -n knative-serving
After the command has completed and all pods have been removed from the
knative-serving
namespace, delete the namespace:$ oc delete namespace knative-serving
10.4. Removing the OpenShift Serverless Operator
After you have removed Knative Serving and Knative Eventing, you can remove the OpenShift Serverless Operator. You can do this by using the OpenShift Container Platform web console or the oc
CLI.
10.4.1. Deleting Operators from a cluster using the web console
Cluster administrators can delete installed Operators from a selected namespace by using the web console.
Prerequisites
-
Access to an OpenShift Container Platform cluster web console using an account with
cluster-admin
permissions.
Procedure
- Navigate to the Operators → Installed Operators page.
- Scroll or enter a keyword into the Filter by name field to find the Operator that you want to remove. Then, click on it.
On the right side of the Operator Details page, select Uninstall Operator from the Actions list.
An Uninstall Operator? dialog box is displayed.
Select Uninstall to remove the Operator, Operator deployments, and pods. Following this action, the Operator stops running and no longer receives updates.
NoteThis action does not remove resources managed by the Operator, including custom resource definitions (CRDs) and custom resources (CRs). Dashboards and navigation items enabled by the web console and off-cluster resources that continue to run might need manual clean up. To remove these after uninstalling the Operator, you might need to manually delete the Operator CRDs.
10.4.2. Deleting Operators from a cluster using the CLI
Cluster administrators can delete installed Operators from a selected namespace by using the CLI.
Prerequisites
-
Access to an OpenShift Container Platform cluster using an account with
cluster-admin
permissions. -
oc
command installed on workstation.
Procedure
Check the current version of the subscribed Operator (for example,
jaeger
) in thecurrentCSV
field:$ oc get subscription jaeger -n openshift-operators -o yaml | grep currentCSV
Example output
currentCSV: jaeger-operator.v1.8.2
Delete the subscription (for example,
jaeger
):$ oc delete subscription jaeger -n openshift-operators
Example output
subscription.operators.coreos.com "jaeger" deleted
Delete the CSV for the Operator in the target namespace using the
currentCSV
value from the previous step:$ oc delete clusterserviceversion jaeger-operator.v1.8.2 -n openshift-operators
Example output
clusterserviceversion.operators.coreos.com "jaeger-operator.v1.8.2" deleted
10.4.3. Refreshing failing subscriptions
In Operator Lifecycle Manager (OLM), if you subscribe to an Operator that references images that are not accessible on your network, you can find jobs in the openshift-marketplace
namespace that are failing with the following errors:
Example output
ImagePullBackOff for Back-off pulling image "example.com/openshift4/ose-elasticsearch-operator-bundle@sha256:6d2587129c846ec28d384540322b40b05833e7e00b25cca584e004af9a1d292e"
Example output
rpc error: code = Unknown desc = error pinging docker registry example.com: Get "https://example.com/v2/": dial tcp: lookup example.com on 10.0.0.1:53: no such host
As a result, the subscription is stuck in this failing state and the Operator is unable to install or upgrade.
You can refresh a failing subscription by deleting the subscription, cluster service version (CSV), and other related objects. After recreating the subscription, OLM then reinstalls the correct version of the Operator.
Prerequisites
- You have a failing subscription that is unable to pull an inaccessible bundle image.
- You have confirmed that the correct bundle image is accessible.
Procedure
Get the names of the
Subscription
andClusterServiceVersion
objects from the namespace where the Operator is installed:$ oc get sub,csv -n <namespace>
Example output
NAME PACKAGE SOURCE CHANNEL subscription.operators.coreos.com/elasticsearch-operator elasticsearch-operator redhat-operators 5.0 NAME DISPLAY VERSION REPLACES PHASE clusterserviceversion.operators.coreos.com/elasticsearch-operator.5.0.0-65 OpenShift Elasticsearch Operator 5.0.0-65 Succeeded
Delete the subscription:
$ oc delete subscription <subscription_name> -n <namespace>
Delete the cluster service version:
$ oc delete csv <csv_name> -n <namespace>
Get the names of any failing jobs and related config maps in the
openshift-marketplace
namespace:$ oc get job,configmap -n openshift-marketplace
Example output
NAME COMPLETIONS DURATION AGE job.batch/1de9443b6324e629ddf31fed0a853a121275806170e34c926d69e53a7fcbccb 1/1 26s 9m30s NAME DATA AGE configmap/1de9443b6324e629ddf31fed0a853a121275806170e34c926d69e53a7fcbccb 3 9m30s
Delete the job:
$ oc delete job <job_name> -n openshift-marketplace
This ensures pods that try to pull the inaccessible image are not recreated.
Delete the config map:
$ oc delete configmap <configmap_name> -n openshift-marketplace
- Reinstall the Operator using OperatorHub in the web console.
Verification
Check that the Operator has been reinstalled successfully:
$ oc get sub,csv,installplan -n <namespace>
10.5. Deleting OpenShift Serverless custom resource definitions
After uninstalling the OpenShift Serverless, the Operator and API custom resource definitions (CRDs) remain on the cluster. You can use the following procedure to remove the remaining CRDs.
Removing the Operator and API CRDs also removes all resources that were defined by using them, including Knative services.
10.5.1. Removing OpenShift Serverless Operator and API CRDs
Delete the Operator and API CRDs using the following procedure.
Prerequisites
-
Install the OpenShift CLI (
oc
). - You have access to an OpenShift Container Platform account with cluster administrator access.
- You have uninstalled Knative Serving and removed the OpenShift Serverless Operator.
Procedure
To delete the remaining OpenShift Serverless CRDs, enter the following command:
$ oc get crd -oname | grep 'knative.dev' | xargs oc delete
Chapter 11. OpenShift Serverless support
If you experience difficulty with a procedure described in this documentation, visit the Red Hat Customer Portal at http://access.redhat.com. You can use the Red Hat Customer Portal to search or browse through the Red Hat Knowledgebase of technical support articles about Red Hat products. You can also submit a support case to Red Hat Global Support Services (GSS), or access other product documentation.
If you have a suggestion for improving this guide or have found an error, you can submit a Jira issue for the most relevant documentation component. Provide specific details, such as the section number, guide name, and OpenShift Serverless version so we can easily locate the content.
11.1. About the Red Hat Knowledgebase
The Red Hat Knowledgebase provides rich content aimed at helping you make the most of Red Hat’s products and technologies. The Red Hat Knowledgebase consists of articles, product documentation, and videos outlining best practices on installing, configuring, and using Red Hat products. In addition, you can search for solutions to known issues, each providing concise root cause descriptions and remedial steps.
11.2. Searching the Red Hat Knowledgebase
In the event of an OpenShift Container Platform issue, you can perform an initial search to determine if a solution already exists within the Red Hat Knowledgebase.
Prerequisites
- You have a Red Hat Customer Portal account.
Procedure
- Log in to the Red Hat Customer Portal.
In the main Red Hat Customer Portal search field, input keywords and strings relating to the problem, including:
- OpenShift Container Platform components (such as etcd)
- Related procedure (such as installation)
- Warnings, error messages, and other outputs related to explicit failures
- Click Search.
- Select the OpenShift Container Platform product filter.
- Select the Knowledgebase content type filter.
11.3. Submitting a support case
Prerequisites
-
You have installed the OpenShift CLI (
oc
). - You have a Red Hat Customer Portal account.
- You have access to OpenShift Cluster Manager.
Procedure
- Log in to the Red Hat Customer Portal and select SUPPORT CASES → Open a case.
- Select the appropriate category for your issue (such as Defect / Bug), product (OpenShift Container Platform), and product version (4.9, if this is not already autofilled).
- Review the list of suggested Red Hat Knowledgebase solutions for a potential match against the problem that is being reported. If the suggested articles do not address the issue, click Continue.
- Enter a concise but descriptive problem summary and further details about the symptoms being experienced, as well as your expectations.
- Review the updated list of suggested Red Hat Knowledgebase solutions for a potential match against the problem that is being reported. The list is refined as you provide more information during the case creation process. If the suggested articles do not address the issue, click Continue.
- Ensure that the account information presented is as expected, and if not, amend accordingly.
Check that the autofilled OpenShift Container Platform Cluster ID is correct. If it is not, manually obtain your cluster ID.
To manually obtain your cluster ID using the OpenShift Container Platform web console:
- Navigate to Home → Dashboards → Overview.
- Find the value in the Cluster ID field of the Details section.
Alternatively, it is possible to open a new support case through the OpenShift Container Platform web console and have your cluster ID autofilled.
- From the toolbar, navigate to (?) Help → Open Support Case.
- The Cluster ID value is autofilled.
To obtain your cluster ID using the OpenShift CLI (
oc
), run the following command:$ oc get clusterversion -o jsonpath='{.items[].spec.clusterID}{"\n"}'
Complete the following questions where prompted and then click Continue:
- Where are you experiencing the behavior? What environment?
- When does the behavior occur? Frequency? Repeatedly? At certain times?
- What information can you provide around time-frames and the business impact?
-
Upload relevant diagnostic data files and click Continue. It is recommended to include data gathered using the
oc adm must-gather
command as a starting point, plus any issue specific data that is not collected by that command. - Input relevant case management details and click Continue.
- Preview the case details and click Submit.
11.4. Gathering diagnostic information for support
When you open a support case, it is helpful to provide debugging information about your cluster to Red Hat Support. The must-gather
tool enables you to collect diagnostic information about your OpenShift Container Platform cluster, including data related to OpenShift Serverless. For prompt support, supply diagnostic information for both OpenShift Container Platform and OpenShift Serverless.
11.4.1. About the must-gather tool
The oc adm must-gather
CLI command collects the information from your cluster that is most likely needed for debugging issues, including:
- Resource definitions
- Service logs
By default, the oc adm must-gather
command uses the default plugin image and writes into ./must-gather.local
.
Alternatively, you can collect specific information by running the command with the appropriate arguments as described in the following sections:
To collect data related to one or more specific features, use the
--image
argument with an image, as listed in a following section.For example:
$ oc adm must-gather --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.9.0
To collect the audit logs, use the
-- /usr/bin/gather_audit_logs
argument, as described in a following section.For example:
$ oc adm must-gather -- /usr/bin/gather_audit_logs
NoteAudit logs are not collected as part of the default set of information to reduce the size of the files.
When you run oc adm must-gather
, a new pod with a random name is created in a new project on the cluster. The data is collected on that pod and saved in a new directory that starts with must-gather.local
. This directory is created in the current working directory.
For example:
NAMESPACE NAME READY STATUS RESTARTS AGE ... openshift-must-gather-5drcj must-gather-bklx4 2/2 Running 0 72s openshift-must-gather-5drcj must-gather-s8sdh 2/2 Running 0 72s ...
11.4.2. About collecting OpenShift Serverless data
You can use the oc adm must-gather
CLI command to collect information about your cluster, including features and objects associated with OpenShift Serverless. To collect OpenShift Serverless data with must-gather
, you must specify the OpenShift Serverless image and the image tag for your installed version of OpenShift Serverless.
Prerequisites
-
Install the OpenShift CLI (
oc
).
Procedure
Collect data by using the
oc adm must-gather
command:$ oc adm must-gather --image=registry.redhat.io/openshift-serverless-1/svls-must-gather-rhel8:<image_version_tag>
Example command
$ oc adm must-gather --image=registry.redhat.io/openshift-serverless-1/svls-must-gather-rhel8:1.14.0
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