Chapter 3. Event sinks


3.1. Event sinks

When you create an event source, you can specify an event sink where events are sent to from the source. An event 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 event sinks. There is also a specific Apache Kafka sink type available.

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.

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 in http://event-display.svc.cluster.local determines that the sink is a Knative service. Other default sink prefixes include channel, and broker.
Tip

You can configure which CRs can be used with the --sink flag for Knative (kn) CLI commands by Customizing kn.

3.2. Creating event sinks

When you create an event source, you can specify an event sink where events are sent to from the source. An event 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 event sinks. There is also a specific Apache Kafka sink type available.

For information about creating resources that can be used as event sinks, see the following documentation:

3.3. Sink for Apache Kafka

Apache Kafka sinks are a type of event sink that are available if a cluster administrator has enabled Apache Kafka on your cluster. You can send events directly from an event source to a Kafka topic by using a Kafka sink.

3.3.1. Creating an Apache Kafka sink by using YAML

You can create a Kafka sink that sends events to a Kafka topic. 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

  1. 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>

  2. To create the Kafka sink, apply the KafkaSink YAML file:

    $ oc apply -f <filename>
  3. 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

    1
    The name of the event source.
    2
    The namespace of the event source.
    3
    The service account for the event source.
    4
    The Kafka sink name.

3.3.2. Creating an event sink for Apache Kafka by using the OpenShift Container Platform web console

You can create a Kafka sink that sends events to a Kafka topic by using the Developer perspective in the OpenShift Container Platform web console. By default, a Kafka sink uses the binary content mode, which is more efficient than the structured mode.

As a developer, you can create an event sink to receive events from a particular source and send them to a Kafka topic.

Prerequisites

  • You have installed the OpenShift Serverless Operator, with Knative Serving, Knative Eventing, and Knative broker for Apache Kafka APIs, from the OperatorHub.
  • You have created a Kafka topic in your Kafka environment.

Procedure

  1. In the Developer perspective, navigate to the +Add view.
  2. Click Event Sink in the Eventing catalog.
  3. Search for KafkaSink in the catalog items and click it.
  4. Click Create Event Sink.
  5. In the form view, type the URL of the bootstrap server, which is a combination of host name and port.

    create event sink
  6. Type the name of the topic to send event data.
  7. Type the name of the event sink.
  8. Click Create.

Verification

  1. In the Developer perspective, navigate to the Topology view.
  2. Click the created event sink to view its details in the right panel.

3.3.3. Configuring security for Apache 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 the Knative broker implementation for Apache 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, or SCRAM-SHA-512.

Procedure

  1. Create the certificate files as a secret in the same namespace as your KafkaSink object:

    Important

    Certificates 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.
    • 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.
  2. Create or modify a KafkaSink object and add a reference to your secret in the auth spec:

    apiVersion: eventing.knative.dev/v1alpha1
    kind: KafkaSink
    metadata:
       name: <sink_name>
       namespace: <namespace>
    spec:
    ...
       auth:
         secret:
           ref:
             name: <secret_name>
    ...
  3. Apply the KafkaSink object:

    $ oc apply -f <filename>

3.4. JobSink

Event processing usually completes within a short time frame, such as a few minutes. This ensures that the HTTP connection remains open and the service does not scale down prematurely.

Maintaining long-running connections increases the risk of failure, potentially leading to processing restarts and repeated request retries.

You can use JobSink to support long-running asynchronous jobs and tasks using the full Kubernetes batch/v1 Job resource and features and Kubernetes job queuing systems such as Kueue.

3.4.1. Using JobSink

When an event is sent to a JobSink, Eventing creates a Job and mounts the received event as JSON file at /etc/jobsink-event/event.

Procedure

  1. Create a JobSink object definition as a YAML file:

    JobSink YAML

    apiVersion: sinks.knative.dev/v1alpha1
    kind: JobSink
    metadata:
      name: job-sink-logger
    spec:
      job:
        spec:
          completions: 1
          parallelism: 1
          template:
            spec:
              restartPolicy: Never
              containers:
                - name: main
                  image: docker.io/library/bash:5
                  command: [ "cat" ]
                  args:
                    - "/etc/jobsink-event/event"

  2. Apply the JobSink YAML file:

    $ oc apply -f <job-sink-file.yaml>
  3. Verify JobSink is ready:

    $ oc get jobsinks.sinks.knative.dev

    Example output:

    NAME              URL                                                                          AGE   READY   REASON
    job-sink-logger   http://job-sink.knative-eventing.svc.cluster.local/default/job-sink-logger   5s    True
  4. Trigger a JobSink. JobSink can be triggered by any event source or trigger.

    $ oc run curl --image=curlimages/curl --rm=true --restart=Never -ti -- -X POST -v \
       -H "content-type: application/json"  \
       -H "ce-specversion: 1.0" \
       -H "ce-source: my/curl/command" \
       -H "ce-type: my.demo.event" \
       -H "ce-id: 123" \
       -d '{"details":"JobSinkDemo"}' \
       http://job-sink.knative-eventing.svc.cluster.local/default/job-sink-logger
  5. Verify a Job is created:

    $ oc logs job-sink-loggerszoi6-dqbtq

    Example output:

    {"specversion":"1.0","id":"123","source":"my/curl/command","type":"my.demo.event","datacontenttype":"application/json","data":{"details":"JobSinkDemo"}}
Note

JobSink creates a Job for each unique event it receives.

An event is uniquely identified by the combination of its source and id attributes.

If an event with the same attributes is received while a Job for that event already exists, another Job will not be created.

3.4.2. Reading the Job event file

Procedure

  • Read the event file and deserialize it by using any CloudEvents JSON deserializer. The following example demonstrates how to read and process an event using CloudEvents Go SDK:

    package mytask
    
    import (
        "encoding/json"
        "fmt"
        "os"
    
        cloudevents "github.com/cloudevents/sdk-go/v2"
    )
    
    func handleEvent() error {
        eventBytes, err := os.ReadFile("/etc/jobsink-event/event")
        if err != nil {
            return err
        }
    
        event := &cloudevents.Event{}
        if err := json.Unmarshal(eventBytes, event); err != nil {
            return err
        }
    
        fmt.Println(event)
    
        return nil
    }

3.4.3. Setting custom event file mount path

You can set a custom event file mount path in your JobSink definition.

Procedure

  • Inside your container definition, include the volumeMounts configuration and set as required.

    apiVersion: sinks.knative.dev/v1alpha1
    kind: JobSink
    metadata:
      name: job-sink-custom-mount-path
    spec:
      job:
        spec:
          completions: 1
          parallelism: 1
          template:
            spec:
              restartPolicy: Never
              containers:
                - name: main
                  image: docker.io/library/bash:5
                  command: [ "bash" ]
                  args:
                    - -c
                    - echo "Hello world!" && sleep 5
    
                  # The event will be available in a file at `/etc/custom-path/event`
                  volumeMounts:
                    - name: "jobsink-event"
                      mountPath: "/etc/custom-path"
                      readOnly: true

3.4.4. Cleaning up finished jobs

You can clean up finished jobs by setting a ttlSecondsAfterFinished value in your JobSink definition. For example, setting the value to 600 removes completed jobs 600 seconds (10 minutes) after they finish.

Procedure

  • In your definition, set the value of ttlSecondsAfterFinished to the required amount.

    Example of ttlSecondsAfterFinished set to 600

    apiVersion: sinks.knative.dev/v1alpha1
    kind: JobSink
    metadata:
      name: job-sink-example
    spec:
      job:
        spec:
          ttlSecondsAfterFinished: 600

3.4.5. Simulating FailJob action

Procedure

  • Trigger a FailJob action by including a bug simulating command in your JobSink definition.

    Example of JobSink failure

    apiVersion: sinks.knative.dev/v1alpha1
    kind: JobSink
    metadata:
      name: job-sink-failure
    spec:
      job:
        metadata:
          labels:
            my-label: my-value
        spec:
          completions: 12
          parallelism: 3
          template:
            spec:
              restartPolicy: Never
              containers:
                - name: main
                  image: docker.io/library/bash:5
                  command: [ "bash" ]        # example command simulating a bug which triggers the FailJob action
                  args:
                    - -c
                    - echo "Hello world!" && sleep 5 && exit 42
          backoffLimit: 6
          podFailurePolicy:
            rules:
              - action: FailJob
                onExitCodes:
                  containerName: main      # optional
                  operator: In             # one of: In, NotIn
                  values: [ 42 ]
              - action: Ignore             # one of: Ignore, FailJob, Count
                onPodConditions:
                  - type: DisruptionTarget   # indicates Pod disruption

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