Chapter 3. Distributed tracing installation
3.1. Installing distributed tracing
You can install Red Hat OpenShift distributed tracing on OpenShift Container Platform in either of two ways:
-
You can install Red Hat OpenShift distributed tracing as part of Red Hat OpenShift Service Mesh. Distributed tracing is included by default in the Service Mesh installation. To install Red Hat OpenShift distributed tracing as part of a service mesh, follow the Red Hat Service Mesh Installation instructions. You must install Red Hat OpenShift distributed tracing in the same namespace as your service mesh, that is, the
ServiceMeshControlPlane
and the Red Hat OpenShift distributed tracing resources must be in the same namespace. - If you do not want to install a service mesh, you can use the Red Hat OpenShift distributed tracing Operators to install distributed tracing by itself. To install Red Hat OpenShift distributed tracing without a service mesh, use the following instructions.
3.1.1. Prerequisites
Before you can install Red Hat OpenShift distributed tracing, review the installation activities, and ensure that you meet the prerequisites:
- Possess an active OpenShift Container Platform subscription on your Red Hat account. If you do not have a subscription, contact your sales representative for more information.
- Review the OpenShift Container Platform 4.6 overview.
Install OpenShift Container Platform 4.6.
-
Install the version of the OpenShift CLI (
oc
) that matches your OpenShift Container Platform version and add it to your path. -
An account with the
cluster-admin
role.
3.1.2. Red Hat OpenShift distributed tracing installation overview
The steps for installing Red Hat OpenShift distributed tracing are as follows:
- Review the documentation and determine your deployment strategy.
- If your deployment strategy requires persistent storage, install the OpenShift Elasticsearch Operator via the OperatorHub.
- Install the Red Hat OpenShift distributed tracing platform Operator via the OperatorHub.
- Modify the custom resource YAML file to support your deployment strategy.
- Deploy one or more instances of Red Hat OpenShift distributed tracing platform to your OpenShift Container Platform environment.
3.1.3. Installing the OpenShift Elasticsearch Operator
The default Red Hat OpenShift distributed tracing platform deployment uses in-memory storage because it is designed to be installed quickly for those evaluating Red Hat OpenShift distributed tracing, giving demonstrations, or using Red Hat OpenShift distributed tracing platform in a test environment. If you plan to use Red Hat OpenShift distributed tracing platform in production, you must install and configure a persistent storage option, in this case, Elasticsearch.
Prerequisites
- You have access to the OpenShift Container Platform web console.
-
You have access to the cluster as a user with the
cluster-admin
role. If you use Red Hat OpenShift Dedicated, you must have an account with thededicated-admin
role.
Do not install Community versions of the Operators. Community Operators are not supported.
If you have already installed the OpenShift Elasticsearch Operator as part of OpenShift Logging, you do not need to install the OpenShift Elasticsearch Operator again. The Red Hat OpenShift distributed tracing platform Operator creates the Elasticsearch instance using the installed OpenShift Elasticsearch Operator.
Procedure
-
Log in to the OpenShift Container Platform web console as a user with the
cluster-admin
role. If you use Red Hat OpenShift Dedicated, you must have an account with thededicated-admin
role. -
Navigate to Operators
OperatorHub. - Type Elasticsearch into the filter box to locate the OpenShift Elasticsearch Operator.
- Click the OpenShift Elasticsearch Operator provided by Red Hat to display information about the Operator.
- Click Install.
- On the Install Operator page, select the stable Update Channel. This automatically updates your Operator as new versions are released.
Accept the default All namespaces on the cluster (default). This installs the Operator in the default
openshift-operators-redhat
project and makes the Operator available to all projects in the cluster.NoteThe Elasticsearch installation requires the openshift-operators-redhat namespace for the OpenShift Elasticsearch Operator. The other Red Hat OpenShift distributed tracing Operators are installed in the
openshift-operators
namespace.Accept the default Automatic approval strategy. By accepting the default, when a new version of this Operator is available, Operator Lifecycle Manager (OLM) automatically upgrades the running instance of your Operator without human intervention. If you select Manual updates, when a newer version of an Operator is available, OLM creates an update request. As a cluster administrator, you must then manually approve that update request to have the Operator updated to the new version.
NoteThe Manual approval strategy requires a user with appropriate credentials to approve the Operator install and subscription process.
- Click Install.
-
On the Installed Operators page, select the
openshift-operators-redhat
project. Wait until you see that the OpenShift Elasticsearch Operator shows a status of "InstallSucceeded" before continuing.
3.1.4. Installing the Red Hat OpenShift distributed tracing platform Operator
To install Red Hat OpenShift distributed tracing platform, you use the OperatorHub to install the Red Hat OpenShift distributed tracing platform Operator.
By default, the Operator is installed in the openshift-operators
project.
Prerequisites
- You have access to the OpenShift Container Platform web console.
-
You have access to the cluster as a user with the
cluster-admin
role. If you use Red Hat OpenShift Dedicated, you must have an account with thededicated-admin
role. - If you require persistent storage, you must also install the OpenShift Elasticsearch Operator before installing the Red Hat OpenShift distributed tracing platform Operator.
Do not install Community versions of the Operators. Community Operators are not supported.
Procedure
-
Log in to the OpenShift Container Platform web console as a user with the
cluster-admin
role. If you use Red Hat OpenShift Dedicated, you must have an account with thededicated-admin
role. -
Navigate to Operators
OperatorHub. - Type distributing tracing platform into the filter to locate the Red Hat OpenShift distributed tracing platform Operator.
- Click the Red Hat OpenShift distributed tracing platform Operator provided by Red Hat to display information about the Operator.
- Click Install.
- On the Install Operator page, select the stable Update Channel. This automatically updates your Operator as new versions are released.
Accept the default All namespaces on the cluster (default). This installs the Operator in the default
openshift-operators
project and makes the Operator available to all projects in the cluster.Accept the default Automatic approval strategy. By accepting the default, when a new version of this Operator is available, Operator Lifecycle Manager (OLM) automatically upgrades the running instance of your Operator without human intervention. If you select Manual updates, when a newer version of an Operator is available, OLM creates an update request. As a cluster administrator, you must then manually approve that update request to have the Operator updated to the new version.
NoteThe Manual approval strategy requires a user with appropriate credentials to approve the Operator install and subscription process.
- Click Install.
-
Navigate to Operators
Installed Operators. -
On the Installed Operators page, select the
openshift-operators
project. Wait until you see that the Red Hat OpenShift distributed tracing platform Operator shows a status of "Succeeded" before continuing.
3.1.5. Installing the Red Hat OpenShift distributed tracing data collection Operator
The Red Hat OpenShift distributed tracing data collection Operator 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 https://access.redhat.com/support/offerings/techpreview/.
To install Red Hat OpenShift distributed tracing data collection, you use the OperatorHub to install the Red Hat OpenShift distributed tracing data collection Operator.
By default, the Operator is installed in the openshift-operators
project.
Prerequisites
- You have access to the OpenShift Container Platform web console.
-
You have access to the cluster as a user with the
cluster-admin
role. If you use Red Hat OpenShift Dedicated, you must have an account with thededicated-admin
role.
Do not install Community versions of the Operators. Community Operators are not supported.
Procedure
-
Log in to the OpenShift Container Platform web console as a user with the
cluster-admin
role. If you use Red Hat OpenShift Dedicated, you must have an account with thededicated-admin
role. -
Navigate to Operators
OperatorHub. - Type distributing tracing data collection into the filter to locate the Red Hat OpenShift distributed tracing data collection Operator.
- Click the Red Hat OpenShift distributed tracing data collection Operator provided by Red Hat to display information about the Operator.
- Click Install.
- On the Install Operator page, accept the default stable Update channel. This automatically updates your Operator as new versions are released.
-
Accept the default All namespaces on the cluster (default). This installs the Operator in the default
openshift-operators
project and makes the Operator available to all projects in the cluster. Accept the default Automatic approval strategy. By accepting the default, when a new version of this Operator is available, Operator Lifecycle Manager (OLM) automatically upgrades the running instance of your Operator without human intervention. If you select Manual updates, when a newer version of an Operator is available, OLM creates an update request. As a cluster administrator, you must then manually approve that update request to have the Operator updated to the new version.
NoteThe Manual approval strategy requires a user with appropriate credentials to approve the Operator install and subscription process.
- Click Install.
-
Navigate to Operators
Installed Operators. -
On the Installed Operators page, select the
openshift-operators
project. Wait until you see that the Red Hat OpenShift distributed tracing data collection Operator shows a status of "Succeeded" before continuing.
3.2. Configuring and deploying distributed tracing
The Red Hat OpenShift distributed tracing platform Operator uses a custom resource definition (CRD) file that defines the architecture and configuration settings to be used when creating and deploying the distributed tracing platform resources. You can either install the default configuration or modify the file to better suit your business requirements.
Red Hat OpenShift distributed tracing platform has predefined deployment strategies. You specify a deployment strategy in the custom resource file. When you create a distributed tracing platform instance the Operator uses this configuration file to create the objects necessary for the deployment.
Jaeger custom resource file showing deployment strategy
apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
name: MyConfigFile
spec:
strategy: production 1
- 1
- The Red Hat OpenShift distributed tracing platform Operator currently supports the following deployment strategies:
allInOne (Default) - This strategy is intended for development, testing, and demo purposes; it is not intended for production use. The main backend components, Agent, Collector, and Query service, are all packaged into a single executable which is configured, by default. to use in-memory storage.
NoteIn-memory storage is not persistent, which means that if the distributed tracing platform instance shuts down, restarts, or is replaced, that your trace data will be lost. And in-memory storage cannot be scaled, since each pod has its own memory. For persistent storage, you must use the
production
orstreaming
strategies, which use Elasticsearch as the default storage.- production - The production strategy is intended for production environments, where long term storage of trace data is important, as well as a more scalable and highly available architecture is required. Each of the backend components is therefore deployed separately. The Agent can be injected as a sidecar on the instrumented application. The Query and Collector services are configured with a supported storage type - currently Elasticsearch. Multiple instances of each of these components can be provisioned as required for performance and resilience purposes.
streaming - The streaming strategy is designed to augment the production strategy by providing a streaming capability that effectively sits between the Collector and the Elasticsearch backend storage. This provides the benefit of reducing the pressure on the backend storage, under high load situations, and enables other trace post-processing capabilities to tap into the real time span data directly from the streaming platform (AMQ Streams/ Kafka).
NoteThe streaming strategy requires an additional Red Hat subscription for AMQ Streams.
The streaming deployment strategy is currently unsupported on IBM Z.
There are two ways to install and use Red Hat OpenShift distributed tracing, as part of a service mesh or as a stand alone component. If you have installed distributed tracing as part of Red Hat OpenShift Service Mesh, you can perform basic configuration as part of the ServiceMeshControlPlane but for completely control you should configure a Jaeger CR and then reference your distributed tracing configuration file in the ServiceMeshControlPlane.
3.2.1. Deploying the distributed tracing default strategy from the web console
The custom resource definition (CRD) defines the configuration used when you deploy an instance of Red Hat OpenShift distributed tracing. The default CR is named jaeger-all-in-one-inmemory
and it is configured with minimal resources to ensure that you can successfully install it on a default OpenShift Container Platform installation. You can use this default configuration to create a Red Hat OpenShift distributed tracing platform instance that uses the AllInOne
deployment strategy, or you can define your own custom resource file.
In-memory storage is not persistent. If the Jaeger pod shuts down, restarts, or is replaced, your trace data will be lost. For persistent storage, you must use the production
or streaming
strategies, which use Elasticsearch as the default storage.
Prerequisites
- The Red Hat OpenShift distributed tracing platform Operator has been installed.
- You have reviewed the instructions for how to customize the deployment.
-
You have access to the cluster as a user with the
cluster-admin
role.
Procedure
-
Log in to the OpenShift Container Platform web console as a user with the
cluster-admin
role. Create a new project, for example
tracing-system
.NoteIf you are installing as part of Service Mesh, the distributed tracing resources must be installed in the same namespace as the
ServiceMeshControlPlane
resource, for exampleistio-system
.-
Navigate to Home
Projects. - Click Create Project.
-
Enter
tracing-system
in the Name field. - Click Create.
-
Navigate to Home
-
Navigate to Operators
Installed Operators. -
If necessary, select
tracing-system
from the Project menu. You may have to wait a few moments for the Operators to be copied to the new project. - Click the Red Hat OpenShift distributed tracing platform Operator. On the Details tab, under Provided APIs, the Operator provides a single link.
- Under Jaeger, click Create Instance.
- On the Create Jaeger page, to install using the defaults, click Create to create the distributed tracing platform instance.
-
On the Jaegers page, click the name of the distributed tracing platform instance, for example,
jaeger-all-in-one-inmemory
. - On the Jaeger Details page, click the Resources tab. Wait until the pod has a status of "Running" before continuing.
3.2.1.1. Deploying the distributed tracing default strategy from the CLI
Follow this procedure to create an instance of distributed tracing platform from the command line.
Prerequisites
- The Red Hat OpenShift distributed tracing platform Operator has been installed and verified.
- You have reviewed the instructions for how to customize the deployment.
-
You have access to the OpenShift CLI (
oc
) that matches your OpenShift Container Platform version. -
You have access to the cluster as a user with the
cluster-admin
role.
Procedure
Log in to the OpenShift Container Platform CLI as a user with the
cluster-admin
role.$ oc login --username=<NAMEOFUSER> https://<HOSTNAME>:8443
Create a new project named
tracing-system
.$ oc new-project tracing-system
Create a custom resource file named
jaeger.yaml
that contains the following text:Example jaeger-all-in-one.yaml
apiVersion: jaegertracing.io/v1 kind: Jaeger metadata: name: jaeger-all-in-one-inmemory
Run the following command to deploy distributed tracing platform:
$ oc create -n tracing-system -f jaeger.yaml
Run the following command to watch the progress of the pods during the installation process:
$ oc get pods -n tracing-system -w
After the installation process has completed, you should see output similar to the following example:
NAME READY STATUS RESTARTS AGE jaeger-all-in-one-inmemory-cdff7897b-qhfdx 2/2 Running 0 24s
3.2.2. Deploying the distributed tracing production strategy from the web console
The production
deployment strategy is intended for production environments that require a more scalable and highly available architecture, and where long-term storage of trace data is important.
Prerequisites
- The OpenShift Elasticsearch Operator has been installed.
- The Red Hat OpenShift distributed tracing platform Operator has been installed.
- You have reviewed the instructions for how to customize the deployment.
-
You have access to the cluster as a user with the
cluster-admin
role.
Procedure
-
Log in to the OpenShift Container Platform web console as a user with the
cluster-admin
role. Create a new project, for example
tracing-system
.NoteIf you are installing as part of Service Mesh, the distributed tracing resources must be installed in the same namespace as the
ServiceMeshControlPlane
resource, for exampleistio-system
.-
Navigate to Home
Projects. - Click Create Project.
-
Enter
tracing-system
in the Name field. - Click Create.
-
Navigate to Home
-
Navigate to Operators
Installed Operators. -
If necessary, select
tracing-system
from the Project menu. You may have to wait a few moments for the Operators to be copied to the new project. - Click the Red Hat OpenShift distributed tracing platform Operator. On the Overview tab, under Provided APIs, the Operator provides a single link.
- Under Jaeger, click Create Instance.
On the Create Jaeger page, replace the default
all-in-one
YAML text with your production YAML configuration, for example:Example jaeger-production.yaml file with Elasticsearch
apiVersion: jaegertracing.io/v1 kind: Jaeger metadata: name: jaeger-production namespace: spec: strategy: production ingress: security: oauth-proxy storage: type: elasticsearch elasticsearch: nodeCount: 3 redundancyPolicy: SingleRedundancy esIndexCleaner: enabled: true numberOfDays: 7 schedule: 55 23 * * * esRollover: schedule: '*/30 * * * *'
- Click Create to create the distributed tracing platform instance.
-
On the Jaegers page, click the name of the distributed tracing platform instance, for example,
jaeger-prod-elasticsearch
. - On the Jaeger Details page, click the Resources tab. Wait until all the pods have a status of "Running" before continuing.
3.2.2.1. Deploying the distributed tracing production strategy from the CLI
Follow this procedure to create an instance of distributed tracing platform from the command line.
Prerequisites
- The OpenShift Elasticsearch Operator has been installed.
- The Red Hat OpenShift distributed tracing platform Operator has been installed.
- You have reviewed the instructions for how to customize the deployment.
-
You have access to the OpenShift CLI (
oc
) that matches your OpenShift Container Platform version. -
You have access to the cluster as a user with the
cluster-admin
role.
Procedure
Log in to the OpenShift Container Platform CLI as a user with the
cluster-admin
role.$ oc login --username=<NAMEOFUSER> https://<HOSTNAME>:8443
Create a new project named
tracing-system
.$ oc new-project tracing-system
-
Create a custom resource file named
jaeger-production.yaml
that contains the text of the example file in the previous procedure. Run the following command to deploy distributed tracing platform:
$ oc create -n tracing-system -f jaeger-production.yaml
Run the following command to watch the progress of the pods during the installation process:
$ oc get pods -n tracing-system -w
After the installation process has completed, you should see output similar to the following example:
NAME READY STATUS RESTARTS AGE elasticsearch-cdm-jaegersystemjaegerproduction-1-6676cf568gwhlw 2/2 Running 0 10m elasticsearch-cdm-jaegersystemjaegerproduction-2-bcd4c8bf5l6g6w 2/2 Running 0 10m elasticsearch-cdm-jaegersystemjaegerproduction-3-844d6d9694hhst 2/2 Running 0 10m jaeger-production-collector-94cd847d-jwjlj 1/1 Running 3 8m32s jaeger-production-query-5cbfbd499d-tv8zf 3/3 Running 3 8m32s
3.2.3. Deploying the distributed tracing streaming strategy from the web console
The streaming
deployment strategy is intended for production environments that require a more scalable and highly available architecture, and where long-term storage of trace data is important.
The streaming
strategy provides a streaming capability that sits between the Collector and the Elasticsearch storage. This reduces the pressure on the storage under high load situations, and enables other trace post-processing capabilities to tap into the real-time span data directly from the Kafka streaming platform.
The streaming strategy requires an additional Red Hat subscription for AMQ Streams. If you do not have an AMQ Streams subscription, contact your sales representative for more information.
The streaming deployment strategy is currently unsupported on IBM Z.
Prerequisites
- The AMQ Streams Operator has been installed. If using version 1.4.0 or higher you can use self-provisioning. Otherwise you must create the Kafka instance.
- The Red Hat OpenShift distributed tracing platform Operator has been installed.
- You have reviewed the instructions for how to customize the deployment.
-
You have access to the cluster as a user with the
cluster-admin
role.
Procedure
-
Log in to the OpenShift Container Platform web console as a user with the
cluster-admin
role. Create a new project, for example
tracing-system
.NoteIf you are installing as part of Service Mesh, the distributed tracing resources must be installed in the same namespace as the
ServiceMeshControlPlane
resource, for exampleistio-system
.-
Navigate to Home
Projects. - Click Create Project.
-
Enter
tracing-system
in the Name field. - Click Create.
-
Navigate to Home
-
Navigate to Operators
Installed Operators. -
If necessary, select
tracing-system
from the Project menu. You may have to wait a few moments for the Operators to be copied to the new project. - Click the Red Hat OpenShift distributed tracing platform Operator. On the Overview tab, under Provided APIs, the Operator provides a single link.
- Under Jaeger, click Create Instance.
-
On the Create Jaeger page, replace the default
all-in-one
YAML text with your streaming YAML configuration, for example:
Example jaeger-streaming.yaml file
apiVersion: jaegertracing.io/v1 kind: Jaeger metadata: name: jaeger-streaming spec: strategy: streaming collector: options: kafka: producer: topic: jaeger-spans #Note: If brokers are not defined,AMQStreams 1.4.0+ will self-provision Kafka. brokers: my-cluster-kafka-brokers.kafka:9092 storage: type: elasticsearch ingester: options: kafka: consumer: topic: jaeger-spans brokers: my-cluster-kafka-brokers.kafka:9092
- Click Create to create the distributed tracing platform instance.
-
On the Jaegers page, click the name of the distributed tracing platform instance, for example,
jaeger-streaming
. - On the Jaeger Details page, click the Resources tab. Wait until all the pods have a status of "Running" before continuing.
3.2.3.1. Deploying the distributed tracing streaming strategy from the CLI
Follow this procedure to create an instance of distributed tracing platform from the command line.
Prerequisites
- The AMQ Streams Operator has been installed. If using version 1.4.0 or higher you can use self-provisioning. Otherwise you must create the Kafka instance.
- The Red Hat OpenShift distributed tracing platform Operator has been installed.
- You have reviewed the instructions for how to customize the deployment.
-
You have access to the OpenShift CLI (
oc
) that matches your OpenShift Container Platform version. -
You have access to the cluster as a user with the
cluster-admin
role.
Procedure
Log in to the OpenShift Container Platform CLI as a user with the
cluster-admin
role.$ oc login --username=<NAMEOFUSER> https://<HOSTNAME>:8443
Create a new project named
tracing-system
.$ oc new-project tracing-system
-
Create a custom resource file named
jaeger-streaming.yaml
that contains the text of the example file in the previous procedure. Run the following command to deploy Jaeger:
$ oc create -n tracing-system -f jaeger-streaming.yaml
Run the following command to watch the progress of the pods during the installation process:
$ oc get pods -n tracing-system -w
After the installation process has completed, you should see output similar to the following example:
NAME READY STATUS RESTARTS AGE elasticsearch-cdm-jaegersystemjaegerstreaming-1-697b66d6fcztcnn 2/2 Running 0 5m40s elasticsearch-cdm-jaegersystemjaegerstreaming-2-5f4b95c78b9gckz 2/2 Running 0 5m37s elasticsearch-cdm-jaegersystemjaegerstreaming-3-7b6d964576nnz97 2/2 Running 0 5m5s jaeger-streaming-collector-6f6db7f99f-rtcfm 1/1 Running 0 80s jaeger-streaming-entity-operator-6b6d67cc99-4lm9q 3/3 Running 2 2m18s jaeger-streaming-ingester-7d479847f8-5h8kc 1/1 Running 0 80s jaeger-streaming-kafka-0 2/2 Running 0 3m1s jaeger-streaming-query-65bf5bb854-ncnc7 3/3 Running 0 80s jaeger-streaming-zookeeper-0 2/2 Running 0 3m39s
3.2.4. Validating your deployment
3.2.4.1. Accessing the Jaeger console
To access the Jaeger console you must have either Red Hat OpenShift Service Mesh or Red Hat OpenShift distributed tracing installed, and Red Hat OpenShift distributed tracing platform installed, configured, and deployed.
The installation process creates a route to access the Jaeger console.
If you know the URL for the Jaeger console, you can access it directly. If you do not know the URL, use the following directions.
Procedure from OpenShift console
-
Log in to the OpenShift Container Platform web console as a user with cluster-admin rights. If you use Red Hat OpenShift Dedicated, you must have an account with the
dedicated-admin
role. -
Navigate to Networking
Routes. On the Routes page, select the control plane project, for example
tracing-system
, from the Namespace menu.The Location column displays the linked address for each route.
-
If necessary, use the filter to find the
jaeger
route. Click the route Location to launch the console. - Click Log In With OpenShift.
Procedure from the CLI
Log in to the OpenShift Container Platform CLI as a user with the
cluster-admin
role. If you use Red Hat OpenShift Dedicated, you must have an account with thededicated-admin
role.$ oc login --username=<NAMEOFUSER> https://<HOSTNAME>:6443
To query for details of the route using the command line, enter the following command. In this example,
tracing-system
is the control plane namespace.$ export JAEGER_URL=$(oc get route -n tracing-system jaeger -o jsonpath='{.spec.host}')
-
Launch a browser and navigate to
https://<JAEGER_URL>
, where<JAEGER_URL>
is the route that you discovered in the previous step. - Log in using the same user name and password that you use to access the OpenShift Container Platform console.
If you have added services to the service mesh and have generated traces, you can use the filters and Find Traces button to search your trace data.
If you are validating the console installation, there is no trace data to display.
3.2.5. Customizing your deployment
3.2.5.1. Deployment best practices
- Red Hat OpenShift distributed tracing instance names must be unique. If you want to have multiple Red Hat OpenShift distributed tracing platform instances and are using sidecar injected agents, then the Red Hat OpenShift distributed tracing platform instances should have unique names, and the injection annotation should explicitly specify the Red Hat OpenShift distributed tracing platform instance name the tracing data should be reported to.
If you have a multitenant implementation and tenants are separated by namespaces, deploy a Red Hat OpenShift distributed tracing platform instance to each tenant namespace.
- Agent as a daemonset is not supported for multitenant installations or Red Hat OpenShift Dedicated. Agent as a sidecar is the only supported configuration for these use cases.
-
If you are installing distributed tracing as part of Red Hat OpenShift Service Mesh, the distributed tracing resources must be installed in the same namespace as the
ServiceMeshControlPlane
resource.
For information about configuring persistent storage, see Understanding persistent storage and the appropriate configuration topic for your chosen storage option.
3.2.5.2. Distributed tracing default configuration options
The Jaeger custom resource (CR) defines the architecture and settings to be used when creating the distributed tracing platform resources. You can modify these parameters to customize your distributed tracing platform implementation to your business needs.
Jaeger generic YAML example
apiVersion: jaegertracing.io/v1 kind: Jaeger metadata: name: name spec: strategy: <deployment_strategy> allInOne: options: {} resources: {} agent: options: {} resources: {} collector: options: {} resources: {} sampling: options: {} storage: type: options: {} query: options: {} resources: {} ingester: options: {} resources: {} options: {}
Parameter | Description | Values | Default value |
---|---|---|---|
| API version to use when creating the object. |
| |
|
| Defines the kind of Kubernetes object to create. |
|
|
Data that helps uniquely identify the object, including a | ||
OpenShift Container Platform automatically generates the |
| Name for the object. | The name of your distributed tracing platform instance. |
|
| Specification for the object to be created. |
Contains all of the configuration parameters for your distributed tracing platform instance. When a common definition for all Jaeger components is required, it is defined under the |
N/A |
| Jaeger deployment strategy |
|
|
|
Because the | |
| Configuration options that define the Agent. | ||
| Configuration options that define the Jaeger Collector. | ||
| Configuration options that define the sampling strategies for tracing. | ||
|
Configuration options that define the storage. All storage-related options must be placed under | ||
| Configuration options that define the Query service. | ||
| Configuration options that define the Ingester service. |
The following example YAML is the minimum required to create a Red Hat OpenShift distributed tracing platform deployment using the default settings.
Example minimum required dist-tracing-all-in-one.yaml
apiVersion: jaegertracing.io/v1 kind: Jaeger metadata: name: jaeger-all-in-one-inmemory
3.2.5.3. Jaeger Collector configuration options
The Jaeger Collector is the component responsible for receiving the spans that were captured by the tracer and writing them to persistent Elasticsearch storage when using the production
strategy, or to AMQ Streams when using the streaming
strategy.
The Collectors are stateless and thus many instances of Jaeger Collector can be run in parallel. Collectors require almost no configuration, except for the location of the Elasticsearch cluster.
Parameter | Description | Values |
---|---|---|
collector: replicas: | Specifies the number of Collector replicas to create. |
Integer, for example, |
Parameter | Description | Values |
---|---|---|
spec: collector: options: {} | Configuration options that define the Jaeger Collector. | |
options: collector: num-workers: | The number of workers pulling from the queue. |
Integer, for example, |
options: collector: queue-size: | The size of the Collector queue. |
Integer, for example, |
options: kafka: producer: topic: jaeger-spans |
The | Label for the producer. |
options: kafka: producer: brokers: my-cluster-kafka-brokers.kafka:9092 | Identifies the Kafka configuration used by the Collector to produce the messages. If brokers are not specified, and you have AMQ Streams 1.4.0+ installed, the Red Hat OpenShift distributed tracing platform Operator will self-provision Kafka. | |
options: log-level: | Logging level for the Collector. |
Possible values: |
3.2.5.4. Distributed tracing sampling configuration options
The Red Hat OpenShift distributed tracing platform Operator can be used to define sampling strategies that will be supplied to tracers that have been configured to use a remote sampler.
While all traces are generated, only a few are sampled. Sampling a trace marks the trace for further processing and storage.
This is not relevant if a trace was started by the Envoy proxy, as the sampling decision is made there. The Jaeger sampling decision is only relevant when the trace is started by an application using the client.
When a service receives a request that contains no trace context, the client starts a new trace, assigns it a random trace ID, and makes a sampling decision based on the currently installed sampling strategy. The sampling decision propagates to all subsequent requests in the trace so that other services are not making the sampling decision again.
distributed tracing platform libraries support the following samplers:
-
Probabilistic - The sampler makes a random sampling decision with the probability of sampling equal to the value of the
sampling.param
property. For example, usingsampling.param=0.1
samples approximately 1 in 10 traces. -
Rate Limiting - The sampler uses a leaky bucket rate limiter to ensure that traces are sampled with a certain constant rate. For example, using
sampling.param=2.0
samples requests with the rate of 2 traces per second.
Parameter | Description | Values | Default value |
---|---|---|---|
spec: sampling: options: {} default_strategy: service_strategy: | Configuration options that define the sampling strategies for tracing. | If you do not provide configuration, the Collectors will return the default probabilistic sampling policy with 0.001 (0.1%) probability for all services. | |
default_strategy: type: service_strategy: type: | Sampling strategy to use. See descriptions above. |
Valid values are |
|
default_strategy: param: service_strategy: param: | Parameters for the selected sampling strategy. | Decimal and integer values (0, .1, 1, 10) | 1 |
This example defines a default sampling strategy that is probabilistic, with a 50% chance of the trace instances being sampled.
Probabilistic sampling example
apiVersion: jaegertracing.io/v1 kind: Jaeger metadata: name: with-sampling spec: sampling: options: default_strategy: type: probabilistic param: 0.5 service_strategies: - service: alpha type: probabilistic param: 0.8 operation_strategies: - operation: op1 type: probabilistic param: 0.2 - operation: op2 type: probabilistic param: 0.4 - service: beta type: ratelimiting param: 5
If there are no user-supplied configurations, the distributed tracing platform uses the following settings:
Default sampling
spec: sampling: options: default_strategy: type: probabilistic param: 1
3.2.5.5. Distributed tracing storage configuration options
You configure storage for the Collector, Ingester, and Query services under spec.storage
. Multiple instances of each of these components can be provisioned as required for performance and resilience purposes.
Parameter | Description | Values | Default value |
---|---|---|---|
spec: storage: type: | Type of storage to use for the deployment. |
|
|
storage: secretname: |
Name of the secret, for example | N/A | |
storage: options: {} | Configuration options that define the storage. |
Parameter | Description | Values | Default value |
---|---|---|---|
storage: esIndexCleaner: enabled: | When using Elasticsearch storage, by default a job is created to clean old traces from the index. This parameter enables or disables the index cleaner job. |
|
|
storage: esIndexCleaner: numberOfDays: | Number of days to wait before deleting an index. | Integer value |
|
storage: esIndexCleaner: schedule: | Defines the schedule for how often to clean the Elasticsearch index. | Cron expression | "55 23 * * *" |
3.2.5.5.1. Auto-provisioning an Elasticsearch instance
When you deploy a Jaeger custom resource, the Red Hat OpenShift distributed tracing platform Operator uses the OpenShift Elasticsearch Operator to create an Elasticsearch cluster based on the configuration provided in the storage
section of the custom resource file. The Red Hat OpenShift distributed tracing platform Operator will provision Elasticsearch if the following configurations are set:
-
spec.storage:type
is set toelasticsearch
-
spec.storage.elasticsearch.doNotProvision
set tofalse
-
spec.storage.options.es.server-urls
is not defined, that is, there is no connection to an Elasticsearch instance that was not provisioned by the Red Hat Elasticsearch Operator.
When provisioning Elasticsearch, the Red Hat OpenShift distributed tracing platform Operator sets the Elasticsearch custom resource name
to the value of spec.storage.elasticsearch.name
from the Jaeger custom resource. If you do not specify a value for spec.storage.elasticsearch.name
, the Operator uses elasticsearch
.
Restrictions
- You can have only one distributed tracing platform with self-provisioned Elasticsearch instance per namespace. The Elasticsearch cluster is meant to be dedicated for a single distributed tracing platform instance.
- There can be only one Elasticsearch per namespace.
If you already have installed Elasticsearch as part of OpenShift Logging, the Red Hat OpenShift distributed tracing platform Operator can use the installed OpenShift Elasticsearch Operator to provision storage.
The following configuration parameters are for a self-provisioned Elasticsearch instance, that is an instance created by the Red Hat OpenShift distributed tracing platform Operator using the OpenShift Elasticsearch Operator. You specify configuration options for self-provisioned Elasticsearch under spec:storage:elasticsearch
in your configuration file.
Parameter | Description | Values | Default value |
---|---|---|---|
elasticsearch: properties: doNotProvision: | Use to specify whether or not an Elasticsearch instance should be provisioned by the Red Hat OpenShift distributed tracing platform Operator. |
|
|
elasticsearch: properties: name: | Name of the Elasticsearch instance. The Red Hat OpenShift distributed tracing platform Operator uses the Elasticsearch instance specified in this parameter to connect to Elasticsearch. | string |
|
elasticsearch: nodeCount: | Number of Elasticsearch nodes. For high availability use at least 3 nodes. Do not use 2 nodes as “split brain” problem can happen. | Integer value. For example, Proof of concept = 1, Minimum deployment =3 | 3 |
elasticsearch: resources: requests: cpu: | Number of central processing units for requests, based on your environment’s configuration. | Specified in cores or millicores, for example, 200m, 0.5, 1. For example, Proof of concept = 500m, Minimum deployment =1 | 1 |
elasticsearch: resources: requests: memory: | Available memory for requests, based on your environment’s configuration. | Specified in bytes, for example, 200Ki, 50Mi, 5Gi. For example, Proof of concept = 1Gi, Minimum deployment = 16Gi* | 16Gi |
elasticsearch: resources: limits: cpu: | Limit on number of central processing units, based on your environment’s configuration. | Specified in cores or millicores, for example, 200m, 0.5, 1. For example, Proof of concept = 500m, Minimum deployment =1 | |
elasticsearch: resources: limits: memory: | Available memory limit based on your environment’s configuration. | Specified in bytes, for example, 200Ki, 50Mi, 5Gi. For example, Proof of concept = 1Gi, Minimum deployment = 16Gi* | |
elasticsearch: redundancyPolicy: | Data replication policy defines how Elasticsearch shards are replicated across data nodes in the cluster. If not specified, the Red Hat OpenShift distributed tracing platform Operator automatically determines the most appropriate replication based on number of nodes. |
| |
elasticsearch: useCertManagement: | Use to specify whether or not distributed tracing platform should use the certificate management feature of the Red Hat Elasticsearch Operator. This feature was added to logging subsystem for Red Hat OpenShift 5.2 in OpenShift Container Platform 4.7 and is the preferred setting for new Jaeger deployments. |
|
|
*Each Elasticsearch node can operate with a lower memory setting though this is NOT recommended for production deployments. For production use, you should have no less than 16Gi allocated to each pod by default, but preferably allocate as much as you can, up to 64Gi per pod. |
Production storage example
apiVersion: jaegertracing.io/v1 kind: Jaeger metadata: name: simple-prod spec: strategy: production storage: type: elasticsearch elasticsearch: nodeCount: 3 resources: requests: cpu: 1 memory: 16Gi limits: memory: 16Gi
Storage example with persistent storage:
apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
name: simple-prod
spec:
strategy: production
storage:
type: elasticsearch
elasticsearch:
nodeCount: 1
storage: 1
storageClassName: gp2
size: 5Gi
resources:
requests:
cpu: 200m
memory: 4Gi
limits:
memory: 4Gi
redundancyPolicy: ZeroRedundancy
- 1
- Persistent storage configuration. In this case AWS
gp2
with5Gi
size. When no value is specified, distributed tracing platform usesemptyDir
. The OpenShift Elasticsearch Operator provisionsPersistentVolumeClaim
andPersistentVolume
which are not removed with distributed tracing platform instance. You can mount the same volumes if you create a distributed tracing platform instance with the same name and namespace.
3.2.5.5.2. Connecting to an existing Elasticsearch instance
You can use an existing Elasticsearch cluster for storage with distributed tracing. An existing Elasticsearch cluster, also known as an external Elasticsearch instance, is an instance that was not installed by the Red Hat OpenShift distributed tracing platform Operator or by the Red Hat Elasticsearch Operator.
When you deploy a Jaeger custom resource, the Red Hat OpenShift distributed tracing platform Operator will not provision Elasticsearch if the following configurations are set:
-
spec.storage.elasticsearch.doNotProvision
set totrue
-
spec.storage.options.es.server-urls
has a value -
spec.storage.elasticsearch.name
has a value, or if the Elasticsearch instance name iselasticsearch
.
The Red Hat OpenShift distributed tracing platform Operator uses the Elasticsearch instance specified in spec.storage.elasticsearch.name
to connect to Elasticsearch.
Restrictions
- You cannot share or reuse a OpenShift Container Platform logging Elasticsearch instance with distributed tracing platform. The Elasticsearch cluster is meant to be dedicated for a single distributed tracing platform instance.
Red Hat does not provide support for your external Elasticsearch instance. You can review the tested integrations matrix on the Customer Portal.
The following configuration parameters are for an already existing Elasticsearch instance, also known as an external Elasticsearch instance. In this case, you specify configuration options for Elasticsearch under spec:storage:options:es
in your custom resource file.
Parameter | Description | Values | Default value |
---|---|---|---|
es: server-urls: | URL of the Elasticsearch instance. | The fully-qualified domain name of the Elasticsearch server. | |
es: max-doc-count: |
The maximum document count to return from an Elasticsearch query. This will also apply to aggregations. If you set both | 10000 | |
es: max-num-spans: |
[Deprecated - Will be removed in a future release, use | 10000 | |
es: max-span-age: | The maximum lookback for spans in Elasticsearch. | 72h0m0s | |
es: sniffer: | The sniffer configuration for Elasticsearch. The client uses the sniffing process to find all nodes automatically. Disabled by default. |
|
|
es: sniffer-tls-enabled: | Option to enable TLS when sniffing an Elasticsearch Cluster. The client uses the sniffing process to find all nodes automatically. Disabled by default |
|
|
es: timeout: | Timeout used for queries. When set to zero there is no timeout. | 0s | |
es: username: |
The username required by Elasticsearch. The basic authentication also loads CA if it is specified. See also | ||
es: password: |
The password required by Elasticsearch. See also, | ||
es: version: | The major Elasticsearch version. If not specified, the value will be auto-detected from Elasticsearch. | 0 |
Parameter | Description | Values | Default value |
---|---|---|---|
es: num-replicas: | The number of replicas per index in Elasticsearch. | 1 | |
es: num-shards: | The number of shards per index in Elasticsearch. | 5 |
Parameter | Description | Values | Default value |
---|---|---|---|
es: create-index-templates: |
Automatically create index templates at application startup when set to |
|
|
es: index-prefix: | Optional prefix for distributed tracing platform indices. For example, setting this to "production" creates indices named "production-tracing-*". |
Parameter | Description | Values | Default value |
---|---|---|---|
es: bulk: actions: | The number of requests that can be added to the queue before the bulk processor decides to commit updates to disk. | 1000 | |
es: bulk: flush-interval: |
A | 200ms | |
es: bulk: size: | The number of bytes that the bulk requests can take up before the bulk processor decides to commit updates to disk. | 5000000 | |
es: bulk: workers: | The number of workers that are able to receive and commit bulk requests to Elasticsearch. | 1 |
Parameter | Description | Values | Default value |
---|---|---|---|
es: tls: ca: | Path to a TLS Certification Authority (CA) file used to verify the remote servers. | Will use the system truststore by default. | |
es: tls: cert: | Path to a TLS Certificate file, used to identify this process to the remote servers. | ||
es: tls: enabled: | Enable transport layer security (TLS) when talking to the remote servers. Disabled by default. |
|
|
es: tls: key: | Path to a TLS Private Key file, used to identify this process to the remote servers. | ||
es: tls: server-name: | Override the expected TLS server name in the certificate of the remote servers. | ||
es: token-file: | Path to a file containing the bearer token. This flag also loads the Certification Authority (CA) file if it is specified. |
Parameter | Description | Values | Default value |
---|---|---|---|
es-archive: bulk: actions: | The number of requests that can be added to the queue before the bulk processor decides to commit updates to disk. | 0 | |
es-archive: bulk: flush-interval: |
A | 0s | |
es-archive: bulk: size: | The number of bytes that the bulk requests can take up before the bulk processor decides to commit updates to disk. | 0 | |
es-archive: bulk: workers: | The number of workers that are able to receive and commit bulk requests to Elasticsearch. | 0 | |
es-archive: create-index-templates: |
Automatically create index templates at application startup when set to |
|
|
es-archive: enabled: | Enable extra storage. |
|
|
es-archive: index-prefix: | Optional prefix for distributed tracing platform indices. For example, setting this to "production" creates indices named "production-tracing-*". | ||
es-archive: max-doc-count: | The maximum document count to return from an Elasticsearch query. This will also apply to aggregations. | 0 | |
es-archive: max-num-spans: |
[Deprecated - Will be removed in a future release, use | 0 | |
es-archive: max-span-age: | The maximum lookback for spans in Elasticsearch. | 0s | |
es-archive: num-replicas: | The number of replicas per index in Elasticsearch. | 0 | |
es-archive: num-shards: | The number of shards per index in Elasticsearch. | 0 | |
es-archive: password: |
The password required by Elasticsearch. See also, | ||
es-archive: server-urls: |
The comma-separated list of Elasticsearch servers. Must be specified as fully qualified URLs, for example, | ||
es-archive: sniffer: | The sniffer configuration for Elasticsearch. The client uses the sniffing process to find all nodes automatically. Disabled by default. |
|
|
es-archive: sniffer-tls-enabled: | Option to enable TLS when sniffing an Elasticsearch Cluster. The client uses the sniffing process to find all nodes automatically. Disabled by default. |
|
|
es-archive: timeout: | Timeout used for queries. When set to zero there is no timeout. | 0s | |
es-archive: tls: ca: | Path to a TLS Certification Authority (CA) file used to verify the remote servers. | Will use the system truststore by default. | |
es-archive: tls: cert: | Path to a TLS Certificate file, used to identify this process to the remote servers. | ||
es-archive: tls: enabled: | Enable transport layer security (TLS) when talking to the remote servers. Disabled by default. |
|
|
es-archive: tls: key: | Path to a TLS Private Key file, used to identify this process to the remote servers. | ||
es-archive: tls: server-name: | Override the expected TLS server name in the certificate of the remote servers. | ||
es-archive: token-file: | Path to a file containing the bearer token. This flag also loads the Certification Authority (CA) file if it is specified. | ||
es-archive: username: |
The username required by Elasticsearch. The basic authentication also loads CA if it is specified. See also | ||
es-archive: version: | The major Elasticsearch version. If not specified, the value will be auto-detected from Elasticsearch. | 0 |
Storage example with volume mounts
apiVersion: jaegertracing.io/v1 kind: Jaeger metadata: name: simple-prod spec: strategy: production storage: type: elasticsearch options: es: server-urls: https://quickstart-es-http.default.svc:9200 index-prefix: my-prefix tls: ca: /es/certificates/ca.crt secretName: tracing-secret volumeMounts: - name: certificates mountPath: /es/certificates/ readOnly: true volumes: - name: certificates secret: secretName: quickstart-es-http-certs-public
The following example shows a Jaeger CR using an external Elasticsearch cluster with TLS CA certificate mounted from a volume and user/password stored in a secret.
External Elasticsearch example:
apiVersion: jaegertracing.io/v1 kind: Jaeger metadata: name: simple-prod spec: strategy: production storage: type: elasticsearch options: es: server-urls: https://quickstart-es-http.default.svc:9200 1 index-prefix: my-prefix tls: 2 ca: /es/certificates/ca.crt secretName: tracing-secret 3 volumeMounts: 4 - name: certificates mountPath: /es/certificates/ readOnly: true volumes: - name: certificates secret: secretName: quickstart-es-http-certs-public
- 1
- URL to Elasticsearch service running in default namespace.
- 2
- TLS configuration. In this case only CA certificate, but it can also contain es.tls.key and es.tls.cert when using mutual TLS.
- 3
- Secret which defines environment variables ES_PASSWORD and ES_USERNAME. Created by kubectl create secret generic tracing-secret --from-literal=ES_PASSWORD=changeme --from-literal=ES_USERNAME=elastic
- 4
- Volume mounts and volumes which are mounted into all storage components.
3.2.5.6. Managing certificates with Elasticsearch
You can create and manage certificates using the Red Hat Elasticsearch Operator. Managing certificates using the Red Hat Elasticsearch Operator also lets you use a single Elasticsearch cluster with multiple Jaeger Collectors.
Managing certificates with Elasticsearch 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 https://access.redhat.com/support/offerings/techpreview/.
Starting with version 2.4, the Red Hat OpenShift distributed tracing platform Operator delegates certificate creation to the Red Hat Elasticsearch Operator by using the following annotations in the Elasticsearch custom resource:
-
logging.openshift.io/elasticsearch-cert-management: "true"
-
logging.openshift.io/elasticsearch-cert.jaeger-<shared-es-node-name>: "user.jaeger"
-
logging.openshift.io/elasticsearch-cert.curator-<shared-es-node-name>: "system.logging.curator"
Where the <shared-es-node-name>
is the name of the Elasticsearch node. For example, if you create an Elasticsearch node named custom-es
, your custom resource might look like the following example.
Example Elasticsearch CR showing annotations
apiVersion: logging.openshift.io/v1 kind: Elasticsearch metadata: annotations: logging.openshift.io/elasticsearch-cert-management: "true" logging.openshift.io/elasticsearch-cert.jaeger-custom-es: "user.jaeger" logging.openshift.io/elasticsearch-cert.curator-custom-es: "system.logging.curator" name: custom-es spec: managementState: Managed nodeSpec: resources: limits: memory: 16Gi requests: cpu: 1 memory: 16Gi nodes: - nodeCount: 3 proxyResources: {} resources: {} roles: - master - client - data storage: {} redundancyPolicy: ZeroRedundancy
Prerequisites
- OpenShift Container Platform 4.7
- logging subsystem for Red Hat OpenShift 5.2
-
The Elasticsearch node and the Jaeger instances must be deployed in the same namespace. For example,
tracing-system
.
You enable certificate management by setting spec.storage.elasticsearch.useCertManagement
to true
in the Jaeger custom resource.
Example showing useCertManagement
apiVersion: jaegertracing.io/v1 kind: Jaeger metadata: name: jaeger-prod spec: strategy: production storage: type: elasticsearch elasticsearch: name: custom-es doNotProvision: true useCertManagement: true
The Red Hat OpenShift distributed tracing platform Operator sets the Elasticsearch custom resource name
to the value of spec.storage.elasticsearch.name
from the Jaeger custom resource when provisioning Elasticsearch.
The certificates are provisioned by the Red Hat Elasticsearch Operator and the Red Hat OpenShift distributed tracing platform Operator injects the certificates.
3.2.5.7. Query configuration options
Query is a service that retrieves traces from storage and hosts the user interface to display them.
Parameter | Description | Values | Default value |
---|---|---|---|
spec: query: replicas: | Specifies the number of Query replicas to create. |
Integer, for example, |
Parameter | Description | Values | Default value |
---|---|---|---|
spec: query: options: {} | Configuration options that define the Query service. | ||
options: log-level: | Logging level for Query. |
Possible values: | |
options: query: base-path: |
The base path for all jaeger-query HTTP routes can be set to a non-root value, for example, | /<path> |
Sample Query configuration
apiVersion: jaegertracing.io/v1 kind: "Jaeger" metadata: name: "my-jaeger" spec: strategy: allInOne allInOne: options: log-level: debug query: base-path: /jaeger
3.2.5.8. Ingester configuration options
Ingester is a service that reads from a Kafka topic and writes to the Elasticsearch storage backend. If you are using the allInOne
or production
deployment strategies, you do not need to configure the Ingester service.
Parameter | Description | Values |
---|---|---|
spec: ingester: options: {} | Configuration options that define the Ingester service. | |
options: deadlockInterval: |
Specifies the interval, in seconds or minutes, that the Ingester must wait for a message before terminating. The deadlock interval is disabled by default (set to |
Minutes and seconds, for example, |
options: kafka: consumer: topic: |
The |
Label for the consumer. For example, |
options: kafka: consumer: brokers: | Identifies the Kafka configuration used by the Ingester to consume the messages. |
Label for the broker, for example, |
options: log-level: | Logging level for the Ingester. |
Possible values: |
Streaming Collector and Ingester example
apiVersion: jaegertracing.io/v1 kind: Jaeger metadata: name: simple-streaming spec: strategy: streaming collector: options: kafka: producer: topic: jaeger-spans brokers: my-cluster-kafka-brokers.kafka:9092 ingester: options: kafka: consumer: topic: jaeger-spans brokers: my-cluster-kafka-brokers.kafka:9092 ingester: deadlockInterval: 5 storage: type: elasticsearch options: es: server-urls: http://elasticsearch:9200
3.2.6. Injecting sidecars
Red Hat OpenShift distributed tracing platform relies on a proxy sidecar within the application’s pod to provide the agent. The Red Hat OpenShift distributed tracing platform Operator can inject Agent sidecars into Deployment workloads. You can enable automatic sidecar injection or manage it manually.
3.2.6.1. Automatically injecting sidecars
The Red Hat OpenShift distributed tracing platform Operator can inject Jaeger Agent sidecars into Deployment workloads. To enable automatic injection of sidecars, add the sidecar.jaegertracing.io/inject
annotation set to either the string true
or to the distributed tracing platform instance name that is returned by running $ oc get jaegers
. When you specify true
, there should be only a single distributed tracing platform instance for the same namespace as the deployment, otherwise, the Operator cannot determine which distributed tracing platform instance to use. A specific distributed tracing platform instance name on a deployment has a higher precedence than true
applied on its namespace.
The following snippet shows a simple application that will inject a sidecar, with the agent pointing to the single distributed tracing platform instance available in the same namespace:
Automatic sidecar injection example
apiVersion: apps/v1
kind: Deployment
metadata:
name: myapp
annotations:
"sidecar.jaegertracing.io/inject": "true" 1
spec:
selector:
matchLabels:
app: myapp
template:
metadata:
labels:
app: myapp
spec:
containers:
- name: myapp
image: acme/myapp:myversion
- 1
- Set to either the string
true
or to the Jaeger instance name.
When the sidecar is injected, the agent can then be accessed at its default location on localhost
.
3.2.6.2. Manually injecting sidecars
The Red Hat OpenShift distributed tracing platform Operator can only automatically inject Jaeger Agent sidecars into Deployment workloads. For controller types other than Deployments
, such as StatefulSets`and `DaemonSets
, you can manually define the Jaeger agent sidecar in your specification.
The following snippet shows the manual definition you can include in your containers section for a Jaeger agent sidecar:
Sidecar definition example for a StatefulSet
apiVersion: apps/v1 kind: StatefulSet metadata: name: example-statefulset namespace: example-ns labels: app: example-app spec: spec: containers: - name: example-app image: acme/myapp:myversion ports: - containerPort: 8080 protocol: TCP - name: jaeger-agent image: registry.redhat.io/distributed-tracing/jaeger-agent-rhel7:<version> # The agent version must match the Operator version imagePullPolicy: IfNotPresent ports: - containerPort: 5775 name: zk-compact-trft protocol: UDP - containerPort: 5778 name: config-rest protocol: TCP - containerPort: 6831 name: jg-compact-trft protocol: UDP - containerPort: 6832 name: jg-binary-trft protocol: UDP - containerPort: 14271 name: admin-http protocol: TCP args: - --reporter.grpc.host-port=dns:///jaeger-collector-headless.example-ns:14250 - --reporter.type=grpc
The agent can then be accessed at its default location on localhost.
3.3. Configuring and deploying distributed tracing data collection
The Red Hat OpenShift distributed tracing data collection Operator uses a custom resource definition (CRD) file that defines the architecture and configuration settings to be used when creating and deploying the Red Hat OpenShift distributed tracing data collection resources. You can either install the default configuration or modify the file to better suit your business requirements.
3.3.1. OpenTelemetry Collector configuration options
The Red Hat OpenShift distributed tracing data collection Operator 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 https://access.redhat.com/support/offerings/techpreview/.
The OpenTelemetry Collector consists of three components that access telemetry data:
- Receivers - A receiver, which can be push or pull based, is how data gets into the Collector. Generally, a receiver accepts data in a specified format, translates it into the internal format and passes it to processors and exporters defined in the applicable pipelines. By default, no receivers are configured. One or more receivers must be configured. Receivers may support one or more data sources.
- Processors - (Optional) Processors are run on data between being received and being exported. By default, no processors are enabled. Processors must be enabled for every data source. Not all processors support all data sources. Depending on the data source, it may be recommended that multiple processors be enabled. In addition, it is important to note that the order of processors matters.
- Exporters - An exporter, which can be push or pull based, is how you send data to one or more backends/destinations. By default, no exporters are configured. One or more exporters must be configured. Exporters may support one or more data sources. Exporters may come with default settings, but many require configuration to specify at least the destination and security settings.
You can define multiple instances of components in a custom resource YAML file. Once configured, these components must be enabled through pipelines defined in the spec.config.service
section of the YAML file. As a best practice you should only enable the components that you need.
sample OpenTelemetry collector custom resource file
apiVersion: opentelemetry.io/v1alpha1 kind: OpenTelemetryCollector metadata: name: cluster-collector namespace: tracing-system spec: mode: deployment config: | receivers: otlp: protocols: grpc: http: processors: exporters: jaeger: endpoint: jaeger-production-collector-headless.tracing-system.svc:14250 tls: ca_file: "/var/run/secrets/kubernetes.io/serviceaccount/service-ca.crt" service: pipelines: traces: receivers: [otlp] processors: [] exporters: [jaeger]
If a component is configured, but not defined within the service
section then it is not enabled.
Parameter | Description | Values | Default |
---|---|---|---|
receivers: | A receiver is how data gets into the Collector. By default, no receivers are configured. There must be at least one enabled receiver for a configuration to be considered valid. Receivers are enabled by being added to a pipeline. |
| None |
receivers: otlp: |
The | ||
processors: | Processors run on data between being received and being exported. By default, no processors are enabled. | None | |
exporters: | An exporter sends data to one or more backends/destinations. By default, no exporters are configured. There must be at least one enabled exporter for a configuration to be considered valid. Exporters are enabled by being added to a pipeline. Exporters may come with default settings, but many require configuration to specify at least the destination and security settings. |
| None |
exporters: jaeger: endpoint: |
The | ||
exporters: jaeger: tls: ca_file: | Path to the CA certificate. For a client this verifies the server certificate. For a server this verifies client certificates. If empty uses system root CA. | ||
service: pipelines: |
Components are enabled by adding them to a pipeline under | ||
service: pipelines: traces: receivers: |
You enable receivers for tracing by adding them under | None | |
service: pipelines: traces: processors: |
You enable processors for tracing by adding them under | None | |
service: pipelines: traces: exporters: |
You enable exporters for tracing by adding them under | None |
3.3.2. Validating your deployment
3.3.3. Accessing the Jaeger console
To access the Jaeger console you must have either Red Hat OpenShift Service Mesh or Red Hat OpenShift distributed tracing installed, and Red Hat OpenShift distributed tracing platform installed, configured, and deployed.
The installation process creates a route to access the Jaeger console.
If you know the URL for the Jaeger console, you can access it directly. If you do not know the URL, use the following directions.
Procedure from OpenShift console
-
Log in to the OpenShift Container Platform web console as a user with cluster-admin rights. If you use Red Hat OpenShift Dedicated, you must have an account with the
dedicated-admin
role. -
Navigate to Networking
Routes. On the Routes page, select the control plane project, for example
tracing-system
, from the Namespace menu.The Location column displays the linked address for each route.
-
If necessary, use the filter to find the
jaeger
route. Click the route Location to launch the console. - Click Log In With OpenShift.
Procedure from the CLI
Log in to the OpenShift Container Platform CLI as a user with the
cluster-admin
role. If you use Red Hat OpenShift Dedicated, you must have an account with thededicated-admin
role.$ oc login --username=<NAMEOFUSER> https://<HOSTNAME>:6443
To query for details of the route using the command line, enter the following command. In this example,
tracing-system
is the control plane namespace.$ export JAEGER_URL=$(oc get route -n tracing-system jaeger -o jsonpath='{.spec.host}')
-
Launch a browser and navigate to
https://<JAEGER_URL>
, where<JAEGER_URL>
is the route that you discovered in the previous step. - Log in using the same user name and password that you use to access the OpenShift Container Platform console.
If you have added services to the service mesh and have generated traces, you can use the filters and Find Traces button to search your trace data.
If you are validating the console installation, there is no trace data to display.
3.4. Upgrading distributed tracing
Operator Lifecycle Manager (OLM) controls the installation, upgrade, and role-based access control (RBAC) of Operators in a cluster. The OLM runs by default in OpenShift Container Platform. OLM queries for available Operators as well as upgrades for installed Operators. For more information about how OpenShift Container Platform handles upgrades, see the Operator Lifecycle Manager documentation.
During an update, the Red Hat OpenShift distributed tracing Operators upgrade the managed distributed tracing instances to the version associated with the Operator. Whenever a new version of the Red Hat OpenShift distributed tracing platform Operator is installed, all the distributed tracing platform application instances managed by the Operator are upgraded to the Operator’s version. For example, after upgrading the Operator from 1.10 installed to 1.11, the Operator scans for running distributed tracing platform instances and upgrades them to 1.11 as well.
For specific instructions on how to update the OpenShift Elasticsearch Operator, see Updating OpenShift Logging.
3.4.1. Changing the Operator channel for 2.0
Red Hat OpenShift distributed tracing 2.0.0 made the following changes:
- Renamed the Red Hat OpenShift Jaeger Operator to the Red Hat OpenShift distributed tracing platform Operator.
- Stopped support for individual release channels. Going forward, the Red Hat OpenShift distributed tracing platform Operator will only support the stable Operator channel. Maintenance channels, for example 1.24-stable, will no longer be supported by future Operators.
As part of the update to version 2.0, you must update your OpenShift Elasticsearch and Red Hat OpenShift distributed tracing platform Operator subscriptions.
Prerequisites
- The OpenShift Container Platform version is 4.6 or later.
- You have updated the OpenShift Elasticsearch Operator.
- You have backed up the Jaeger custom resource file.
-
An account with the
cluster-admin
role. If you use Red Hat OpenShift Dedicated, you must have an account with thededicated-admin
role.
If you have not already updated your OpenShift Elasticsearch Operator as described in Updating OpenShift Logging complete that update before updating your Red Hat OpenShift distributed tracing platform Operator.
For instructions on how to update the Operator channel, see Upgrading installed Operators.
3.5. Removing distributed tracing
The steps for removing Red Hat OpenShift distributed tracing from an OpenShift Container Platform cluster are as follows:
- Shut down any Red Hat OpenShift distributed tracing pods.
- Remove any Red Hat OpenShift distributed tracing instances.
- Remove the Red Hat OpenShift distributed tracing platform Operator.
- Remove the Red Hat OpenShift distributed tracing data collection Operator.
3.5.1. Removing a Red Hat OpenShift distributed tracing platform instance using the web console
When deleting an instance that uses the in-memory storage, all data is permanently lost. Data stored in a persistent storage such as Elasticsearch is not be deleted when a Red Hat OpenShift distributed tracing platform instance is removed.
Procedure
- Log in to the OpenShift Container Platform web console.
-
Navigate to Operators
Installed Operators. -
Select the name of the project where the Operators are installed from the Project menu, for example,
openshift-operators
. - Click the Red Hat OpenShift distributed tracing platform Operator.
- Click the Jaeger tab.
- Click the Options menu next to the instance you want to delete and select Delete Jaeger.
- In the confirmation message, click Delete.
3.5.2. Removing a Red Hat OpenShift distributed tracing platform instance from the CLI
Log in to the OpenShift Container Platform CLI.
$ oc login --username=<NAMEOFUSER>
To display the distributed tracing platform instances run the command:
$ oc get deployments -n <jaeger-project>
For example,
$ oc get deployments -n openshift-operators
The names of Operators have the suffix
-operator
. The following example shows two Red Hat OpenShift distributed tracing platform Operators and four distributed tracing platform instances:$ oc get deployments -n openshift-operators
You should see output similar to the following:
NAME READY UP-TO-DATE AVAILABLE AGE elasticsearch-operator 1/1 1 1 93m jaeger-operator 1/1 1 1 49m jaeger-test 1/1 1 1 7m23s jaeger-test2 1/1 1 1 6m48s tracing1 1/1 1 1 7m8s tracing2 1/1 1 1 35m
To remove an instance of distributed tracing platform, run the following command:
$ oc delete jaeger <deployment-name> -n <jaeger-project>
For example:
$ oc delete jaeger tracing2 -n openshift-operators
To verify the deletion, run the
oc get deployments
command again:$ oc get deployments -n <jaeger-project>
For example:
$ oc get deployments -n openshift-operators
You should see generated output that is similar to the following example:
NAME READY UP-TO-DATE AVAILABLE AGE elasticsearch-operator 1/1 1 1 94m jaeger-operator 1/1 1 1 50m jaeger-test 1/1 1 1 8m14s jaeger-test2 1/1 1 1 7m39s tracing1 1/1 1 1 7m59s
3.5.3. Removing the Red Hat OpenShift distributed tracing Operators
Procedure
Follow the instructions for Deleting Operators from a cluster.
- Remove the Red Hat OpenShift distributed tracing platform Operator.
- After the Red Hat OpenShift distributed tracing platform Operator has been removed, if appropriate, remove the OpenShift Elasticsearch Operator.