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The {OTELOperator} automatically creates a service named `<instance_name>-collector-monitoring` that exposes the Collector's internal metrics. This service listens on port `8888` by default.
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You can use these metrics for monitoring the Collector's performance, resource consumption, and other internal behaviors. You can also use a Prometheus instance or another monitoring tool to scrape these metrics from the mentioned `<instance_name>-collector-monitoring` service.
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[NOTE]
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====
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When the `spec.observability.metrics.enableMetrics` field in the `OpenTelemetryCollector` custom resource (CR) is set to `true`, the `OpenTelemetryCollector` CR automatically creates a Prometheus `ServiceMonitor` or `PodMonitor` CR to enable Prometheus to scrape your metrics.
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====
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.Prerequisites
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* Monitoring for user-defined projects is enabled in the cluster.
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.Procedure
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* To enable metrics of an OpenTelemetry Collector instance, set the `spec.observability.metrics.enableMetrics` field to `true`:
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[source,yaml]
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----
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apiVersion: opentelemetry.io/v1beta1
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kind: OpenTelemetryCollector
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metadata:
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name: <name>
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spec:
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observability:
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metrics:
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enableMetrics: true
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----
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.Verification
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You can use the *Administrator* view of the web console to verify successful configuration:
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. Go to *Observe* -> *Targets*.
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. Filter by *Source: User*.
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. Check that the *ServiceMonitors* or *PodMonitors* in the `opentelemetry-collector-<instance_name>` format have the *Up* status.
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.Additional resources
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* link:https://docs.redhat.com/en/documentation/monitoring_stack_for_red_hat_openshift/latest/html-single/configuring_user_workload_monitoring/index#enabling-monitoring-for-user-defined-projects-uwm_preparing-to-configure-the-monitoring-stack-uwm[Enabling monitoring for user-defined projects]
As a cluster administrator, you can configure the OpenTelemetry Collector custom resource (CR) to perform the following tasks:
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* Create a Prometheus `ServiceMonitor` CR for scraping the Collector’s pipeline metrics and the enabled Prometheus exporters.
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* Configure the Prometheus receiver to scrape metrics from the in-cluster monitoring stack.
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[role="_abstract"]
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You can use the OpenTelemetry Collector custom resource (CR) to configure the Prometheus receiver to scrape metrics from the in-cluster monitoring stack or to configure a Prometheus ServiceMonitor CR for scraping the Collector pipeline metrics and the enabled Prometheus exporters.
Installing the {OTELShortName} involves the following steps:
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. Installing the {OTELOperator}.
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. Creating a namespace for an OpenTelemetry Collector instance.
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. Creating an `OpenTelemetryCollector` custom resource to deploy the OpenTelemetry Collector instance.
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[role="_abstract"]
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Installing the {otel} involves installing the {OTelOperator}, creating a namespace for an OpenTelemetry Collector instance, and creating an `OpenTelemetryCollector` custom resource to deploy the OpenTelemetry Collector instance.
To schedule the OpenTelemetry pods on dedicated nodes, see link:https://access.redhat.com/solutions/7040771[How to deploy the different OpenTelemetry components on infra nodes using nodeSelector and tolerations in OpenShift 4]
If you are already using the {JaegerName} for your applications, you can migrate to the {OTELName}, which is based on the link:https://opentelemetry.io/[OpenTelemetry] open-source project.
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The {OTELShortName} provides a set of APIs, libraries, agents, and instrumentation to facilitate observability in distributed systems. The OpenTelemetry Collector in the {OTELShortName} can ingest the Jaeger protocol, so you do not need to change the SDKs in your applications.
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Migration from the {JaegerShortName} to the {OTELShortName} requires configuring the OpenTelemetry Collector and your applications to report traces seamlessly. You can migrate sidecar and sidecarless deployments.
Copy file name to clipboardExpand all lines: modules/otel-about-rn.adoc
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= About this release
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[role="_abstract"]
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{OTELName} 3.9 is provided through the link:https://catalog.redhat.com/software/containers/rhosdt/opentelemetry-operator-bundle/615618406feffc5384e84400/history[{OTELOperator} 0.144.0] and based on the open source link:https://opentelemetry.io/docs/collector/[OpenTelemetry] release 0.144.0.
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The {otel} 3.9 is available through the link:https://catalog.redhat.com/software/containers/rhosdt/opentelemetry-operator-bundle/615618406feffc5384e84400/history[{OTelOperator} 0.144.0] and based on the open source link:https://opentelemetry.io/docs/collector/[OpenTelemetry] release 0.144.0.
Copy file name to clipboardExpand all lines: modules/otel-autoinstrumentation.adoc
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:_mod-docs-content-type: CONCEPT
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[id="otel-autoinstrumentation_{context}"]
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= Auto-instrumentation in the {OTELOperator}
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= Auto-instrumentation in the {OTelOperator}
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Auto-instrumentation in the {OTELOperator} can automatically instrument an application without manual code changes. Developers and administrators can monitor applications with minimal effort and changes to the existing codebase.
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[role="_abstract"]
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Auto-instrumentation in the {OTelOperator} can automatically instrument an application without manual code changes. Developers and administrators can monitor applications with minimal effort and changes to the existing codebase.
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Auto-instrumentation runs as follows:
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. The {OTELOperator} injects an init-container, or a sidecar container for Go, to add the instrumentation libraries for the programming language of the instrumented application.
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. The {OTelOperator} injects an init-container, or a sidecar container for Go, to add the instrumentation libraries for the programming language of the instrumented application.
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. The {OTELOperator} sets the required environment variables in the application's runtime environment. These variables configure the auto-instrumentation libraries to collect traces, metrics, and logs and send them to the appropriate OpenTelemetry Collector or another telemetry backend.
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. The {OTelOperator} sets the required environment variables in the application's runtime environment. These variables configure the auto-instrumentation libraries to collect traces, metrics, and logs and send them to the appropriate OpenTelemetry Collector or another telemetry backend.
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. The injected libraries automatically instrument your application by connecting to known frameworks and libraries, such as web servers or database clients, to collect telemetry data. The source code of the instrumented application is not modified.
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