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OSDOCS-14333: adds OTEL for AI model-server metrics MicroShift
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microshift_ai/microshift-rhoai.adoc

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include::modules/microshift-rhoai-inferenceservice-ex.adoc[leveloffset=+1]
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include::modules/microshift-rhoai-export-metrics-otel.adoc[leveloffset=+2]
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include::modules/microshift-inferenceservice-more-options.adoc[leveloffset=+2]
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include::modules/microshift-rhoai-model-serving-rt-verify.adoc[leveloffset=+1]

modules/microshift-inferenceservice-more-options.adoc

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//
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// * microshift_ai/microshift-rhoai.adoc
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:_mod-docs-content-type: CONCEPT
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:_mod-docs-content-type: REFERENCE
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[id="microshift-rhoai-inferenceservice-more-options_{context}"]
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= More InferenceService CRD options
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= More InferenceService CR options
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The inference service YAML file can include many different options. For example, you can include a `resources` section that is passed first to the deployment and then to the pod, so that the model server gets access to your hardware through the device plugin.
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// Module included in the following assemblies:
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//
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// * microshift_ai/microshift-rhoai.adoc
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:_mod-docs-content-type: PROCEDURE
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[id="microshift-rhoai-export-metrics-otel_{context}"]
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= Exporting model-server metrics by using Open Telemetry
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You can export model-server metrics by using Open Telemetry if you installed the `microshift-observability` RPM for {microshift-short}.
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[NOTE]
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====
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You can alternatively get the Prometheus-format metrics of the model server by making a request on the `/metrics` endpoint. See "Getting the model-server metrics" for more information.
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====
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.Prerequisites
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* You configured the `ServingRuntimes` CR.
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* You have root user access to your machine.
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* The {oc-first} is installed.
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* You installed the `microshift-observability` RPM.
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* Your {microshift-short} Open Telemetry configuration includes the Prometheus Receiver. For more information, see link:https://docs.redhat.com/en/documentation/openshift_container_platform/4.18/html/red_hat_build_of_opentelemetry/configuring-the-collector#prometheus-receiver_otel-collector-receivers[Prometheus Receiver].
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.Procedure
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* Add the following Open Telemetry annotation to your `InferenceService` custom resource:
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.Example `InferenceService` object with Open Telemetry
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[source,yaml]
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----
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apiVersion: serving.kserve.io/v1beta1
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kind: InferenceService
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metadata:
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name: ovms-resnet50
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#...
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annotations:
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prometheus.io/scrape: "true"
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#...
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----

modules/microshift-rhoai-get-model-server-metrics.adoc

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After making a query, you can get the model server's metrics to identify bottlenecks, optimize resource allocation, and ensure efficient infrastructure utilization.
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[NOTE]
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====
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You can alternatively configure Open Telemetry for {microshift-short} to get model-server metrics. See "Adding Open Telemetry to an InferenceService custom resource" for more information.
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====
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.Prerequisites
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* The {microshift-short} cluster is running.

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