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Trace data contains rich information, and the data is normalized across instrumented languages and frameworks.
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Therefore, request rate, error, and duration (RED) metrics can be extracted from traces.
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The metrics can be visualized in Jaeger console in the *Monitor* tab.
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You can have the request rate, error, and duration (RED) metrics extracted from traces and visualized through the Jaeger Console in the *Monitor* tab of the {product-title} web console. The metrics are derived from spans in the OpenTelemetry Collector that are scraped from the Collector by Prometheus, which you can deploy in your user-workload monitoring stack. The Jaeger UI queries these metrics from the Prometheus endpoint and visualizes them.
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The metrics are derived from spans in the OpenTelemetry Collector that are scraped from the Collector by the Prometheus deployed in the user-workload monitoring stack.
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The Jaeger UI queries these metrics from the Prometheus endpoint and visualizes them.
* You have configured the permissions and tenants for the {TempoShortName}. For more information, see "Configuring the permissions and tenants".
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The OpenTelemetry Collector requires configuration of the `spanmetrics` connector that derives metrics from traces and exports the metrics in the Prometheus format.
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.Procedure
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.OpenTelemetry Collector custom resource for span RED
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. In the `OpenTelemetryCollector` custom resource of the OpenTelemetry Collector, enable the Spanmetrics Connector (`spanmetrics`), which derives metrics from traces and exports the metrics in the Prometheus format.
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.Example `OpenTelemetryCollector` custom resource for span RED
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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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apiVersion: opentelemetry.io/v1alpha1
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metadata:
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name: otel
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spec:
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endpoint: 0.0.0.0:8889
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add_metric_suffixes: false
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resource_to_telemetry_conversion:
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enabled: true # by default resource attributes are dropped
The `TempoStack` custom resource must specify the following: the *Monitor* tab is enabled, and the Prometheus endpoint is set to the Thanos querier service to query the data from the user-defined monitoring stack.
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<5> The resource attributes are dropped by default.
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<6> The Spanmetrics connector is configured as exporter in traces pipeline.
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<7> The Spanmetrics connector is configured as receiver in metrics pipeline.
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.TempoStack custom resource with the enabled Monitor tab
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. In the `TempoStack` custom resource, enable the *Monitor* tab and set the Prometheus endpoint to the Thanos querier service to query the data from your user-defined monitoring stack.
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.Example `TempoStack` custom resource with the enabled Monitor tab
<1> Enables the monitoring tab in the Jaeger console.
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<2> The service name for Thanos Querier from user-workload monitoring.
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<3> Optional: The metrics namespace on which the Jaeger query retrieves the Prometheus metrics. Include this line only if you are using an OpenTelemetry Collector version earlier than 0.109.0. If you are using an OpenTelemetry Collector version 0.109.0 or later, omit this line.
The metrics generated by the `spanmetrics` connector are usable with alerting rules. For example, for alerts about a slow service or to define service level objectives (SLOs), the connector creates a `duration_bucket` histogram and the `calls` counter metric. These metrics have labels that identify the service, API name, operation type, and other attributes.
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. Optional: Use the span RED metrics generated by the `spanmetrics` connector with alerting rules. For example, for alerts about a slow service or to define service level objectives (SLOs), the connector creates a `duration_bucket` histogram and the `calls` counter metric. These metrics have labels that identify the service, API name, operation type, and other attributes.
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.Labels of the metrics created in the `spanmetrics` connector
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[options="header"]
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[cols="a, a, a"]
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* `SPAN_KIND_INTERNAL`
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|===
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.Example `PrometheusRule` CR that defines an alerting rule for SLO when not serving 95% of requests within 2000ms on the front-end service
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.Example `PrometheusRule` custom resource that defines an alerting rule for SLO when not serving 95% of requests within 2000ms on the front-end service
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