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Added Metering docs for OpenShift Serverless
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abrennan
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openshift-cherrypick-robot
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@@ -1244,6 +1244,9 @@ Topics:
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### Monitoring
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- Name: Monitoring OpenShift Serverless components
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File: monitoring-serverless
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### Metering
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- Name: Using metering with OpenShift Serverless
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File: serverless-metering
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### Cluster Logging
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- Name: Cluster logging with OpenShift Serverless
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File: cluster-logging-serverless
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71
modules/serverless-metering-datasources.adoc
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71
modules/serverless-metering-datasources.adoc
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// Module included in the following assemblies:
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// serverless-metering.adoc
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[id="datasources-metering-serverless_{context}"]
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= Datasources for Knative Serving metering
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The following `ReportDataSources` are examples of how Knative Serving can be used with {product-title} metering.
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[id="knative-service-cpu-usage-ds_{context}"]
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== Datasource for CPU usage in Knative Serving
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This datasource provides the accumulated CPU seconds used per Knative service over the report time period.
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.YAML file
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[source, yaml]
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----
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apiVersion: metering.openshift.io/v1alpha1
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kind: ReportDataSource
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metadata:
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name: knative-service-cpu-usage
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spec:
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prometheusMetricsImporter:
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query: >
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sum
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by(namespace,
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label_serving_knative_dev_service,
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label_serving_knative_dev_revision)
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(
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label_replace(rate(container_cpu_usage_seconds_total{container_name!="POD",container_name!="",pod_name!=""}[1m]), "pod", "$1", "pod_name", "(.*)")
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*
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on(pod, namespace)
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group_left(label_serving_knative_dev_service, label_serving_knative_dev_revision)
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kube_pod_labels{label_serving_knative_dev_service!=""}
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)
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----
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[id="knative-service-memory-usage-ds_{context}"]
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== Datasource for memory usage in Knative Serving
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This datasource provides the average memory consumption per Knative service over the report time period.
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.YAML file
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[source, yaml]
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----
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apiVersion: metering.openshift.io/v1alpha1
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kind: ReportDataSource
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metadata:
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name: knative-service-memory-usage
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spec:
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prometheusMetricsImporter:
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query: >
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sum
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by(namespace,
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label_serving_knative_dev_service,
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label_serving_knative_dev_revision)
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(
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label_replace(container_memory_usage_bytes{container_name!="POD", container_name!="",pod_name!=""}, "pod", "$1", "pod_name", "(.*)")
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*
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on(pod, namespace)
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group_left(label_serving_knative_dev_service, label_serving_knative_dev_revision)
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kube_pod_labels{label_serving_knative_dev_service!=""}
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)
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----
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[id="applying-datasources-knative_{context}"]
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== Applying Datasources for Knative Serving metering
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You can apply the `ReportDataSources` by using the following command:
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----
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$ oc apply -f <datasource-name>.yaml
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----
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.Example
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----
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$ oc apply -f knative-service-memory-usage.yaml
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----
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127
modules/serverless-metering-queries.adoc
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127
modules/serverless-metering-queries.adoc
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// Module included in the following assemblies:
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// serverless-metering.adoc
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[id="queries-metering-serverless_{context}"]
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= Queries for Knative Serving metering
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The following `ReportQuery` resources reference the example `DataSources` provided.
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[id="knative-service-cpu-usage-query_{context}"]
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== Query for CPU usage in Knative Serving
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.YAML file
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[source, yaml]
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----
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apiVersion: metering.openshift.io/v1alpha1
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kind: ReportQuery
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metadata:
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name: knative-service-cpu-usage
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spec:
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inputs:
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- name: ReportingStart
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type: time
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- name: ReportingEnd
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type: timeq
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- default: knative-service-cpu-usage
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name: KnativeServiceCpuUsageDataSource
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type: ReportDataSource
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columns:
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- name: period_start
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type: timestamp
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unit: date
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- name: period_end
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type: timestamp
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unit: date
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- name: namespace
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type: varchar
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unit: kubernetes_namespace
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- name: service
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type: varchar
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- name: data_start
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type: timestamp
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unit: date
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- name: data_end
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type: timestamp
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unit: date
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- name: service_cpu_seconds
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type: double
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unit: cpu_core_seconds
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query: |
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SELECT
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timestamp '{| default .Report.ReportingStart .Report.Inputs.ReportingStart| prestoTimestamp |}' AS period_start,
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timestamp '{| default .Report.ReportingEnd .Report.Inputs.ReportingEnd | prestoTimestamp |}' AS period_end,
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labels['namespace'] as project,
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labels['label_serving_knative_dev_service'] as service,
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min("timestamp") as data_start,
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max("timestamp") as data_end,
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sum(amount * "timeprecision") AS service_cpu_seconds
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FROM {| dataSourceTableName .Report.Inputs.KnativeServiceCpuUsageDataSource |}
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WHERE "timestamp" >= timestamp '{| default .Report.ReportingStart .Report.Inputs.ReportingStart | prestoTimestamp |}'
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AND "timestamp" < timestamp '{| default .Report.ReportingEnd .Report.Inputs.ReportingEnd | prestoTimestamp |}'
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GROUP BY labels['namespace'],labels['label_serving_knative_dev_service']
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----
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[id="knative-service-memory-usage-query_{context}"]
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== Query for memory usage in Knative Serving
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.YAML file
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[source, yaml]
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----
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apiVersion: metering.openshift.io/v1alpha1
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kind: ReportQuery
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metadata:
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name: knative-service-memory-usage
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spec:
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inputs:
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- name: ReportingStart
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type: time
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- name: ReportingEnd
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type: timeq
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- default: knative-service-memory-usage
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name: KnativeServiceMemoryUsageDataSource
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type: ReportDataSource
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columns:
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- name: period_start
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type: timestamp
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unit: date
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- name: period_end
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type: timestamp
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unit: date
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- name: namespace
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type: varchar
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unit: kubernetes_namespace
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- name: service
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type: varchar
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- name: data_start
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type: timestamp
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unit: date
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- name: data_end
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type: timestamp
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unit: date
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- name: service_usage_memory_byte_seconds
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type: double
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unit: bytes_seconds
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query: |
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SELECT
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timestamp '{| default .Report.ReportingStart .Report.Inputs.ReportingStart| prestoTimestamp |}' AS period_start,
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timestamp '{| default .Report.ReportingEnd .Report.Inputs.ReportingEnd | prestoTimestamp |}' AS period_end,
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labels['namespace'] as project,
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labels['label_serving_knative_dev_service'] as service,
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min("timestamp") as data_start,
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max("timestamp") as data_end,
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sum(amount * "timeprecision") AS service_usage_memory_byte_seconds
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FROM {| dataSourceTableName .Report.Inputs.KnativeServiceMemoryUsageDataSource |}
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WHERE "timestamp" >= timestamp '{| default .Report.ReportingStart .Report.Inputs.ReportingStart | prestoTimestamp |}'
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AND "timestamp" < timestamp '{| default .Report.ReportingEnd .Report.Inputs.ReportingEnd | prestoTimestamp |}'
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GROUP BY labels['namespace'],labels['label_serving_knative_dev_service']
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----
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[id="applying-queries-knative_{context}"]
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== Applying Queries for Knative Serving metering
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You can apply the `ReportQuery` by using the following command:
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----
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$ oc apply -f <query-name>.yaml
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----
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.Example
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----
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$ oc apply -f knative-service-memory-usage.yaml
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----
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40
modules/serverless-metering-reports.adoc
Normal file
40
modules/serverless-metering-reports.adoc
Normal file
@@ -0,0 +1,40 @@
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// Module included in the following assemblies:
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// serverless-metering.adoc
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[id="reports-metering-serverless_{context}"]
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= Metering reports for Knative Serving
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You can run metering reports against Knative Serving by creating `Report` resources.
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Before you run a report, you must modify the input parameter within the `Report` resource to specify the start and end dates of the reporting period.
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.YAML file
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[source, yaml]
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----
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apiVersion: metering.openshift.io/v1alpha1
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kind: Report
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metadata:
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name: knative-service-cpu-usage
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spec:
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reportingStart: '2019-06-01T00:00:00Z' <1>
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reportingEnd: '2019-06-30T23:59:59Z' <2>
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query: knative-service-cpu-usage <3>
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runImmediately: true
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----
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<1> Start date of the report, in ISO 8601 format.
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<2> End date of the report, in ISO 8601 format.
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<3> Either `knative-service-cpu-usage` for CPU usage report or `knative-service-memory-usage` for a memory usage report.
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[id="reports-metering-serverless-run_{context}"]
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== Running a metering report
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Once you have provided the input parameters, you can run the report using the command:
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----
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$ oc apply -f <report-name>.yml
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----
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You can then check the report as shown in the following example:
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----
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$ kubectl get report
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NAME QUERY SCHEDULE RUNNING FAILED LAST REPORT TIME AGE
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knative-service-cpu-usage knative-service-cpu-usage Finished 2019-06-30T23:59:59Z 10h
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----
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17
serverless/serverless-metering.adoc
Normal file
17
serverless/serverless-metering.adoc
Normal file
@@ -0,0 +1,17 @@
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[id="metering-serverless"]
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= Using metering with {ServerlessProductName}
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include::modules/common-attributes.adoc[]
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include::modules/serverless-document-attributes.adoc[]
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:context: metering-serverless
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As an {product-title} cluster administrator, you can use metering to analyze what is happening in your {ServerlessProductName} cluster.
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For more information about metering on {product-title}, see xref:../metering/metering-about-metering.adoc[About metering].
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[id="installing-metering-serverless_{context}"]
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== Installing metering
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For information about installing metering on {product-title}, see xref:../metering/metering-installing-metering.adoc[Installing Metering].
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include::modules/serverless-metering-datasources.adoc[leveloffset=+1]
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include::modules/serverless-metering-queries.adoc[leveloffset=+1]
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include::modules/serverless-metering-reports.adoc[leveloffset=+1]
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