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Managing metrics - Monitoring | Observability | Red Hat OpenShift Service on AWS
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Managing metrics

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Understanding metrics

In Red Hat OpenShift Service on AWS, cluster components are monitored by scraping metrics exposed through service endpoints. You can also configure metrics collection for user-defined projects. Metrics enable you to monitor how cluster components and your own workloads are performing.

You can define the metrics that you want to provide for your own workloads by using Prometheus client libraries at the application level.

In Red Hat OpenShift Service on AWS, metrics are exposed through an HTTP service endpoint under the /metrics canonical name. You can list all available metrics for a service by running a curl query against http://<endpoint>/metrics. For instance, you can expose a route to the prometheus-example-app example application and then run the following to view all of its available metrics:

$ curl http://<example_app_endpoint>/metrics
Example output
# HELP http_requests_total Count of all HTTP requests
# TYPE http_requests_total counter
http_requests_total{code="200",method="get"} 4
http_requests_total{code="404",method="get"} 2
# HELP version Version information about this binary
# TYPE version gauge
version{version="v0.1.0"} 1
Additional resources
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Setting up metrics collection for user-defined projects

You can create a ServiceMonitor resource to scrape metrics from a service endpoint in a user-defined project. This assumes that your application uses a Prometheus client library to expose metrics to the /metrics canonical name.

This section describes how to deploy a sample service in a user-defined project and then create a ServiceMonitor resource that defines how that service should be monitored.

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Deploying a sample service

To test monitoring of a service in a user-defined project, you can deploy a sample service.

Prerequisites

  • You have access to the cluster as a user with the cluster-admin cluster role or as a user with administrative permissions for the namespace.

Procedure

  1. Create a YAML file for the service configuration. In this example, it is called prometheus-example-app.yaml.

  2. Add the following deployment and service configuration details to the file:

    apiVersion: v1
kind: Namespace
metadata:
  name: ns1
---
apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    app: prometheus-example-app
  name: prometheus-example-app
  namespace: ns1
spec:
  replicas: 1
  selector:
    matchLabels:
      app: prometheus-example-app
  template:
    metadata:
      labels:
        app: prometheus-example-app
    spec:
      containers:
      - image: ghcr.io/rhobs/prometheus-example-app:0.4.2
        imagePullPolicy: IfNotPresent
        name: prometheus-example-app
---
apiVersion: v1
kind: Service
metadata:
  labels:
    app: prometheus-example-app
  name: prometheus-example-app
  namespace: ns1
spec:
  ports:
  - port: 8080
    protocol: TCP
    targetPort: 8080
    name: web
  selector:
    app: prometheus-example-app
  type: ClusterIP

    This configuration deploys a service named prometheus-example-app in the user-defined ns1 project. This service exposes the custom version metric.

  3. Apply the configuration to the cluster:

    $ oc apply -f prometheus-example-app.yaml

    It takes some time to deploy the service.

  4. You can check that the pod is running:

    $ oc -n ns1 get pod
    Example output
    NAME                                      READY     STATUS    RESTARTS   AGE
prometheus-example-app-7857545cb7-sbgwq   1/1       Running   0          81m
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Specifying how a service is monitored

To use the metrics exposed by your service, you must configure Red Hat OpenShift Service on AWS monitoring to scrape metrics from the /metrics endpoint. You can do this using a ServiceMonitor custom resource definition (CRD) that specifies how a service should be monitored, or a PodMonitor CRD that specifies how a pod should be monitored. The former requires a Service object, while the latter does not, allowing Prometheus to directly scrape metrics from the metrics endpoint exposed by a pod.

This procedure shows you how to create a ServiceMonitor resource for a service in a user-defined project.

Prerequisites

  • You have access to the cluster as a user with the dedicated-admin role or the monitoring-edit role.

  • For this example, you have deployed the prometheus-example-app sample service in the ns1 project.

    The prometheus-example-app sample service does not support TLS authentication.
Procedure

  1. Create a new YAML configuration file named example-app-service-monitor.yaml.

  2. Add a ServiceMonitor resource to the YAML file. The following example creates a service monitor named prometheus-example-monitor to scrape metrics exposed by the prometheus-example-app service in the ns1 namespace:

    apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
  name: prometheus-example-monitor
  namespace: ns1 (1)
spec:
  endpoints:
  - interval: 30s
    port: web (2)
    scheme: http
  selector: (3)
    matchLabels:
      app: prometheus-example-app
    1 Specify a user-defined namespace where your service runs.
    2 Specify endpoint ports to be scraped by Prometheus.
    3 Configure a selector to match your service based on its metadata labels.

    A ServiceMonitor resource in a user-defined namespace can only discover services in the same namespace. That is, the namespaceSelector field of the ServiceMonitor resource is always ignored.

  3. Apply the configuration to the cluster:

    $ oc apply -f example-app-service-monitor.yaml

    It takes some time to deploy the ServiceMonitor resource.

  4. Verify that the ServiceMonitor resource is running:

    $ oc -n <namespace> get servicemonitor
    Example output
    NAME                         AGE
prometheus-example-monitor   81m

Example service endpoint authentication settings

You can configure authentication for service endpoints for user-defined project monitoring by using ServiceMonitor and PodMonitor custom resource definitions (CRDs).

The following samples show different authentication settings for a ServiceMonitor resource. Each sample shows how to configure a corresponding secret object that contains authentication credentials and other relevant settings.

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Sample YAML authentication with a bearer token

The following sample shows bearer token settings for a secret object named example-bearer-auth in the ns1 namespace:

Example bearer token secret
apiVersion: v1
kind: secret
metadata:
  name: example-bearer-auth
  namespace: ns1
stringData:
  token: <authentication_token> (1)
1 Specify an authentication token.

The following sample shows bearer token authentication settings for a ServiceMonitor CRD. The example uses a secret object named example-bearer-auth:

Example bearer token authentication settings
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
  name: prometheus-example-monitor
  namespace: ns1
spec:
  endpoints:
  - authorization:
      credentials:
        key: token (1)
        name: example-bearer-auth (2)
    port: web
  selector:
    matchLabels:
      app: prometheus-example-app
1 The key that contains the authentication token in the specified secret object.
2 The name of the secret object that contains the authentication credentials.

Do not use bearerTokenFile to configure bearer token. If you use the bearerTokenFile configuration, the ServiceMonitor resource is rejected.

Sample YAML for Basic authentication

The following sample shows Basic authentication settings for a secret object named example-basic-auth in the ns1 namespace:

Example Basic authentication secret
apiVersion: v1
kind: secret
metadata:
  name: example-basic-auth
  namespace: ns1
stringData:
  user: <basic_username> (1)
  password: <basic_password>  (2)
1 Specify a username for authentication.
2 Specify a password for authentication.

The following sample shows Basic authentication settings for a ServiceMonitor CRD. The example uses a secret object named example-basic-auth:

Example Basic authentication settings
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
  name: prometheus-example-monitor
  namespace: ns1
spec:
  endpoints:
  - basicAuth:
      username:
        key: user (1)
        name: example-basic-auth (2)
      password:
        key: password (3)
        name: example-basic-auth (2)
    port: web
  selector:
    matchLabels:
      app: prometheus-example-app
1 The key that contains the username in the specified secret object.
2 The name of the secret object that contains the Basic authentication.
3 The key that contains the password in the specified secret object.

Sample YAML authentication with OAuth 2.0

The following sample shows OAuth 2.0 settings for a secret object named example-oauth2 in the ns1 namespace:

Example OAuth 2.0 secret
apiVersion: v1
kind: secret
metadata:
  name: example-oauth2
  namespace: ns1
stringData:
  id: <oauth2_id> (1)
  secret: <oauth2_secret> (2)
1 Specify an Oauth 2.0 ID.
2 Specify an Oauth 2.0 secret.

The following sample shows OAuth 2.0 authentication settings for a ServiceMonitor CRD. The example uses a secret object named example-oauth2:

Example OAuth 2.0 authentication settings
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
  name: prometheus-example-monitor
  namespace: ns1
spec:
  endpoints:
  - oauth2:
      clientId:
        secret:
          key: id (1)
          name: example-oauth2 (2)
      clientsecret:
        key: secret (3)
        name: example-oauth2 (2)
      tokenUrl: https://example.com/oauth2/token (4)
    port: web
  selector:
    matchLabels:
      app: prometheus-example-app
1 The key that contains the OAuth 2.0 ID in the specified secret object.
2 The name of the secret object that contains the OAuth 2.0 credentials.
3 The key that contains the OAuth 2.0 secret in the specified secret object.
4 The URL used to fetch a token with the specified clientId and clientsecret.
Additional resources
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Querying metrics

The Red Hat OpenShift Service on AWS monitoring dashboard enables you to run Prometheus Query Language (PromQL) queries to examine metrics visualized on a plot. This functionality provides information about the state of a cluster and any user-defined workloads that you are monitoring.

As a dedicated-admin, you can query one or more namespaces at a time for metrics about user-defined projects.

As a developer, you must specify a project name when querying metrics. You must have the required privileges to view metrics for the selected project.

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Querying metrics for all projects as a cluster administrator

As a dedicated-admin or as a user with view permissions for all projects, you can access metrics for all default Red Hat OpenShift Service on AWS and user-defined projects in the Metrics UI.

Only dedicated administrators have access to the third-party UIs provided with Red Hat OpenShift Service on AWS monitoring.
Prerequisites

  • You have access to the cluster as a user with the dedicated-admin role or with view permissions for all projects.

  • You have installed the OpenShift CLI (oc).

Procedure

  1. From the Administrator perspective in the Red Hat OpenShift Service on AWS web console, select Observe → Metrics.

  2. To add one or more queries, do any of the following:

    Option Description

    Create a custom query.

    Add your Prometheus Query Language (PromQL) query to the Expression field.

    As you type a PromQL expression, autocomplete suggestions appear in a drop-down list. These suggestions include functions, metrics, labels, and time tokens. You can use the keyboard arrows to select one of these suggested items and then press Enter to add the item to your expression. You can also move your mouse pointer over a suggested item to view a brief description of that item.

    Add multiple queries.

    Select Add query.

    Duplicate an existing query.

    Select the Options menu kebab next to the query, then choose Duplicate query.

    Disable a query from being run.

    Select the Options menu kebab next to the query and choose Disable query.

  3. To run queries that you created, select Run queries. The metrics from the queries are visualized on the plot. If a query is invalid, the UI shows an error message.

    Queries that operate on large amounts of data might time out or overload the browser when drawing time series graphs. To avoid this, select Hide graph and calibrate your query using only the metrics table. Then, after finding a feasible query, enable the plot to draw the graphs.

    By default, the query table shows an expanded view that lists every metric and its current value. You can select ˅ to minimize the expanded view for a query.

  4. Optional: The page URL now contains the queries you ran. To use this set of queries again in the future, save this URL.

  5. Explore the visualized metrics. Initially, all metrics from all enabled queries are shown on the plot. You can select which metrics are shown by doing any of the following:

    Option Description

    Hide all metrics from a query.

    Click the Options menu kebab for the query and click Hide all series.

    Hide a specific metric.

    Go to the query table and click the colored square near the metric name.

    Zoom into the plot and change the time range.

    Either:

    • Visually select the time range by clicking and dragging on the plot horizontally.

    • Use the menu in the left upper corner to select the time range.

    Reset the time range.

    Select Reset zoom.

    Display outputs for all queries at a specific point in time.

    Hold the mouse cursor on the plot at that point. The query outputs will appear in a pop-up box.

    Hide the plot.

    Select Hide graph.
Additional resources
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Querying metrics for user-defined projects as a developer

You can access metrics for a user-defined project as a developer or as a user with view permissions for the project.

In the Developer perspective, the Metrics UI includes some predefined CPU, memory, bandwidth, and network packet queries for the selected project. You can also run custom Prometheus Query Language (PromQL) queries for CPU, memory, bandwidth, network packet and application metrics for the project.

Developers can only use the Developer perspective and not the Administrator perspective. As a developer, you can only query metrics for one project at a time. Developers cannot access the third-party UIs provided with Red Hat OpenShift Service on AWS monitoring.
Prerequisites

  • You have access to the cluster as a developer or as a user with view permissions for the project that you are viewing metrics for.

  • You have enabled monitoring for user-defined projects.

  • You have deployed a service in a user-defined project.

  • You have created a ServiceMonitor custom resource definition (CRD) for the service to define how the service is monitored.

Procedure

  1. From the Developer perspective in the Red Hat OpenShift Service on AWS web console, select Observe → Metrics.

  2. Select the project that you want to view metrics for in the Project: list.

  3. Select a query from the Select query list, or create a custom PromQL query based on the selected query by selecting Show PromQL. The metrics from the queries are visualized on the plot.

    In the Developer perspective, you can only run one query at a time.

  4. Explore the visualized metrics by doing any of the following:

    Option Description

    Zoom into the plot and change the time range.

    Either:

    • Visually select the time range by clicking and dragging on the plot horizontally.

    • Use the menu in the left upper corner to select the time range.

    Reset the time range.

    Select Reset zoom.

    Display outputs for all queries at a specific point in time.

    Hold the mouse cursor on the plot at that point. The query outputs appear in a pop-up box.
Additional resources
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Getting detailed information about a metrics target

In the Administrator perspective in the Red Hat OpenShift Service on AWS web console, you can use the Metrics targets page to view, search, and filter the endpoints that are currently targeted for scraping, which helps you to identify and troubleshoot problems. For example, you can view the current status of targeted endpoints to see when Red Hat OpenShift Service on AWS Monitoring is not able to scrape metrics from a targeted component.

The Metrics targets page shows targets for user-defined projects.

Prerequisites

  • You have access to the cluster as a user with the dedicated-admin role.

Procedure

  1. In the Administrator perspective, select Observe → Targets. The Metrics targets page opens with a list of all service endpoint targets that are being scraped for metrics.

    This page shows details about targets for default Red Hat OpenShift Service on AWS and user-defined projects. This page lists the following information for each target:

    • Service endpoint URL being scraped

    • ServiceMonitor component being monitored

    • The up or down status of the target

    • Namespace

    • Last scrape time

    • Duration of the last scrape

  2. Optional: The list of metrics targets can be long. To find a specific target, do any of the following:

    Option Description

    Filter the targets by status and source.

    Select filters in the Filter list.

    The following filtering options are available:

    • Status filters:

      • Up. The target is currently up and being actively scraped for metrics.

      • Down. The target is currently down and not being scraped for metrics.

    • Source filters:

      • Platform. Platform-level targets relate only to default Red Hat OpenShift Service on AWS projects. These projects provide core Red Hat OpenShift Service on AWS functionality.

      • User. User targets relate to user-defined projects. These projects are user-created and can be customized.

    Search for a target by name or label.

    Enter a search term in the Text or Label field next to the search box.

    Sort the targets.

    Click one or more of the Endpoint Status, Namespace, Last Scrape, and Scrape Duration column headers.

  3. Click the URL in the Endpoint column for a target to navigate to its Target details page. This page provides information about the target, including the following:

    • The endpoint URL being scraped for metrics

    • The current Up or Down status of the target

    • A link to the namespace

    • A link to the ServiceMonitor details

    • Labels attached to the target

    • The most recent time that the target was scraped for metrics