$ curl http://<example_app_endpoint>/metrics
You can collect metrics to monitor how cluster components and your own workloads are performing.
In OpenShift Container Platform 4.7, cluster components are monitored by scraping metrics exposed through service endpoints. You can also configure metrics collection for user-defined projects.
You can define the metrics that you want to provide for your own workloads by using Prometheus client libraries at the application level.
In OpenShift Container Platform, 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 service and then run the following to view all of its available metrics:
$ curl http://<example_app_endpoint>/metrics
# 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
See the Prometheus documentation for details on Prometheus client libraries.
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.
To test monitoring of a service in a user-defined project, you can deploy a sample service.
Create a YAML file for the service configuration. In this example, it is called prometheus-example-app.yaml
.
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:0.3.0
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.
Apply the configuration to the cluster:
$ oc apply -f prometheus-example-app.yaml
It takes some time to deploy the service.
You can check that the pod is running:
$ oc -n ns1 get pod
NAME READY STATUS RESTARTS AGE
prometheus-example-app-7857545cb7-sbgwq 1/1 Running 0 81m
To use the metrics exposed by your service, you must configure OpenShift Container Platform 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.
You have access to the cluster as a user with the cluster-admin
role or the monitoring-edit
role.
You have enabled monitoring for user-defined projects.
For this example, you have deployed the prometheus-example-app
sample service in the ns1
project.
The |
Create a YAML file for the ServiceMonitor
resource configuration. In this example, the file is called example-app-service-monitor.yaml
.
Add the following ServiceMonitor
resource configuration details:
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
labels:
k8s-app: prometheus-example-monitor
name: prometheus-example-monitor
namespace: ns1
spec:
endpoints:
- interval: 30s
port: web
scheme: http
selector:
matchLabels:
app: prometheus-example-app
This defines a ServiceMonitor
resource that scrapes the metrics exposed by the prometheus-example-app
sample service, which includes the version
metric.
A |
Apply the configuration to the cluster:
$ oc apply -f example-app-service-monitor.yaml
It takes some time to deploy the ServiceMonitor
resource.
You can check that the ServiceMonitor
resource is running:
$ oc -n ns1 get servicemonitor
NAME AGE
prometheus-example-monitor 81m
The OpenShift Container Platform 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 cluster administrator, you can query metrics for all core OpenShift Container Platform and 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.
As a cluster administrator or as a user with view permissions for all projects, you can access metrics for all default OpenShift Container Platform and user-defined projects in the Metrics UI.
Only cluster administrators have access to the third-party UIs provided with OpenShift Container Platform Monitoring. |
You have access to the cluster as a user with the cluster-admin
role or with view permissions for all projects.
You have installed the OpenShift CLI (oc
).
In the Administrator perspective within the OpenShift Container Platform web console, select Monitoring → Metrics.
Select Insert Metric at Cursor to view a list of predefined queries.
To create a custom query, add your Prometheus Query Language (PromQL) query to the Expression field.
To add multiple queries, select Add Query.
To delete a query, select next to the query, then choose Delete query.
To disable a query from being run, select next to the query and choose Disable query.
Select Run Queries to run the queries that you have created. 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. |
Optional: The page URL now contains the queries you ran. To use this set of queries again in the future, save this URL.
See the Prometheus query documentation for more information about creating PromQL queries.
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 OpenShift Container Platform monitoring that are for core platform components. Instead, use the Metrics UI for your user-defined project. |
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.
From the Developer perspective in the OpenShift Container Platform web console, select Monitoring → Metrics.
Select the project that you want to view metrics for in the Project: list.
Choose a query from the Select Query list, or run a custom PromQL query by selecting Show PromQL.
In the Developer perspective, you can only run one query at a time. |
See the Prometheus query documentation for more information about creating PromQL queries.
See the Querying metrics for user-defined projects as a developer for details on accessing non-cluster metrics as a developer or a privileged user
After running the queries, the metrics are displayed on an interactive plot. The X-axis in the plot represents time and the Y-axis represents metrics values. Each metric is shown as a colored line on the graph. You can manipulate the plot interactively and explore the metrics.
In the Administrator perspective:
Initially, all metrics from all enabled queries are shown on the plot. You can select which metrics are shown.
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. |
To hide all metrics from a query, click for the query and click Hide all series.
To hide a specific metric, go to the query table and click the colored square near the metric name.
To zoom into the plot and change the time range, do one of the following:
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.
To reset the time range, select Reset Zoom.
To 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.
To hide the plot, select Hide Graph.
In the Developer perspective:
To zoom into the plot and change the time range, do one of the following:
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.
To reset the time range, select Reset Zoom.
To 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.
See the Querying metrics section on using the PromQL interface