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Volcengine Managed Service for Prometheus

Custom integration

Go application integration

Prometheus provides an official Go library to collect and expose monitoring data. This topic describes how to use the library to expose the Go runtime data and use Volcengine Managed Service for Prometheus (VMP) to collect and display metric data with some basic samples.

tip

For more details about Go client API documentation, refer to Prometheus Go client library.

Install dependencies

You can install the relevant dependencies by running the following go get command:

Runtime metrics

Create an HTTP service with the path /metrics. You can directly use the Handler function provided in prometheus/promhttp.

The following section shows a sample Go application, which exposes some default metric data through http://localhost:2023/metrics. The metrics include runtime, process, and build metrics.

Run the following command to start the application:

Execute the following command to view metric data during runtime:

Application layer metrics

The preceding example only exposes some basic built-in metrics. You need to add metrics at the application layer additionally.

As shown in the following example, the metric rpc_durations_seconds is exposed, which is used to collect statistics on the Remote Procedure Call (RPC) latency of the service.

Run the following command to start the application:

Execute the following command to view metric data during runtime:

From the output result, you can see the information about the rpc_durations_seconds counter, including the help documentation, type information, metric name, and current value.

Monitor the Go application

The preceding example only shows how to use the Go library of Prometheus to expose application metric data. However, the exposed metric data needs to be collected and stored through VMP for data monitoring and alerting.

Package the application

A Go application can be packaged into an image through a Dockerfile in the following format. In this way, the Go application can be deployed in a Volcengine Kubernetes Engine (VKE) cluster.

tip

The Dockerfile only serves as an example. You can modify its parameters based on your business requirements.

After the image is created, it can be uploaded to CR for use. You can also use another public cloud or self-built image registry.

tip

For the image pushing method of CR, see Pushing and pulling images with Docker.

Deploy the application

You can use the images from Container Registry to deploy applications in the VKE cluster. Procedure:

In the left navigation pane, click Cluster. In the cluster list on the right side, find the target cluster.

Click the name of the cluster to go to the cluster details page.

Click Workload > Deployment in the left navigation pane. Click Create with Yaml to deploy the application.

In the left navigation pane of the cluster details page, click Services and Ingresses > Service. On the page that appears, click Create with Yaml to configure a service for load balancing and service discovery.

Configure service discovery

After the application is deployed and works as expected, you can use ServiceMonitor to configure service discovery to allow the collector to collect the metrics of the application. The specific procedure is as follows:

In the left navigation bar, click Workload > Resource Explorer. Click Create with Yaml to configure service discovery through ServiceMonitor.

Select Custom from the Type drop-down menu.

Enter the YAML configuration in the Yamlfield.

View monitoring data

You can view metric data by using the Explore feature of VMP. For more details, refer to Querying metrics.

You can also use Grafana to read data stored in VMP and create metric dashboards.

Last updated: 2026.10.10 10:16:50