Docs

Volcengine Kubernetes Engine

Observability

Monitoring application instances deployed in clusters

When you deploy application instances in a VKE cluster, you can use cloud-native observability to monitor the application instances. This topic describes how to monitor MySQL instances in clusters.

Background information

MySQL is a commonly used relational database. In Kubernetes, you can use the open source mysqld-exporter to monitor the running status of MySQL instances deployed in clusters.

Prerequisites

Cloud-native observability has been enabled. For details, see Enabling observability.

The target cluster has been connected by using kubectl. For details, see Connecting to clusters.

Grafana has been deployed in the cluster. For details, see Deploying Grafana in a VKE cluster and integrating Grafana with a workspace.

Procedure

Step 1: Grant permissions on the database

mysqld-exporter performs monitoring by querying status data in the target database. Therefore, you need to grant the required permissions on the corresponding database instance. You can run the following command to grant permissions to a user.

tip

We recommend that you specify the maximum number of connections for the user to prevent the database from being affected by monitoring data collection. However, this configuration may not take effect in all database versions. For example, MariaDB v10.1 does not allow you to specify the maximum number of connections.

Step 2: Create a MySQL connection string Secret

In the left navigation bar, click Cluster.

On the Cluster page, click the name of the target cluster to go to the cluster management page.

In the left navigation bar, click Configurations > Secret. On the Secret page, click Create with Yaml to configure a Secret.

apiVersion: v1
kind: Secret
metadata:
name: mysql-secret-demo # Specify a name for the Secret.
namespace: volcano-metrics # Specify a namespace for the Secret.
type: Opaque
stringData:
datasource: "user:password@tcp(ip:port)/" # Specify connection string information for the MySQL instance, including the username, password, address, and port number.

Step 3: Deploy mysql-exporter

In the left navigation bar, click Workload > Deployment. Click Create with Yaml to deploy mysql-exporter.

Step 4: Configure service discovery

In the left navigation bar, click Workload > Resource Explorer. Click Create with Yaml to configure a collection rule by using a PodMonitor.

Select Custom from the Type drop-down menu.

Edit the configurations in the Yaml box.

apiVersion: monitoring.coreos.com/v1
kind: PodMonitor
metadata:
name: mysql-exporter # Specify a name for the PodMonitor.
namespace: volcano-metrics # Specify a namespace for the PodMonitor.
labels:
volcengine.vmp: "true" # Configure PodMonitor labels to make it discoverable by prometheus-agent.
spec:
podMetricsEndpoints:
- interval: 30s
port: metric-port # Specify a name for the container port.
path: /metrics # Specify the container metric path. The default value is /metrics if it is left empty.
relabelings: # Configure metric relabeling. This can be omitted if not required.
- action: replace
sourceLabels:
- instance
regex: (.*)
targetLabel: instance
replacement: 'mysql-xxxxxx' # Specify the ID of the corresponding MySQL instance.
namespaceSelector:
matchNames:
- volcano-metrics # Specify the namespace where the container resides.
selector:
matchLabels:
app-name: mysql-exporter # Specify the container label value to locate and select the target pod.

Validating results

Run the following command to configure Grafana port mapping.

kubectl port-forward service/grafana 3000:3000 -n volcano-metrics

Open a browser in the local environment (Linux/Mac), enter localhost:3000 in the address bar to go to the Grafana login page, and then log in to Grafana by using the default username admin and password admin.

Create a MySQL dashboard to view MySQL metrics.

tip

For detailed parameters of mysql-exporter, see mysqld-exporter.

Last updated: 2026.10.23 10:41:06