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Volcengine Managed Service for Prometheus

Volcengine Managed Service for Prometheus

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    • Volcengine Managed Service for PrometheusIntegration GuidePrometheus ecosystem integrationExporter integrationKafka exporter integration
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Exporter integration
Kafka exporter integration
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Kafka exporter integration
Volcengine Managed Service for Prometheus (VMP) monitors the operational status of Kafka by using the exporter. This topic describes how to deploy kafka-exporter in a cluster and monitor Kafka.​
Prerequisites​
  • VMP​
  • VKE​
  • A Volcano Engine root user has been created, and VKE has been activated.​
  • The VKE cluster has been integrated with VMP. For details, see VKE integration.​
  • Grafana has been deployed and integrated with the workspace.​
Procedure​
Step 1: Deploy kafka-exporter​
  1. Log in to the VKE console.​
  1. In the left navigation pane, click Cluster. In the cluster list on the right side, find the target cluster.​
  1. Click the name of the cluster to go to the cluster details page.​
  1. Click Workload > Deployment in the left navigation pane. Click Create with Yaml to deploy kafka-exporter.​
​
apiVersion: apps/v1​
kind: Deployment​
metadata: ​
name: kafka-exporter # Specify the name of the exporter.​
namespace: volcano-metrics # Specify the namespace of the exporter.​
labels: ​
app-name: kafka-exporter # Configure the labels of the exporter.​
spec: ​
replicas: 1 # Specify the number of replicas for the exporter.​
selector: ​
matchLabels: ​
app-name: kafka-exporter # Change the name based on your business requirements. It is recommended to add information about the Kafka instance.​
template: ​
metadata: ​
labels: ​
app-name: kafka-exporter # Change the name based on your business requirements. It is recommended to add information about the Kafka instance.​
spec: ​
containers: ​
- args: ​
- --kafka.server=x.x.x.x:9092 # Specify the address and port number of the Kafka instance.​
image: danielqsj/kafka-exporter:latest # Pull the exporter image from Docker Hub.​
imagePullPolicy: IfNotPresent​
name: kafka-exporter # Specify the container name.​
ports:​
- containerPort: 9308 # Specify the container port number.​
name: metric-port # Specify the container port name.​
dnsPolicy: ClusterFirst​
restartPolicy: Always​
terminationGracePeriodSeconds: 30​
​
tip​
For detailed parameters of kafka-exporter, refer to kafka-exporter.​
Step 2: Configure service discovery​
  1. Click Workload > Resource Explorer in the left navigation pane.​
  1. Click Create with Yaml to configure service discovery by using PodMonitor.​
  • Select Custom from the Type drop-down menu.​
  • Enter the YAML configuration in the Yaml field.​
​
apiVersion: monitoring.coreos.com/v1​
kind: PodMonitor​
metadata:​
name: kafka-exporter # Specify the name of PodMonitor.​
namespace: volcano-metrics # Specify the namespace of PodMonitor.​
labels: ​
volcengine.vmp: "true" # Configure the labels for PodMonitor to allow the labels to be identified by prometheus-agent.​
spec:​
podMetricsEndpoints:​
- interval: 30s​
port: metric-port # Specify the container port name of the exporter.​
path: /metrics # Specify the URI path for metric exposure. The value is /metrics by default if it is not specified.​
relabelings: # Configure metric relabeling. This parameter can be omitted if it is not required.​
- action: replace​
sourceLabels:​
- instance​
regex: (.*)​
targetLabel: instance​
replacement: 'kafka-xxxxxx' # Specify the ID of the Kafka instance.​
namespaceSelector:​
matchNames: ​
- volcano-metrics # Specify the namespace where the exporter is located.​
selector: ​
matchLabels:​
app-name: kafka-exporter # Specify the label value of the exporter to locate and select the target pod.​
​
Validate results​
  1. Execute the following command to configure Grafana port forwarding:​
​
kubectl port-forward service/grafana 3000:3000 -n volcano-metrics​
​
  1. Open a browser in your local environment (Linux/Mac), enter localhost:3000 into the address bar to go to the Grafana login interface. Use the default username admin, with the password admin, to log in. ​
  • ​alt​​
  1. After you log in to Grafana, you can create a dashboard to view the metric information of Kafka.​
  • ​alt​​
tip​
For detailed parameters of kafka-exporter, refer to kafka-exporter.​
​
Last updated: 2026.10.10 10:16:50