Connecting Kafka Exporter to AOM for Monitoring Metrics

Scenario

When using Kafka, you need to monitor their running, for example, checking the cluster status and whether messages are stacked. The Prometheus monitoring function monitors Kafka running using Exporter in the CCE container scenario. This section describes how to deploy Kafka Exporter and implement alarm access.

Constraints

You are advised to use CCE for unified Exporter management.

Prerequisites

• A CCE cluster has been created and Kafka has been installed.
• Your service has been connected for Prometheus monitoring and a CCE cluster has also been connected. For details, see Prometheus Instance for CCE.
• You have uploaded the kafka_exporter image to SoftWare Repository for Container (SWR). For details, see Uploading an Image Through a Container Engine Client.

Deploying Kafka Exporter in a CCE Cluster

1. Log in to the CCE console.
2. Click the connected cluster. The cluster management page is displayed.
3. Perform the following operations to deploy Exporter:
   1. Deploy Kafka Exporter.

      In the navigation pane, choose Workloads. In the upper right corner, click Create Workload. Then select the Deployment workload and select a desired namespace to deploy Kafka Exporter.

      The following shows the YAML used to deploy Exporter. For parameters, see kafka-exporter.

      apiVersion: apps/v1
      kind: Deployment
      metadata:
        labels:
          k8s-app: kafka-exporter # Change the name based on service requirements. You are advised to add the Kafka instance information, for example, ckafka-2vrgx9fd-kafka-exporter.
        name: kafka-exporter # Change the name based on service requirements. You are advised to add the Kafka instance information, for example, ckafka-2vrgx9fd-kafka-exporter.
        namespace: default # Namespace of an existing cluster.
      spec:
        replicas: 1
        selector:
          matchLabels:
            k8s-app: kafka-exporter # Change the name based on service requirements. You are advised to add the Kafka instance information, for example, ckafka-2vrgx9fd-kafka-exporter.
        template:
          metadata:
            labels:
              k8s-app: kafka-exporter # Change the name based on service requirements. You are advised to add the Kafka instance information, for example, ckafka-2vrgx9fd-kafka-exporter.
          spec:
            containers:
            - args:
              - --kafka.server=120.46.215.4:30092 # Address of the Kafka instance.
              image: swr.cn-north-4.myhuaweicloud.com/mall-swarm-demo/kafka-exporter:latest
              imagePullPolicy: IfNotPresent
              name: kafka-exporter
              ports:
              - containerPort: 9308
                name: metric-port # Required when you configure a collection task.
              securityContext:
                privileged: false
              terminationMessagePath: /dev/termination-log
              terminationMessagePolicy: File
            dnsPolicy: ClusterFirst
            imagePullSecrets:
            - name: default-secret
            restartPolicy: Always
            schedulerName: default-scheduler
            securityContext: {}
            terminationGracePeriodSeconds: 30
      ---
      apiVersion: v1
      kind: Service
      metadata:
        name: kafka-exporter
      spec:
        type: NodePort
        selector:
          k8s-app: kafka-exporter
        ports:
          - protocol: TCP
            nodePort: 30091
            port: 9308
            targetPort: 9308

   2. Check whether Kafka Exporter is successfully deployed.
      1. On the Deployments tab page, click the Deployment created in 3.a. In the pod list, choose More > View Logs in the Operation column. The Exporter is successfully started and its access address is exposed.
      2. Run the following commands to check whether Kafka Exporter is successfully deployed. If metric data is returned, it is successfully deployed. Perform verification using one of the following methods:
         • Log in to a cluster node and run either of the following commands:

           curl http://{Cluster IP address}:9308/metrics

           curl http://{Private IP address of any node in the cluster}:30091/metrics

         • In the instance list, choose More > Remote Login in the Operation column and run the following command:

           curl http://localhost:9308/metric

         • Access http://{Public IP address of any node in the cluster}:30091/metrics.
           Figure 1 Access address
           

Configuring a CCE Cluster Metric Collection Rule

Add PodMonitor to configure a Prometheus collection rule for monitoring the service data of applications deployed in the CCE cluster.

1. Log in to the AOM 2.0 console.
2. In the navigation pane on the left, choose Prometheus Monitoring > Instances.
3. In the instance list, click a Prometheus instance for CCE.
4. In the navigation pane on the left, choose Metric Management. On the Settings tab page, click PodMonitor.
5. Click Add PodMonitor. In the displayed dialog box, set parameters and click OK.

   In the following example, metrics are collected every 30s. Therefore, you can check the reported metrics on the AOM page about 30s later.

   apiVersion: monitoring.coreos.com/v1
   kind: PodMonitor
   metadata:
     name: kafka-exporter
     namespace: default 
   spec:
     namespaceSelector: # Select the namespace where the target Exporter pod is located.
       matchNames:
         - default # Namespace where Exporter is located.
     podMetricsEndpoints:
     - interval: 30s # Set the metric collection period.
       path: /metrics # Enter the path corresponding to Prometheus Exporter. Default: /metrics.
       port: metric-port # Enter the name of ports in the YAML file corresponding to Prometheus Exporter.
     selector: # Enter the label of the target Exporter pod.
       matchLabels:
         k8s-app: kafka-exporter

Verifying that CCE Cluster Metrics Can Be Reported to AOM

1. Log in to the AOM 2.0 console.
2. In the navigation pane on the left, choose Prometheus Monitoring > Instances.
3. Click the Prometheus instance connected to the CCE cluster. The instance details page is displayed.
4. On the Metrics tab page of the Metric Management page, select your target cluster.
5. Select job {namespace}/kafka-exporter to query custom metrics starting with kafka.

Setting a Dashboard and Alarm Rule on AOM

By setting a dashboard, you can monitor CCE cluster data on the same screen. By setting an alarm rule, you can detect cluster faults and implement warning in a timely manner.

• Setting a dashboard
  1. Log in to the AOM 2.0 console.
  2. In the navigation pane, choose Dashboard > Dashboard. On the displayed page, click Add Dashboard to add a dashboard. For details, see Creating a Dashboard.
  3. On the Dashboard page, select a Prometheus instance for CCE and click Add Graph. For details, see Adding a Graph to a Dashboard.
• Setting an alarm rule
  1. Log in to the AOM 2.0 console.
  2. In the navigation pane, choose Alarm Center > Alarm Rules.
  3. On the Prometheus Monitoring tab page, click Create Alarm Rule to create an alarm rule. For details, see Creating a Metric Alarm Rule.