Elastic Log Alerting

Learn how to create an async function to find out error logs.

This document describes how to create an async function to find out error logs.

Overview

This document uses an asynchronous function to analyze the log stream in Kafka to find out the error logs. The async function will then send alerts to Slack. The following diagram illustrates the entire workflow.

Prerequisites

Create a Kafka Server and Topic

  1. Run the following commands to install strimzi-kafka-operator in the default namespace.

    helm repo add strimzi https://strimzi.io/charts/
    helm install kafka-operator -n default strimzi/strimzi-kafka-operator
    
  2. Use the following content to create a file kafka.yaml.

    apiVersion: kafka.strimzi.io/v1beta2
    kind: Kafka
    metadata:
      name: kafka-logs-receiver
      namespace: default
    spec:
      kafka:
        version: 3.1.0
        replicas: 1
        listeners:
          - name: plain
            port: 9092
            type: internal
            tls: false
          - name: tls
            port: 9093
            type: internal
            tls: true
        config:
          offsets.topic.replication.factor: 1
          transaction.state.log.replication.factor: 1
          transaction.state.log.min.isr: 1
          default.replication.factor: 1
          min.insync.replicas: 1
          inter.broker.protocol.version: "3.1"
        storage:
          type: ephemeral
      zookeeper:
        replicas: 1
        storage:
          type: ephemeral
      entityOperator:
        topicOperator: {}
        userOperator: {}
    ---
    apiVersion: kafka.strimzi.io/v1beta2
    kind: KafkaTopic
    metadata:
      name: logs
      namespace: default
      labels:
        strimzi.io/cluster: kafka-logs-receiver
    spec:
      partitions: 10
      replicas: 1
      config:
        retention.ms: 7200000
        segment.bytes: 1073741824
    
  3. Run the following command to deploy a 1-replica Kafka server named kafka-logs-receiver and 1-replica Kafka topic named logs in the default namespace.

    kubectl apply -f kafka.yaml
    
  4. Run the following command to check pod status and wait for Kafka and Zookeeper to be up and running.

    $ kubectl get po
    NAME                                                     READY   STATUS        RESTARTS   AGE
    kafka-logs-receiver-entity-operator-57dc457ccc-tlqqs     3/3     Running       0          8m42s
    kafka-logs-receiver-kafka-0                              1/1     Running       0          9m13s
    kafka-logs-receiver-zookeeper-0                          1/1     Running       0          9m46s
    strimzi-cluster-operator-687fdd6f77-cwmgm                1/1     Running       0          11m
    
  5. Run the following commands to view the metadata of the Kafka cluster.

    # Starts a utility pod.
    $ kubectl run utils --image=arunvelsriram/utils -i --tty --rm
    # Checks metadata of the Kafka cluster.
    $ kafkacat -L -b kafka-logs-receiver-kafka-brokers:9092
    

Create a Logs Handler Function

  1. Use the following example YAML file to create a manifest logs-handler-function.yaml and modify the value of spec.image to set your own image registry address.

    apiVersion: core.openfunction.io/v1beta1
    kind: Function
    metadata:
      name: logs-async-handler
    spec:
      version: "v2.0.0"
      image: <your registry name>/logs-async-handler:latest
      imageCredentials:
        name: push-secret
      build:
        builder: openfunction/builder-go:latest
        env:
          FUNC_NAME: "LogsHandler"
          FUNC_CLEAR_SOURCE: "true"
          # Use FUNC_GOPROXY to set the goproxy
          # FUNC_GOPROXY: "https://goproxy.cn"
        srcRepo:
          url: "https://github.com/OpenFunction/samples.git"
          sourceSubPath: "functions/async/logs-handler-function/"
          revision: "main"
      serving:
        runtime: "async"
        scaleOptions:
          keda:
            scaledObject:
              pollingInterval: 15
              minReplicaCount: 0
              maxReplicaCount: 10
              cooldownPeriod: 60
              advanced:
                horizontalPodAutoscalerConfig:
                  behavior:
                    scaleDown:
                      stabilizationWindowSeconds: 45
                      policies:
                      - type: Percent
                        value: 50
                        periodSeconds: 15
                    scaleUp:
                      stabilizationWindowSeconds: 0
        triggers:
          - type: kafka
            metadata:
              topic: logs
              bootstrapServers: kafka-server-kafka-brokers.default.svc.cluster.local:9092
              consumerGroup: logs-handler
              lagThreshold: "20"
        template:
          containers:
            - name: function
              imagePullPolicy: Always
        inputs:
          - name: kafka
            component: kafka-receiver
        outputs:
          - name: notify
            component: notification-manager
            operation: "post"
        bindings:
          kafka-receiver:
            type: bindings.kafka
            version: v1
            metadata:
              - name: brokers
                value: "kafka-server-kafka-brokers:9092"
              - name: authRequired
                value: "false"
              - name: publishTopic
                value: "logs"
              - name: topics
                value: "logs"
              - name: consumerGroup
                value: "logs-handler"
          notification-manager:
            type: bindings.http
            version: v1
            metadata:
              - name: url
                value: http://notification-manager-svc.kubesphere-monitoring-system.svc.cluster.local:19093/api/v2/alerts
    
  2. Run the following command to create the function logs-async-handler.

    kubectl apply -f logs-handler-function.yaml
    
  3. The logs handler function will be triggered by messages from the logs topic in Kafka.


Last modified April 13, 2022: Update EN Documents (#56) (c6c10f0)