Apache Kafka

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This document describes how to configure your Google Kubernetes Engine deployment so that you can use Google Cloud Managed Service for Prometheus to collect metrics from Apache Kafka. This document shows you how to do the following:

  • Set up the exporter for Kafka to report metrics.
  • Configure a PodMonitoring resource for Managed Service for Prometheus to collect the exported metrics.
  • Access a dashboard in Cloud Monitoring to view the metrics.
  • Configure alerting rules to monitor the metrics.

These instructions apply only if you are using using managed collection with Managed Service for Prometheus. If instead you are using self-deployed collection, then see the source repository for the Kafka exporter for installation information.

For information about Kafka, see Kafka.

Prerequisites

To collect metrics from Kafka by using Managed Service for Prometheus and managed collection, your deployment must meet the following requirements:

  • Your cluster must be running Google Kubernetes Engine version 1.21.4-gke.300 or later.
  • You must be running Managed Service for Prometheus with managed collection enabled. For more information, see Get started with managed collection.

  • To use dashboards available in Cloud Monitoring for the Kafka integration, you must use kafka_exporter version v1.6.0 or later.

    For more information about available dashboards, see View dashboards.

Install the Kafka exporter

We recommend that you install the Kafka exporter, kafka_exporter, by using the following config:

# Copyright 2022 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

apiVersion: apps/v1
kind: Deployment
metadata:
  name: kafka-exporter
  labels:
    app.kubernetes.io/name: kafka-exporter
spec:
  replicas: 1
  selector:
    matchLabels:
      app.kubernetes.io/name: kafka-exporter
  template:
    metadata:
      labels:
        app.kubernetes.io/name: kafka-exporter
    spec:
      containers:
      - name: exporter
        image: danielqsj/kafka-exporter:v1.6.0
        args:
        - --kafka.server=kafka:9092
        ports:
        - containerPort: 9308
          name: prometheus
The Kafka exporter is configurable with flags, which can be set as container args. This example assumes Kafka is available as a ClusterIP service named kafka on port 9092.

To apply configuration changes from a local file, run the following command:

kubectl apply -n NAMESPACE_NAME -f FILE_NAME

You can also use Terraform to manage your configurations.

Define a PodMonitoring resource

For target discovery, the Managed Service for Prometheus Operator requires a PodMonitoring resource that corresponds to the Kafka exporter in the same namespace.

You can use the following PodMonitoring configuration:

# Copyright 2022 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

apiVersion: monitoring.googleapis.com/v1
kind: PodMonitoring
metadata:
  name: kafka-exporter
  labels:
    app.kubernetes.io/name: kafka-exporter
    app.kubernetes.io/part-of: google-cloud-managed-prometheus
spec:
  endpoints:
  - port: prometheus
    scheme: http
    interval: 30s
    path: /metrics
  selector:
    matchLabels:
      app.kubernetes.io/name: kafka-exporter

To apply configuration changes from a local file, run the following command:

kubectl apply -n NAMESPACE_NAME -f FILE_NAME

You can also use Terraform to manage your configurations.

Define rules and alerts

You can use the following Rules configuration to define alerts on your Kafka metrics:

# Copyright 2022 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

apiVersion: monitoring.googleapis.com/v1
kind: Rules
metadata:
  name: kafka-rules
  labels:
    app.kubernetes.io/component: rules
    app.kubernetes.io/name: kafka-rules
    app.kubernetes.io/part-of: google-cloud-managed-prometheus
spec:
  groups:
  - name: kafka
    interval: 30s
    rules:
    - alert: KafkaChangeInNumberOfISRs
      annotations:
        description: |-
          Kafka change in number of isrs
            VALUE = {{ $value }}
            LABELS: {{ $labels }}
        summary: Kafka change in number of isrs (instance {{ $labels.instance }})
      expr: kafka_topic_partition_in_sync_replica != 10
      for: 5m
      labels:
        severity: critical
    - alert: KafkaUnderReplicatedPartitions
      annotations:
        description: |-
          Kafka under replicated partitions
            VALUE = {{ $value }}
            LABELS: {{ $labels }}
        summary: Kafka under replicated partitions (instance {{ $labels.instance }})
      expr: kafka_topic_partition_under_replicated_partition > 0
      for: 1m
      labels:
        severity: warning

To apply configuration changes from a local file, run the following command:

kubectl apply -n NAMESPACE_NAME -f FILE_NAME

You can also use Terraform to manage your configurations.

For more information about applying rules to your cluster, see Managed rule evaluation and alerting.

You can adjust the alert thresholds to suit your application.

Verify the configuration

You can use Metrics Explorer to verify that you correctly configured the Kafka exporter. It might take one or two minutes for Cloud Monitoring to ingest your metrics.

To verify the metrics are ingested, do the following:

  1. In the Google Cloud console, select Monitoring or click the following button:
    Go to Monitoring
  2. In the navigation pane, select   Metrics Explorer.
  3. Select the PromQL tab, and run the following query:
    up{job="kafka-exporter", cluster="CLUSTER_NAME", namespace="NAMESPACE_NAME"}

View dashboards

The Cloud Monitoring integration includes the Kafka Prometheus Overview dashboard. Dashboards are automatically installed when you configure the integration. You can also view static previews of dashboards without installing the integration.

To view an installed dashboard, do the following:

  1. In the Google Cloud console, select Monitoring or click the following button:
    Go to Monitoring
  2. In the navigation pane, select  Dashboards.
  3. Select the Dashboard List tab.
  4. Choose the Integrations category.
  5. Click the name of the dashboard, for example, Kafka Prometheus Overview.

To view a static preview of the dashboard, do the following:

  1. In the Google Cloud console, select Monitoring or click the following button:
    Go to Monitoring
  2. In the navigation pane, select  Integrations.
  3. Click the Kubernetes Engine deployment-platform filter.
  4. Locate the Apache Kafka integration and click View Details.
  5. Select the Dashboards tab.

Troubleshooting

For information about troubleshooting metric-ingestion problems, see Problems with collection from exporters in Troubleshooting ingestion-side problems.