What is KPOps?

With a couple of easy commands in the shell, and a pipeline.yaml of under 30 lines, KPOps can not only deploy a Kafka pipeline¹ to a Kubernetes cluster, but also reset, clean or destroy it!

Key features

• Deploy Kafka apps to Kubernetes: KPOps allows to deploy consecutive Kafka Streams applications and producers using an easy-to-read and -write pipeline definition.
• Manage Kafka Connectors: KPOps connects with your Kafka Connect cluster and deploys, validates, and deletes your connectors.
• Configure multiple pipelines and steps: KPOps has various abstractions that simplify configuring multiple pipelines and steps within pipelines by sharing common configuration between different components, such as producers or streaming applications.
• Handle your topics and schemas: KPOps not only creates and deletes your topics but also registers and deletes your schemas.
• Clean termination of Kafka components: KPOps removes your pipeline components (i.e., Kafka Streams applications) from the Kubernetes cluster and cleans up the component-related states (i.e., removing/resetting offset of Kafka consumer groups).
• Preview your pipeline changes: With the KPOps dry-run, you can ensure your pipeline definition is set up correctly. This helps to minimize downtime and prevent potential errors or issues that could impact your production environment.

Example

An overview of Word-count pipeline shown in Streams Explorer

- type: producer-app
  name: data-producer
  values:
    image: bakdata/kpops-demo-sentence-producer
    imageTag: "2.0.0"

- type: streams-app
  name: word-count-app
  values:
    image: bakdata/kpops-demo-word-count-app
    imageTag: "2.0.0"
    replicaCount: 1
  to:
    topics:
      ${output_topic_name}:
        type: output
        configs:
          cleanup.policy: compact

- type: kafka-sink-connector
  name: redis-sink-connector
  config:
    connector.class: com.github.jcustenborder.kafka.connect.redis.RedisSinkConnector
    redis.hosts: redis-headless:6379
    redis.database: 0
    tasks.max: 1
    key.converter: org.apache.kafka.connect.storage.StringConverter
    value.converter: org.apache.kafka.connect.storage.StringConverter

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1. A Kafka pipeline can consist of consecutive streaming applications, producers, and connectors. ↩