Chapter 2. Streams for Apache Kafka deployment of Kafka Apache Kafka components are provided for deployment to OpenShift with the Streams for Apache Kafka distribution. The Kafka components are generally run as clusters for availability. A typical deployment incorporating Kafka components might include: Kafka cluster of broker nodes ZooKeeper cluster of replicated ZooKeeper instances Kafka Connect cluster for external data connections Kafka MirrorMaker cluster to mirror the Kafka cluster in a secondary cluster Kafka Exporter to extract additional Kafka metrics data for monitoring Kafka Bridge to make HTTP-based requests to the Kafka cluster Cruise Control to rebalance topic partitions across broker nodes Not all of these components are mandatory, though you need Kafka and ZooKeeper as a minimum. Some components can be deployed without Kafka, such as MirrorMaker or Kafka Connect. 2.1. Kafka component architecture A Kafka cluster comprises the brokers responsible for message delivery. ZooKeeper is used for cluster management. When deploying Kafka in KRaft (Kafka Raft metadata) mode, cluster management is simplified by integrating broker and controller roles within Kafka nodes, eliminating the need for ZooKeeper. Kafka nodes take on the roles of brokers, controllers, or both. Roles are configured in Streams for Apache Kafka using node pools. Each of the other Kafka components interact with the Kafka cluster to perform specific roles. Kafka component interaction Apache ZooKeeper Apache ZooKeeper provides a cluster coordination service, storing and tracking the status of brokers and consumers. ZooKeeper is also used for controller election. If ZooKeeper is used, the ZooKeeper cluster must be ready before running Kafka. In KRaft mode, ZooKeeper is not required because the coordination is managed in the Kafka cluster by Kafka nodes operating as controllers. Kafka Connect Kafka Connect is an integration toolkit for streaming data between Kafka brokers and other systems using Connector plugins. Kafka Connect provides a framework for integrating Kafka with an external data source or target, such as a database, for import or export of data using connectors. Connectors are plugins that provide the connection configuration needed. A source connector pushes external data into Kafka. A sink connector extracts data out of Kafka External data is translated and transformed into the appropriate format. You can deploy Kafka Connect with build configuration that automatically builds a container image with the connector plugins you require for your data connections. Kafka MirrorMaker Kafka MirrorMaker replicates data between two Kafka clusters, within or across data centers. MirrorMaker takes messages from a source Kafka cluster and writes them to a target Kafka cluster. Kafka Bridge Kafka Bridge provides an API for integrating HTTP-based clients with a Kafka cluster. Kafka Exporter Kafka Exporter extracts data for analysis as Prometheus metrics, primarily data relating to offsets, consumer groups, consumer lag and topics. Consumer lag is the delay between the last message written to a partition and the message currently being picked up from that partition by a consumer

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