Administration of Confluent Apache Kafka Training Course

Module 1: Overview of Confluent Apache Kafka Cluster Architecture and Configuration

• The role of Kafka within modern data pipelines.
• Distinguishing between Apache Kafka and Confluent Kafka.
• Key components: producers, consumers, brokers, topics, and partitions.
• Deployment models for Kafka clusters and considerations for scaling.

Module 2: Configuring Zookeeper Quorums

• An introduction to Zookeeper.
• The function of Zookeeper within a Kafka cluster.
• Determining Zookeeper Quorum size.
• Zookeeper configuration processes.
• Setting up SSH on our servers.
• Practical session: Configuring Zookeeper (as a team and as a service).
• Utilizing the Zookeeper Command Line Interface (CLI).
• Practical session: Configuring Zookeeper Quorums.
• Understanding the Zookeeper internal file system.
• Performance factors impacting Zookeeper.
• Demonstration of Zookeeper management tools and Zoonavigator.

Module 3: Configuring the Kafka Cluster

• Fundamental Kafka concepts.
• General Kafka configuration.
• Practical session: Configuring Kafka brokers.
• Practical session: Executing Kafka commands.
• Practical session: Configuring a Kafka Multi-Broker Cluster.
• Practical session: Testing Kafka clusters.
• Verifying connectivity to your Kafka cluster.
• The Advertised.listeners configuration: a critical setting.
• Topic configuration details.
• Settings for downloading and ingesting messages within topics.
• Practical session: Demonstrating Kafka resilience.
• Kafka performance: I/O.
• Kafka performance: Network (RED).
• Kafka performance: RAM.
• Kafka performance: CPU.
• Kafka performance: Operating System (OS).
• Kafka performance: Other factors.
• Practical session: Modifying Kafka broker configurations.

Module 4: Advanced Kafka Configuration

• Configuring the Landoop Kafka topic UI, Confluent REST Proxy, and Confluent Schema Registry.
• Transmitting and receiving messages via CLI, Java, and the Spring framework.
• Monitoring metrics and tools, such as Confluent Control Center and Elasticsearch.
• Managing log files and offsets.
• Ensuring high availability and disaster recovery.
• Achieving high availability through replication.
• Optimizing producer and consumer performance.
• Developing disaster recovery strategies.
• Controlling failover and recovering data.
• Configuring connectors.
• Implementing Kafka Connect.
• Kafka security features.

Summary and Next Steps