Administration of Confluent Apache Kafka Training Course

Module 1: Overview of the architecture and configuration for Confluent Apache Kafka clusters

• The function of Kafka within modern data pipelines
• Key distinctions between Apache Kafka and Confluent Kafka
• Essential elements: producers, consumers, brokers, topics, and partitions
• Deployment strategies and scaling considerations for Kafka clusters

Module 2: Configuring the Zookeeper Quorum

• Introduction to Zookeeper
• The function of Zookeeper within a Kafka cluster
• Determining the appropriate Zookeeper Quorum size
• Configuring Zookeeper settings
• Implementing SSH on server infrastructure
• Practical exercise: Configuring Zookeeper (as a team and as a service)
• Utilizing the Zookeeper Command Line Interface (CLI)
• Practical exercise: Setting up the Zookeeper Quorum
• The Zookeeper internal file system
• Performance metrics influencing Zookeeper efficiency
• Demonstration of Zookeeper management tools and Zoonavigator

Module 3: Configuring the Kafka Cluster

• Fundamental concepts of Kafka
• General Kafka configuration
• Practical exercise: Setting up Kafka brokers
• Practical exercise: Running Kafka commands
• Practical exercise: Configuring a multi-broker Kafka cluster
• Practical exercise: Testing the Kafka cluster
• Verifying connectivity to the Kafka cluster
• Configuring Advertised.listeners: a critical setting
• Topic-level configurations
• Settings for downloading and ingesting messages within topics
• Practical exercise: Demonstrating Kafka resilience
• Kafka performance: Input/Output (I/O)
• Kafka performance: Network (RED)
• Kafka performance: Memory (RAM)
• Kafka performance: Central Processing Unit (CPU)
• Kafka performance: Operating System (OS)
• Kafka performance: Other factors
• Practical exercise: Modifying Kafka broker configurations

Module 4: Advanced Kafka Configurations

• Configuring the Landoop Kafka topic interface, Confluent REST Proxy, and Confluent Schema Registry
• Transmitting and receiving messages via CLI, Java, and the Spring framework
• Monitoring metrics using tools such as Confluent Control Center and Elasticsearch
• Management of log files and offsets
• Strategies for high availability and disaster recovery
• Achieving high availability through replication
• Optimizing producer and consumer performance
• Disaster recovery approaches
• Controlling failover and recovering data
• Configuring connectors
• Implementing Kafka Connect
• Integrating Kafka security features

Summary and Subsequent Steps