Administration of Confluent Apache Kafka Training Course

Module 1: Overview of Confluent Apache Kafka Architecture and Configuration

• The role of Kafka in contemporary data pipelines
• Distinguishing between Apache Kafka and Confluent Kafka
• Essential components: producers, consumers, brokers, topics, and partitions
• Deployment models for Kafka clusters and scaling strategies

Module 2: Configuring the Zookeeper Quorum

• An introduction to Zookeeper
• The function of Zookeeper within a Kafka cluster
• Determining appropriate Zookeeper Quorum sizes
• Configuring Zookeeper settings
• Setting up SSH on server infrastructure
• Hands-on: Configuring Zookeeper both as a team member and as a standalone service
• Utilizing the Zookeeper Command Line Interface (CLI)
• Hands-on: Configuring the Zookeeper Quorum
• Exploring the Zookeeper internal file system
• Key performance factors influencing Zookeeper
• Demonstrating management tools for Zookeeper and Zoonavigator

Module 3: Configuring the Kafka Cluster

• Foundational concepts of Kafka
• General Kafka configuration practices
• Hands-on: Configuring a Kafka broker
• Hands-on: Executing standard Kafka commands
• Hands-on: Setting up a Multi-Broker Kafka Cluster
• Hands-on: Testing the stability of a Kafka cluster
• Verifying connectivity to the Kafka cluster
• Configuring Advertised.listeners: A critical setting
• Managing topic configurations
• Settings for downloading and ingesting messages within topics
• Hands-on: Demonstrating Kafka resilience mechanisms
• Optimizing Kafka performance: I/O operations
• Optimizing Kafka performance: Network (RED metrics)
• Optimizing Kafka performance: RAM usage
• Optimizing Kafka performance: CPU utilization
• Optimizing Kafka performance: Operating System (OS) level adjustments
• Other performance considerations
• Hands-on: 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
• Managing log files and offsets
• Ensuring high availability and disaster recovery
• Achieving high availability through replication strategies
• Tuning producer and consumer performance
• Formulating disaster recovery strategies
• Controlling failover processes and managing data recovery
• Configuring connectors
• Implementing Kafka Connect
• Implementing Kafka security features

Summary and Recommended Next Steps