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 Duration 21 hours (3 days)

Course Outline

Module 1: Overview of Confluent Apache Kafka Architecture and Configuration

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

Module 2: Configuring Zookeeper Quorum

  • Introduction to Zookeeper
  • The function of Zookeeper within a Kafka cluster
  • Determining Zookeeper Quorum size
  • Configuring Zookeeper settings
  • Setting up SSH on server environments
  • Practical exercise: Configuring Zookeeper as both a team and a service
  • Utilizing the Zookeeper Command Line Interface (CLI)
  • Practical exercise: Configuring the Zookeeper Quorum
  • Understanding the Zookeeper internal file system
  • Performance variables that impact Zookeeper
  • Demonstration of management tools, including Zookeeper and Zoonavigator

Module 3: Configuring the Kafka Cluster

  • Foundational Kafka concepts
  • General Kafka configuration settings
  • Practical exercise: Configuring Kafka brokers
  • Practical exercise: Running Kafka commands
  • Practical exercise: Setting up a Multi-Broker Kafka Cluster
  • Practical exercise: Testing the Kafka cluster
  • Verifying connectivity to your Kafka cluster
  • Advertised.listeners configuration: a critical setting
  • Topic-specific configurations
  • Settings for downloading and ingesting messages within topics
  • Practical exercise: Illustrating Kafka resilience
  • Kafka performance: Input/Output (I/O)
  • Kafka performance: Network (RED)
  • Kafka performance: RAM
  • Kafka performance: CPU
  • Kafka performance: Operating System (OS)
  • Kafka performance: Additional 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 using CLI, Java, and the Spring framework
  • Monitoring metrics and utilizing tools such as Confluent Control Center and Elasticsearch
  • Managing log files and offsets
  • High availability and disaster recovery planning
  • Ensuring high availability via replication
  • Optimizing producer and consumer performance
  • Disaster recovery strategies
  • Controlling failover and managing data recovery
  • Connector configurations
  • Implementing Kafka Connect
  • Exploring Kafka security features

Summary and Future Directions

Requirements

  • Knowledge of distributed systems and messaging principles
  • Proficiency with the Linux command line
  • Fundamental understanding of networking and system administration

Intended Audience

  • System administrators
  • DevOps engineers
  • Platform and infrastructure teams

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