Kafka Internals

Prerequisites:

• Basic Java experience (This can be modified for a C# or other language environment)

• Familiarity with command line interface

• Preferably Mac or Linux operating system

Course Objectives:

• Gain a deep understanding of Kafka's internal architecture and components.

• Master the use of producers, consumers, and brokers for data streaming.

• Build real-time data pipelines using Kafka Connect.

• Effectively leverage Kafka developer APIs to interact with the platform.

Course Length: 3 days

Course Content:

Module 1: Introduction to Kafka Internals

• Kafka Fundamentals:

  • Overview of Kafka as a distributed messaging system for real-time data processing.

  • Key terminology used in Kafka (topics, partitions, replicas, brokers, consumers, producers).

• Kafka Architecture (Deep Dive):

  • Logical Architecture: Understanding the abstract components and their interactions.

  • Physical Architecture: Exploring the real-world implementation of Kafka components.

  • Hands-on Labs: Configuring and deploying a local Kafka cluster.

• Kafka Internals:

  • Brokers: Responsibilities and functionalities of brokers within the cluster.

  • Producers and Consumers: Mechanisms for sending and receiving data streams.

  • Partitions and Topics: Data organization and distribution within Kafka.

  • Replication Mechanism: Ensuring data availability and fault tolerance.

  • Message Delivery Semantics: Understanding different message delivery guarantees.

• ZooKeeper/Kraft Integration:

  • Role of ZooKeeper and Kraft in Kafka cluster coordination and management.

  • Exploring Kraft/ZooKeeper's basic operations and interaction with Kafka.

Module 2: Kafka Administration and Advanced Topics

• Kafka Administration:

  • Key considerations for effective Kafka cluster management and monitoring.

  • Tools and techniques for monitoring Kafka cluster health and performance.

• Kafka Security:

  • Implementing security measures like authentication and authorization for secure access.

• Performance Tuning:

  • Strategies for optimizing Kafka performance based on hardware and data volume.

• Kafka Integrations:

  • Building real-time data pipelines using Kafka Connect for data ingestion from various sources.

  • Hands-on Labs: Constructing an end-to-end streaming ETL pipeline utilizing Kafka Connect.

Module 3: Kafka Developer APIs and Advanced Concepts

• Kafka Core APIs:

  • Producer API: Deep dive into producer configurations, message delivery mechanisms (sync/async), and message acknowledgment strategies.

  • Consumer API: Understanding various message delivery semantics and configuration options for fine-grained control of consumer behavior.

  • Hands-on Labs: Working with producer and consumer APIs to send and receive messages in Kafka.

• Kafka Streams and KTables (Optional):

  • Introduction to Kafka Streams and KTables for building real-time stream processing applications.

• KSQL (Optional):

  • Overview of KSQL DB for stream processing using SQL-like syntax.

  • Exploring functionalities like KTables, global KTables, and REST access.

• Application Integrations (Optional):

  • Integrating Kafka with Spring Boot or Node.js applications for data ingestion and processing.

Note:

• This is a sample outline, and the specific content covered may vary depending on the instructor and course provider.

• If desired Zookeeper content can be 100% replaced with Kraft

• Optional modules (KSQL, Application Integrations) can be included based on available time and student interest.

Additional Considerations:

• While this course does not cover KSQL in depth, a basic introduction is included as an optional module.

• Hands-on exercises are integrated throughout the course to provide practical experience with Kafka concepts and APIs.