Apache Kafka for Programmers Training Course

Introduction

• Overview of Apache Kafka
• Introduction to event streaming and real-time data processing
• Key features and capabilities of Apache Kafka
• Application use cases and advantages of Kafka in modern development

Kafka Architecture and Core Concepts

• Kafka architecture components: brokers, topics, partitions, and replicas
• Producers and consumers: handling message publishing and consumption
• The role of ZooKeeper within the Kafka ecosystem

Kafka Topics and Partitions

• Creating and configuring topics
• Understanding partitions and their impact on performance
• Replication mechanisms and fault tolerance in Kafka

Kafka Producers

• Building Kafka producers across various programming languages
• Message serialization and effective serialization techniques
• Optimal producer configurations and industry best practices

Kafka Consumers

• Developing Kafka consumers in different programming languages
• Managing consumer groups and offset settings
• Approaches to message processing and ensuring delivery guarantees

Connecting Kafka to External Systems via Kafka Connect

• Introduction to Kafka Connect and its connector types
• Setting up and utilizing Kafka Connect for data integration
• Linking Kafka with third-party systems

Building Streaming Applications with Kafka Streams and ksqlDB

• Getting started with Kafka Streams and its processing capabilities
• Developing stream processing applications using Kafka Streams
• Leveraging ksqlDB for real-time data analysis and processing

Connecting Kafka Client Applications to Confluent Cloud

• Overview of Confluent Cloud and its key features
• Configuration and connection of Kafka client applications to Confluent Cloud

Kafka Security

• Introduction to security features in Kafka
• Configuring SSL/TLS for secure communications
• Authentication and authorization protocols in Kafka

Monitoring and Operations

• Tracking Kafka performance using metrics and operational tools
• Managing Kafka clusters and associated resources
• Resolving common issues and optimizing performance

Best Practices and Industry Use Cases

• Recommended practices for designing Kafka-based applications
• Case studies illustrating Kafka implementation across various sectors
• Strategies for creating scalable and resilient Kafka architectures

Conclusion and Future Steps