Apache Kafka for Programmers Training Course

Introduction

• Fundamental overview of Apache Kafka
• Basics of event streaming and real-time data processing
• Detailed exploration of Apache Kafka features
• Applications and advantages of Kafka in modern development

Kafka Architecture and Core Concepts

• Architecture components: brokers, topics, partitions, and replicas
• Roles of producers and consumers in message publication and consumption
• The function of ZooKeeper within the Kafka ecosystem

Managing Kafka Topics and Partitions

• Processes for topic creation and configuration
• Implications of partitioning strategies
• Mechanisms for replication and fault-tolerance

Kafka Producers

• Implementing producers using various programming languages
• Techniques for message serialization
• Optimal producer configurations and recommended practices

Kafka Consumers

• Building consumers in different programming languages
• Setting up consumer groups and managing offsets
• Approaches to message processing and ensuring delivery guarantees

System Integration with Kafka Connect

• Fundamentals of Kafka Connect and its connector ecosystem
• Configuring Kafka Connect for effective data integration
• Strategies for integrating Kafka with third-party systems

Building Streaming Applications with Kafka Streams & ksqlDB

• Introduction to Kafka Streams and its processing capabilities
• Developing applications for stream processing
• Leveraging ksqlDB for real-time analytics and data processing

Cloud Integration with Confluent Cloud

• Overview of Confluent Cloud capabilities
• Steps for configuring and connecting Kafka clients to Confluent Cloud

Kafka Security

• Key security features available in Kafka
• Implementing SSL/TLS for secure communications
• Managing authentication and authorization protocols

Monitoring and Operations

• Utilizing metrics and tools for Kafka monitoring
• Managing cluster resources and health
• Diagnosing common issues and optimizing performance

Best Practices and Industry Applications

• Guidelines for designing robust Kafka-based applications
• Case studies illustrating Kafka implementations across sectors
• Strategies for building scalable, fault-tolerant architectures

Summary and Future Steps