Apache Kafka for Programmers Training Course

Introduction

• General overview of Apache Kafka
• Fundamentals of event streaming and real-time data processing
• Detailed look at Apache Kafka features and capabilities
• Key use cases and advantages of Kafka in contemporary app development

Kafka Architecture and Core Concepts

• Architectural components: brokers, topics, partitions, and replicas
• Role of producers and consumers in message publishing and consumption
• The function of ZooKeeper within the Kafka ecosystem

Managing Kafka Topics and Partitions

• Procedures for topic creation and configuration
• Implications and mechanics of partitioning
• Achieving replication and fault tolerance in Kafka

Working with Kafka Producers

• Implementation of Kafka producers across various programming languages
• Techniques for message serialization and deserialization
• Optimal producer configurations and industry best practices

Developing Kafka Consumers

• Creating Kafka consumers using different programming languages
• Setting up consumer groups and managing offsets
• Strategies for message processing and ensuring delivery guarantees

External System Integration via Kafka Connect

• Introduction to Kafka Connect and its connector framework
• Configuration and application of Kafka Connect for data integration
• Establishing connections between Kafka and external systems

Stream Processing with Kafka Streams & ksqlDB

• Foundations of Kafka Streams and its processing capabilities
• Building stream processing applications with Kafka Streams
• Leveraging ksqlDB for real-time analytics and data processing

Cloud Integration with Confluent Cloud

• Overview of Confluent Cloud features and benefits
• Configuration and connection of Kafka clients to Confluent Cloud

Securing Kafka

• Introduction to Kafka security features
• Implementing SSL/TLS for secure communication channels
• Mechanisms for authentication and authorization in Kafka

Monitoring and Operational Management

• Utilizing metrics and tools for Kafka monitoring
• Administration of Kafka clusters and resource management
• Diagnosing common issues and optimizing performance

Best Practices and Industry Applications

• Recommended practices for designing Kafka-centric applications
• Case studies highlighting Kafka implementations across various sectors
• Strategies for constructing scalable and resilient Kafka architectures

Summary and Future Directions