Apache Kafka for Programmers Training Course

Introduction

• Overview of Apache Kafka
• Introduction to event streaming and real-time data processing
• Features and capabilities of Apache Kafka
• Use cases and advantages of Kafka in modern application development

Kafka Architecture and Core Concepts

• Architecture components: brokers, topics, partitions, and replicas
• Producers and consumers: the process of publishing and consuming messages
• The role of ZooKeeper in the Kafka ecosystem

Managing Topics and Partitions

• Creating and configuring topics
• Implications of partitioning strategies
• Replication mechanisms and fault-tolerance in Kafka

Working with Kafka Producers

• Implementing Kafka producers in various programming languages
• Message serialization methods and techniques
• Optimizing producer configurations and best practices

Working with Kafka Consumers

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

Connecting Kafka to External Systems with Kafka Connect

• Overview of Kafka Connect and its connector ecosystem
• Configuration and usage of Kafka Connect for data integration
• Strategies for integrating Kafka with third-party systems

Building Streaming Applications with Kafka Streams & ksqlDB

• Fundamentals of Kafka Streams and stream processing capabilities
• Development of stream processing applications using Kafka Streams
• Leveraging ksqlDB for real-time data processing and analytics

Connecting Client Applications to Confluent Cloud

• Features and overview of Confluent Cloud
• Configuration and connection of Kafka client applications to Confluent Cloud

Enhancing Kafka Security

• Overview of built-in Kafka security features
• Implementation of SSL/TLS for secure communication
• Authentication and authorization protocols within Kafka

Monitoring and Operational Management

• Tracking performance via metrics and monitoring tools
• Administration of Kafka clusters and resource allocation
• Diagnosing common issues and optimizing performance

Best Practices and Industry Applications

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

Conclusion and Future Directions