"Kafka is the heartbeat of real-time data streaming. Seamlessly scalable, fault-tolerant, and lightning-fast, it revolutionizes data pipelines, enabling distributed processing with ease. Harness its power to unlock insights from vast streams of data, We teach you from beginner to Master in Kafka streams for data processing" Register for live classes.

Module 1: Introduction to Apache Kafka

1. Overview of Apache Kafka

2. History and evolution

3. Kafka architecture and components

4. Use cases and benefits

Module 2: Kafka Fundamentals

1. Installation and setup

2. Kafka core concepts:

• Topics

• Partitions

• Producers

• Consumers

• Brokers

• Zookeeper

Module 3: Kafka Core Operations

1. Producing and consuming messages

2. Message serialization and deserialization

3. Managing topics and partitions

4. Configuring Kafka clusters

Module 4: Advanced Kafka Concepts

1. Message retention and cleanup policies

2. Kafka Streams API

3. Exactly-once processing semantics

4. Security and authentication

Module 5: Kafka Connect

1. Overview of Kafka Connect

2. Using Kafka Connect for data integration

3. Connectors and sink connectors

4. Building custom connectors

Module 6: Kafka in Production

1. Monitoring Kafka clusters

2. Performance tuning and optimization

3. High availability and fault tolerance

4. Disaster recovery strategies

Module 7: Kafka Ecosystem

1. Apache Kafka clients

2. Apache Kafka REST Proxy

3. Confluent Schema Registry

4. Kafka Streams for stream processing

Module 8: Kafka Integration

1. Integrating Kafka with Spring Boot

2. Integrating Kafka with other frameworks (e.g., Apache Spark, Apache Flink)

3. Real-world use cases and case studies

Module 9: Best Practices and Design Patterns

1. Designing Kafka-based architectures

2. Design patterns for building scalable and resilient systems

3. Error handling and retries

4. Scalability and performance optimization techniques

Module 10: Hands-on Projects

1. Building a real-time data pipeline with Kafka

2. Implementing a distributed messaging system

3. Developing stream processing applications with Kafka Streams

4. Building microservices with Kafka and Spring Boot

Module 11: Industry Trends and Future Directions

1. Overview of emerging trends in event streaming and real-time data processing

2. Kafka roadmap and future developments

3. Exploring the wider ecosystem (e.g., Kubernetes, cloud-native technologies)