Apache Kafka for Programmers Training Course

Introduction

• Overview of the Apache Kafka platform
• Fundamentals of event streaming and real-time data processing
• Key features and capabilities of Apache Kafka
• Practical use cases and advantages of Kafka in modern application development

Exploring Kafka Architecture and Core Principles

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

Kafka Topics and Partitioning

• Creating and configuring topics effectively
• The significance of partitions and their impact on performance
• Implementing replication and ensuring fault-tolerance

Working with Kafka Producers

• Implementing Kafka producers across various programming languages
• Techniques for message serialization
• Optimizing producer configurations and adhering to best practices

Working with Kafka Consumers

• Building Kafka consumers using different programming languages
• Managing consumer groups and offset tracking
• Applying strategies for efficient message processing and ensuring delivery guarantees

Connecting Kafka to External Systems via Kafka Connect

• Understanding Kafka Connect and its range of connectors
• Setting up and utilizing Kafka Connect for seamless data integration
• Linking Kafka with diverse external systems

Building Streaming Applications with Kafka Streams & ksqlDB

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

Connecting to Confluent Cloud

• Overview of Confluent Cloud features and benefits
• Configuring and establishing connections between client applications and Confluent Cloud

Securing Kafka

• Introduction to Kafka's security mechanisms
• Configuring SSL/TLS for encrypted communication
• Implementing authentication and authorization controls

Monitoring and Operations

• Utilizing metrics and tools to monitor Kafka performance
• Efficient management of Kafka clusters and resources
• Diagnosing common issues and optimizing performance

Best Practices and Industry Applications

• Strategic best practices for designing Kafka-centric applications
• Case studies showcasing Kafka implementations across various sectors
• Guidelines for constructing scalable and resilient Kafka architectures

Conclusion and Path Forward