Apache Kafka for Programmers Training Course

Introduction

• General overview of Apache Kafka
• Basics of event streaming and real-time data processing
• Detailed look at Apache Kafka and its key features
• Applications and advantages of Kafka in modern software development

Exploring Kafka Architecture and Core Principles

• Kafka architecture components: brokers, topics, partitions, and replicas
• Role of producers and consumers in message publishing and consumption
• Understanding ZooKeeper's function within Kafka

Kafka Topics and Partitioning

• Creating and configuring topics
• The impact of partitions on data distribution
• Replication strategies and fault tolerance in Kafka

Kafka Producers

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

Kafka Consumers

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

Connecting Kafka to External Systems via Kafka Connect

• Overview of Kafka Connect and its connector ecosystem
• Configuring and deploying Kafka Connect for data integration
• Linking Kafka with external data sources

Building Streaming Applications with Kafka Streams and ksqlDB

• Familiarizing with Kafka Streams and its stream processing features
• Developing stream processing applications using Kafka Streams
• Leveraging ksqlDB for real-time data analysis and processing

Connecting Kafka Client Applications to Confluent Cloud

• Introduction to Confluent Cloud and its capabilities
• Establishing connections between Kafka client applications and Confluent Cloud

Kafka Security

• Overview of security features in Kafka
• Setting up SSL/TLS for secure communication channels
• Implementing authentication and authorization mechanisms in Kafka

Monitoring and Operations

• Tracking Kafka performance using metrics and monitoring tools
• Managing Kafka clusters and associated resources
• Diagnosing common issues and optimizing performance

Best Practices and Real-World Applications

• Guidelines for designing effective Kafka-based applications
• Case studies and examples of Kafka adoption across various industries
• Strategies for creating scalable and fault-tolerant Kafka architectures

Conclusion and Future Steps