Apache Kafka for Programmers Training Course

Introduction

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

Kafka Architecture and Core Principles

• Architectural components: brokers, topics, partitions, and replicas
• Message flow: understanding producers and consumers
• The function of ZooKeeper within the Kafka ecosystem

Managing Topics and Partitions

• Process for creating and configuring topics
• Impact of partitioning on data distribution
• Mechanisms for replication and fault tolerance

Implementing Kafka Producers

• Building producers across multiple programming languages
• Techniques for message serialization
• Optimizing producer configurations and adhering to best practices

Implementing Kafka Consumers

• Developing consumer applications in various languages
• Setting up consumer groups and managing offsets
• Ensuring delivery guarantees and effective message processing strategies

System Integration via Kafka Connect

• Introduction to Kafka Connect and its connector ecosystem
• Configuration and deployment for data integration
• Establishing bridges to external data sources

Building Streaming Applications with Kafka Streams & ksqlDB

• Exploring stream processing capabilities in Kafka Streams
• Developing robust stream processing applications
• Leveraging ksqlDB for immediate data analytics and processing

Cloud Deployment with Confluent Cloud

• Key features and benefits of Confluent Cloud
• Steps to configure and link Kafka clients to Confluent Cloud

Security in Kafka

• Overview of available security features
• Setting up SSL/TLS for encrypted communication
• Implementing authentication and authorization controls

Monitoring and Operational Management

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

Best Practices and Industry Applications

• Strategic design patterns for Kafka-based systems
• Real-world case studies from diverse sectors
• Constructing scalable and resilient Kafka architectures

Conclusion and Future Directions