Duration: 48 hours

Target audience: Java developers

Description: This comprehensive training equips you with the expertise to design, implement, and operate robust, scalable, and efficient stream processing solutions using Apache Kafka

Key takeaways:

• Understand the fundamentals of distributed systems and the role of stream processing in modern data architectures.
• Gain in-depth knowledge of Apache Kafka’s architecture, including brokers, topics, partitions, producers, and consumers.
• Learn to set up, configure, and manage Kafka clusters for high availability, scalability, and fault tolerance.
• Master Kafka Producer and Consumer APIs and their customization for various real-time data streaming scenarios.
• Develop stream processing applications using the Kafka Streams API, including transformations, aggregations, joins, and windowing.
• Explore Kafka ecosystem components such as Kafka Connect for data integration.
• Implement security best practices in Kafka clusters, including authentication, authorization, and encryption.
• Monitor and tune Kafka clusters and stream processing applications for optimal performance and reliability.
• Apply best practices for deploying, scaling, and troubleshooting Kafka in production environments.
• Build real-world projects involving end-to-end data pipelines, real-time analytics, and event-driven architectures using Kafka and its ecosystem.
• Acquire hands-on experience through practical labs and projects to consolidate theoretical knowledge and develop job-ready skills in distributed stream processing with Apache Kafka.

Training program:

Module 1: Kafka Core Concepts and Java Setup (6 hours)

• Overview of brokers, topics, partitions, and their role in Kafka’s distributed architecture

• Setting up Kafka cluster and Java development environment

• Java Kafka client basics: Producer and Consumer APIs

• Writing simple Java producers and consumers with asynchronous send and poll methods

• Hands-on: Build and run a basic Java producer and consumer application with Kafka

Module 2: Advanced Producer and Consumer Features in Java (10 hours)

• Detailed Java API usage for KafkaProducer and KafkaConsumer

• Implementing asynchronous data production and consumption with callbacks

• Using interceptors in Java producers and consumers for monitoring and modifying records

• Implementing exactly-once semantics using Kafka transactions and idempotent producers

• Handling failures and retries in asynchronous processing

• Handling compacted topics and understanding their use cases

• Hands-on: Code exercises on transactional producers, interceptors, and compacted topic usage

• Hands-on: Develop robust Java applications ensuring exactly-once event processing guarantees

Module 3: Kafka Admin Client and Programmatic Administration (6 hours)

• Introduction to Kafka AdminClient API for managing topics, partitions, and configurations programmatically

• Creating, deleting, and modifying topics using Java AdminClient

• Managing ACLs, quotas, and broker configurations via Java APIs

• Hands-on: Write Java programs to automate Kafka cluster administration tasks

Module 4: Performance Monitoring and Visualization (6 hours)

• Kafka metrics overview: producer, consumer, broker, and stream metrics

• Configuring Prometheus to scrape Kafka metrics via JMX exporter

• Setting up Grafana dashboards for real-time Kafka monitoring

• Writing Java code to expose custom metrics and integrate with monitoring tools

• Hands-on: Build a monitoring stack with Prometheus and Grafana for Kafka clusters and applications

Module 5: Kafka Streams – KStream and KTable (8 hours)

• Introduction to Kafka Streams API and its programming model

• Differences between KStream and KTable abstractions

• Writing Java stream processing applications: filtering, mapping, aggregations, joins, and windowing

• Managing state stores and fault tolerance in Kafka Streams

• Exactly-once processing guarantees with Kafka Streams

• Hands-on: Build and deploy Java Kafka Streams applications using KStream and KTable APIs

Module 6: Practical Problem Solving and Project Work (8 hours)

• Real-world problem scenarios involving brokers, partitions, and topic design

• Debugging and troubleshooting Java Kafka clients and stream applications

• Project 1: End-to-end Kafka pipeline with transactional producers and consumers

• Project 2: Stream processing with KStream and KTable including joins and aggregations

• Code reviews, performance tuning, and best practices discussion

Module 7: Review, Assessment, and Next Steps (4 hours)

• Recap of key Java APIs and Kafka concepts

• Hands-on coding assessment and problem-solving exercises

• Q&A and troubleshooting common Kafka Java client issues

• Guidance on further learning and Kafka ecosystem tools

This program ensures participants gain deep hands-on expertise in Kafka’s Java client APIs, advanced Kafka features like transactions, interceptors, compacted topics, and Kafka Streams, combined with practical skills in monitoring and administration using Prometheus and Grafana.