Day: February 28, 2025

Here's a complete roadmap to learn Apache Kafka from basics to advanced, structured over 4 weeks for a solid grasp of Kafka concepts, hands-on practice, and real-world applications. This roadmap is designed for developers like you with experience in Java and backend technologies. Week 1: Kafka Fundamentals Day 1: Introduction to Kafka ✅ What is Kafka?✅ Kafka use cases and advantages✅ Kafka vs. traditional message brokers (RabbitMQ, ActiveMQ)✅ Kafka architecture overview 🔹 Hands-on: Install Apache Kafka and Zookeeper locally Start Kafka and create a topic Day 2: Kafka Core Concepts ✅ Kafka Topics, Partitions, and Offsets✅ Brokers, Producers, and Consumers✅ Consumer Groups and Load Balancing 🔹 Hands-on: Create topics with different partition settings Produce and consume messages using the Kafka CLI Day 3: Kafka Producers & Consumers ✅ Kafka Producer internals✅ Acknowledgment modes (acks=0,1,all)✅ Kafka Consumer internals✅ Consumer offset management 🔹 Hands-on: Write a Java Producer using the Kafka Client library Write a Java Consumer to consume messages Day 4: Kafka Message Delivery Semantics ✅ At-most-once, At-least-once, Exactly-once semantics✅ Message ordering and deduplication strategies 🔹 Hands-on: Experiment with different acknowledgment strategies Day 5: Kafka Retention & Compaction ✅ Log Retention Policies✅ Log Compaction 🔹 Hands-on: Set up log retention and compaction policies for topics Day 6: Kafka Configuration & Monitoring ✅ Important Kafka configurations (server.properties)✅ Monitoring Kafka (JMX, Kafka Manager, Grafana) 🔹 Hands-on: Use kafka-topics.sh and kafka-consumer-groups.sh for topic/consumer monitoring Set up monitoring tools like Prometheus & Grafana Day 7: Recap & Hands-on Practice ✅ Revise all key concepts✅ Practice Kafka CLI commands 🔹 Hands-on: Implement a small Java-based producer-consumer system Week 2: Advanced Kafka Concepts Day 8: Kafka Broker & Cluster Management ✅ Multi-node Kafka cluster setup✅ Kafka leader election & ISR (In-Sync Replicas)✅ Kafka fault tolerance 🔹 Hands-on: Set up a multi-broker Kafka cluster Day 9: Kafka Internals & Performance Optimization ✅ Kafka internals: Page Cache, Batching, Zero Copy✅ Performance tuning: Producer & Consumer settings 🔹 Hands-on: Optimize Kafka producer for high throughput Day 10: Kafka Security ✅ Authentication (SSL, SASL)✅ Authorization (ACLs) 🔹 Hands-on: Set up SSL authentication between Kafka clients and brokers Day 11: Kafka Schema Management ✅ Avro and Schema Registry✅ Schema evolution (Backward/Forward compatibility) 🔹 Hands-on: Set up Confluent Schema Registry and use Avro for serialization Day 12: Kafka Streams API (Intro) ✅ Kafka Streams vs. Other Stream Processing Frameworks✅ Stateless vs. Stateful Transformations✅ Windowing & Joins 🔹 Hands-on: Write a simple Kafka Streams application Day 13: Kafka Streams API (Advanced) ✅ KTables, GlobalKTables✅ Interactive Queries 🔹 Hands-on: Implement a Kafka Streams application with stateful processing Day 14: Recap & Hands-on ✅ Debugging common Kafka issues✅ Best practices 🔹 Hands-on: Fix common Kafka issues (offset reset, rebalancing, etc.) Week 3: Kafka in Real-world Applications Day 15: Kafka Connect Introduction ✅ Kafka Connect framework✅ Source & Sink connectors 🔹 Hands-on: Set up a JDBC Source Connector to stream data from MySQL to Kafka Day 16: Kafka Connect Advanced ✅ Distributed Mode vs. Standalone Mode✅ Custom Connectors 🔹 Hands-on: Implement a Kafka Sink Connector for Elasticsearch Day 17: Kafka with Microservices ✅ Kafka as an Event Bus in Microservices✅ Event-Driven Architecture with Kafka 🔹 Hands-on: Integrate Kafka with a Spring Boot microservice Day 18: Kafka & Transactional Messaging ✅ Kafka Transactions✅ Idempotent Producers 🔹 Hands-on: Implement Exactly-Once Processing in Kafka Day 19: Kafka Streams vs. Flink vs. Spark Streaming ✅ Key Differences✅ When to use what? 🔹 Hands-on: Compare Kafka Streams with Spark Streaming using a sample dataset Day 20: Event Sourcing with Kafka ✅ Event Sourcing Concepts✅ CQRS Pattern with Kafka 🔹 Hands-on: Implement an Event Sourcing pattern using Kafka Week 4: Expert Level & Real-world Scenarios Day 21: Kafka in Large-scale Systems ✅ Kafka in Data Pipelines (Lambda & Kappa Architectures)✅ Kafka in Machine Learning & Analytics 🔹 Hands-on: Design a Kafka-based data pipeline Day 22: Kafka Disaster Recovery & High Availability ✅ Replication across data centers✅ Multi-cluster Kafka setup 🔹 Hands-on: Set up a cross-data-center Kafka replication using MirrorMaker Day 23: Debugging & Troubleshooting Kafka Issues ✅ Common Kafka Issues (Consumer Lag, Offset Reset, Rebalancing)✅ Debugging tools (kafka-consumer-groups.sh, kafka-topics.sh) 🔹 Hands-on: Simulate failures and recover Kafka Day 24: Kafka Monitoring & Observability ✅ Kafka Metrics & Logs✅ OpenTelemetry for Kafka 🔹 Hands-on: Set up distributed tracing with OpenTelemetry Day 25: Kafka Certifications & Interview Prep ✅ Kafka certifications (Confluent Certified Developer/Admin)✅ Top Kafka interview questions & mock interview practice 🔹 Hands-on: Take a Kafka mock interview Day 26: Build a Kafka Real-world Project ✅ Choose a real-world use case (e.g., real-time stock market data pipeline)✅ Design and implement the system 🔹 Hands-on: Build & deploy a Kafka-based event-driven system Day 27-28: Capstone Project & Final Review ✅ Optimize and scale the Kafka project✅ Write a blog post/documentation on your Kafka learning journey 📌 Final Notes ✅ Follow this roadmap, and you'll go from a beginner to an expert in Kafka within a month.✅ Practice hands-on as much as possible.✅ Use real-world use cases to solidify your learning.✅ Prepare for Kafka interview questions alongside your learning. 🔥 Ready to start? Which step do you want to begin with? 🚀

Day: February 28, 2025

🧠 Mastering Apache Kafka: The Complete Roadmap from Beginner to Expert (2025 Edition)

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