Kafka

Table of Contents Introduction Fundamentals of Event‑Driven Architecture (EDA) Why Apache Kafka? A Deep Dive into Core Concepts Designing Scalable Event‑Driven Systems Advanced Microservices Patterns for Event‑Driven Workflows 5.1 Event Sourcing 5.2 CQRS (Command Query Responsibility Segregation) 5.3 Saga & Distributed Transactions 5.4 Outbox Pattern 5.5 Idempotent Consumers 5.6 Consumer Groups & Partitioning Strategies 5.7 Back‑Pressure & Flow Control Practical Implementation: A Sample Kafka‑Powered Microservice 6.1 Project Structure 6.2 Producer Example (Spring Boot) 6.3 Consumer Example with Idempotency & Retry 6.4 Testing the Event Flow Deployment, Operations, and Scaling Observability, Monitoring, and Alerting Security, Governance, and Schema Management Common Pitfalls & Best‑Practice Checklist Conclusion Resources Introduction In today’s hyper‑connected world, applications must react to data in real time, handle unpredictable traffic spikes, and evolve independently without causing cascading failures. Event‑driven architectures (EDA), powered by robust messaging platforms, have become the de‑facto strategy for building such resilient, scalable systems. ...

Table of Contents Introduction: Why Kafka and KafkaJS Matter Understanding Kafka Fundamentals Setting Up Your Development Environment Your First KafkaJS Producer Your First KafkaJS Consumer Advanced Producer Patterns Advanced Consumer Patterns Schema Management and Serialization Error Handling and Resilience Performance Optimization Production Deployment Resources and Further Learning Introduction: Why Kafka and KafkaJS Matter Apache Kafka has become the backbone of modern data architecture. Think of it as the central nervous system for your applications: ...