🧭 Complete Expert Syllabus: Kafka, RabbitMQ, and Event-Driven Architecture (EDA)

✅ PHASE 1 – Foundations of Event-Driven Architecture (EDA)

1.1 What is Event-Driven Architecture

• 1.1.1 Definition, Principles

• 1.1.2 Benefits (Scalability, Loose Coupling, Resilience)

• 1.1.3 Event-Driven vs Request-Driven Systems

• 1.1.4 Use Cases (Chat, Orders, IoT, Analytics)

1.2 Core Concepts

• 1.2.1 Events

• 1.2.2 Producers

• 1.2.3 Consumers

• 1.2.4 Brokers (Kafka, RabbitMQ, Cloud Brokers)

• 1.2.5 Event Bus, Event Store

1.3 Event Types

• 1.3.1 Domain Events

• 1.3.2 Integration Events

• 1.3.3 Business Events

• 1.3.4 System Events

1.4 Event Delivery Patterns

• 1.4.1 Event Notification

• 1.4.2 Event-Carried State Transfer

1.5 Event Flow Patterns

• 1.5.1 Point-to-Point

• 1.5.2 Pub/Sub

• 1.5.3 Fan-Out

• 1.5.4 Fan-In

✅ PHASE 2 – Messaging & Communication Patterns

2.1 Messaging Components

• 2.1.1 Publisher, Subscriber

• 2.1.2 Broker (Kafka, RabbitMQ, others)

• 2.1.3 Message Format (Avro, JSON, Protobuf)

• 2.1.4 Event Store

2.2 Messaging Patterns

• 2.2.1 Fire-and-Forget

• 2.2.2 Request-Reply

• 2.2.3 Command vs Event

• 2.2.4 Event Sourcing

2.3 Delivery Guarantees

• 2.3.1 At-most-once

• 2.3.2 At-least-once

• 2.3.3 Exactly-once

• 2.3.4 Idempotency, Deduplication

2.4 Sync vs Async

• 2.4.1 Pros and Cons

• 2.4.2 Hybrid Architectures

✅ PHASE 3 – Kafka: Core to Expert

3.1 Kafka Fundamentals

• 3.1.1 Topics, Partitions, Offsets

• 3.1.2 Producer API

• 3.1.3 Consumer Groups

• 3.1.4 Kafka Broker Internals

• 3.1.5 ZooKeeper vs KRaft

3.2 Kafka in Spring Boot

• 3.2.1 spring-kafka Setup

• 3.2.2 KafkaTemplate, KafkaListener

• 3.2.3 Serializers/Deserializers

• 3.2.4 Retry & Dead Letter Topics

3.3 Kafka Advanced

• 3.3.1 Kafka Streams API

• 3.3.2 KSQL / ksqlDB

• 3.3.3 Kafka Connect (source/sink)

• 3.3.4 Schema Registry (Confluent, Apicurio)

3.4 Kafka Ops & Infra

• 3.4.1 Kafka on Kubernetes

• 3.4.2 Kafka ACLs, Security (SASL, TLS)

• 3.4.3 Multi-Cluster Kafka (MirrorMaker)

• 3.4.4 Monitoring (Cruise Control, Burrow, JMX)

✅ PHASE 4 – RabbitMQ: Core to Expert

4.1 RabbitMQ Basics

• 4.1.1 Exchanges (Direct, Topic, Fanout, Headers)

• 4.1.2 Queues & Bindings

• 4.1.3 Message Acknowledgements

4.2 Spring Boot with RabbitMQ

• 4.2.1 spring-amqp Configuration

• 4.2.2 Message Listeners, Templates

• 4.2.3 Retry Queues, Dead Letter Exchange (DLX)

4.3 RabbitMQ Advanced

• 4.3.1 Federation vs Shovel

• 4.3.2 Priority Queues, TTL, Lazy Queues

• 4.3.3 Streams (new feature)

4.4 RabbitMQ Security & Ops

• 4.4.1 TLS, User Permissions

• 4.4.2 Clustering, High Availability

• 4.4.3 Monitoring (Prometheus, Grafana)

✅ PHASE 5 – Cloud-Based EDA (AWS, Azure, GCP)

5.1 AWS Event Services

• 5.1.1 Amazon MSK (Managed Kafka)

• 5.1.2 SQS, SNS, EventBridge

• 5.1.3 Kinesis Data Streams vs Kafka

5.2 Azure Event Services

• 5.2.1 Azure Event Grid

• 5.2.2 Azure Service Bus

• 5.2.3 Azure Event Hubs

5.3 GCP Event Services

• 5.3.1 GCP Pub/Sub

• 5.3.2 GCP Eventarc

• 5.3.3 Integration with Cloud Functions

5.4 Hybrid & Multi-Cloud EDA

• 5.4.1 Kafka Connect to Cloud

• 5.4.2 Self-hosted Kafka + Cloud Pub/Sub

• 5.4.3 Cloud-to-Cloud bridges

✅ PHASE 6 – Design & Architecture

6.1 Event-Driven Microservices

• 6.1.1 Order → Payment → Shipping Pipeline

• 6.1.2 Choreography vs Orchestration

• 6.1.3 Saga Pattern

6.2 DDD with EDA

• 6.2.1 Bounded Contexts

• 6.2.2 Event Storming

• 6.2.3 Aggregates & Events

6.3 Event Replay & Time Travel

• 6.3.1 Immutable Event Logs

• 6.3.2 Event Versioning

✅ PHASE 7 – Testing, Observability, and Reliability

7.1 Testing

• 7.1.1 Unit vs Integration vs Contract Testing

• 7.1.2 Embedded Kafka, RabbitMQ

• 7.1.3 Pact.io, Spring Cloud Contract

• 7.1.4 Chaos Testing

7.2 Observability

• 7.2.1 Distributed Tracing (Zipkin, Jaeger, OpenTelemetry)

• 7.2.2 Metrics with Prometheus + Grafana

• 7.2.3 Kafka Lag Monitoring (Burrow, Cruise Control)

• 7.2.4 RabbitMQ Queue Monitoring

7.3 Reliability

• 7.3.1 Retry Logic (Exponential Backoff)

• 7.3.2 Dead Letter Topics / Exchanges

• 7.3.3 Poison Message Handling

✅ PHASE 8 – Security & Compliance

8.1 Kafka Security

• 8.1.1 TLS, SASL, ACLs

• 8.1.2 Authentication & Authorization

• 8.1.3 Encryption at Rest & In Transit

8.2 RabbitMQ Security

• 8.2.1 User Roles, TLS

• 8.2.2 Plugin-based Auth

8.3 Secure Payload Handling

• 8.3.1 JWT in Events

• 8.3.2 Encrypted Event Data

• 8.3.3 Data Masking, GDPR/PII

✅ PHASE 9 – CI/CD, DevOps & Infra

9.1 Infrastructure as Code

• 9.1.1 Terraform for Kafka, RabbitMQ

• 9.1.2 Helm Charts, Kustomize (K8s)

9.2 Kafka DevOps

• 9.2.1 GitOps for Topic Management

• 9.2.2 Confluent Operator

9.3 RabbitMQ DevOps

• 9.3.1 RabbitMQ on Kubernetes

• 9.3.2 RabbitMQ Operator

9.4 Deployment Strategies

• 9.4.1 Blue-Green Deployment

• 9.4.2 Canary Releases for Event Consumers

✅ PHASE 10 – Real-Time Streaming & Analytics

10.1 Streaming Architectures

• 10.1.1 Kafka Streams

• 10.1.2 Apache Flink

• 10.1.3 Spark Streaming

10.2 Stream Processing Concepts

• 10.2.1 Tumbling/Sliding Windows

• 10.2.2 Event-Time vs Processing-Time

• 10.2.3 Watermarks

✅ PHASE 11 – Capstone Projects

11.1 Real-World Systems

• 11.1.1 E-Commerce Order Pipeline

• 11.1.2 Real-Time Fraud Detection

• 11.1.3 IoT Sensor Network with Kafka Streams

• 11.1.4 Cross-Region Event-Driven System (Hybrid Cloud)

✅ BONUS: Interview & Certification Prep

• Apache Kafka Confluent Cert (CCDAK)

• RabbitMQ Expert Interview Prep

• Cloud Event System Architecture Diagrams

• Design Case Studies