Spring, RabbitMQ, and Modern Java Platform Engineering

Designing, Building, and Operating Reliable Distributed Systems

Introduction

1. What This Book Covers
2. How This Book Is Structured
3. Who Should Read This Book
4. The Philosophy Behind This Book

Chapter 1: The Reality of Distributed Systems

1. The Moment Everything Changes
2. The Fundamental Tensions: Consistency, Availability, and Partition Tolerance
3. Latency, Concurrency, and Partial Failure
4. Why “Just Add a Message Broker” Is Not an Answer
5. Communication Models: RPC, Messaging, Events, and Their Trade-offs
6. The Operational Dimension: What Production Really Demands
7. Introducing OrderFlow: Our Reference Platform

Chapter 2: Modern Java for Platform Engineering

1. Why Java Matters for Distributed Systems
2. Java 21 Features That Matter: Records, Sealed Classes, Pattern Matching, Virtual Threads
3. JVM Fundamentals for Production: Memory Model, Garbage Collection, Tuning Basics
4. Build Tooling: Maven, Modularization, and Dependency Management
5. Concurrency in Java: Executors, Virtual Threads, Structured Concurrency
6. Structured Logging and Observability-Ready Code
7. Defensive Programming: Null Safety, Immutable Data, and Failure Handling

Chapter 3: Architectural Principles and Patterns

1. From Monolith to Distributed: When and Why to Break Apart
2. Domain-Driven Design: Bounded Contexts, Ubiquitous Language, and Strategic Design
3. Event-Driven Architecture: Core Concepts and Anti-Patterns
4. Microservices and Service-Oriented Architecture: Truths and Misconceptions
5. Synchronous vs Asynchronous: Choosing the Right Communication Style
6. Designing for Failure: Resilience Patterns and Graceful Degradation

Chapter 4: Spring Boot for Production Systems

1. How Spring Boot Works: Auto-Configuration, Starters, and the Application Context
2. Dependency Injection and the Component Model
3. Configuration Management: Profiles, Externalization, and Hierarchies
4. REST with Spring Web MVC and WebFlux
5. Actuator: Health, Metrics, and Production Visibility
6. Lifecycle Management and Graceful Shutdown

Chapter 5: Data Access and Persistence with Spring Data

1. Spring Data JPA: Entities, Repositories, and Query Methods
2. Transaction Management: Propagation, Isolation, and Distributed Considerations
3. Database Migrations with Flyway
4. Connection Pooling and Performance
5. Choosing Persistence Technologies: Relational vs Document vs Specialized Stores
6. Persistence Anti-Patterns and Pitfalls

Chapter 6: RabbitMQ Fundamentals

1. RabbitMQ Architecture: Broker, Nodes, Clusters, and the Management Layer
2. The AMQP Protocol: Concepts, Versioning, and Alternatives
3. Connections, Channels, and Resource Management
4. Queues, Exchanges, and Bindings: The Core Data Model
5. Message Flow and Lifecycle
6. RabbitMQ Management: UI, HTTP API, and CLI Tools

Chapter 7: Exchange Types, Routing, and Topology Design

1. Direct Exchanges: Point-to-Point Routing
2. Fanout Exchanges: Broadcasting and Multicast
3. Topic Exchanges: Pattern-Based Routing and Hierarchies
4. Headers Exchanges and Use Cases
5. Designing Exchange and Queue Topologies for OrderFlow
6. Virtual Hosts, Namespaces, and Multi-Tenancy

Chapter 8: Message Delivery Semantics and Reliability

1. At-Least-Once, At-Most-Once, and Exactly-Once: What They Really Mean
2. Publisher Confirms: Ensuring Messages Reach the Broker
3. Consumer Acknowledgments: Manual vs Automatic, Negative Acknowledgments
4. Message Durability: Persistent Messages and Queue Durability
5. Transactional Publishing: AMQP Transactions and Trade-offs
6. Implementing Reliable Delivery in OrderFlow

Chapter 9: Advanced Messaging Patterns with RabbitMQ

1. Dead Letter Exchanges and Queues: Handling Failed Messages
2. Message Timeouts and TTL-Based Expiration
3. Delayed Message Processing with Plugins and Alternatives
4. Priority Queues and Work Prioritization
5. Queue Length Limits and Overflow Handling
6. Message Inspection and Redelivery Control

Chapter 10: RabbitMQ Clustering, High Availability, and Scaling

1. RabbitMQ Clustering: Architecture, Topologies, and Quorum
2. HA Queues and Quorum Queues: Choosing the Right Model
3. Scaling Out: Adding Nodes, Rebalancing, and Monitoring
4. Broker Upgrades and Maintenance Procedures
5. Disaster Recovery Strategies and Data Backup
6. Performance Tuning: Memory, Disk, and Erlang Considerations

Chapter 11: Spring AMQP Fundamentals

1. The Spring AMQP Abstraction: RabbitTemplate, ConnectionFactory, and Channel
2. Configuring RabbitMQ Connections in Spring Boot
3. Sending Messages: RabbitTemplate and Producer Configuration
4. Receiving Messages: RabbitListener and Consumer Configuration
5. Message Conversion and Serialization
6. Error Handling Fundamentals: DefaultErrorHandler and Beyond

Chapter 12: Building Reliable Producers with Spring AMQP

1. Publisher Confirms and Returns in Spring AMQP
2. ConfirmsCallback and ReturnCallback: Handling Broker Feedback
3. Retry Semantics: SimpleMessageConverter and RetryTemplate Integration
4. Correlation IDs and Message Tracing
5. Batching and Bulk Publishing
6. Producer Performance and Throughput Optimization

Chapter 13: Building Reliable Consumers with Spring AMQP

1. Acknowledgment Modes: AUTO, MANUAL, and BATCH
2. Concurrency Tuning: Prefetch, Consumer Threads, and Queue Partitioning
3. The DefaultMessageListenerContainer Lifecycle and Configuration
4. Consumer Error Handling: Retry, Backoff, and DLQ Routing
5. Idempotent Consumer Design
6. Graceful Consumer Shutdown and Message In-Flight Handling

Chapter 14: Message Serialization, Schema Evolution, and Compatibility

1. JSON Serialization with Jackson: Configuration and Customization
2. Avro and Schema Registry for Contract-Governed Messages
3. Protobuf and Performance-Sensitive Scenarios
4. Schema Evolution Strategies: Backward, Forward, and Full Compatibility
5. Versioning Messages and Supporting Multiple Consumers
6. Message Schema Documentation and Governance

Chapter 15: Event-Driven Design and the Outbox Pattern

1. Domain Events and Integration Events: Defining the Distinction
2. The Transactional Outbox Pattern: Theory and Implementation
3. Implementing Outbox with Spring Data and Polling
4. CDC-Based Outbox: Debezium and Change Data Capture
5. Event Publishing in OrderFlow: From Database to RabbitMQ
6. Testing Event-Driven Components

Chapter 16: The Inbox Pattern and Idempotent Processing

1. Why Idempotency Matters: Duplicate Detection and Processing
2. The Inbox Pattern: Tracking Received Messages
3. Implementing Idempotency Keys and State Stores
4. Outbox-Inbox: End-to-End Reliable Communication
5. Handling Partial Failures and Compensating Actions
6. Idempotency in OrderFlow Services

Chapter 17: Sagas and Distributed Transactions

1. Why Distributed Transactions Fail: Two-Phase Commit and Its Problems
2. Saga Pattern: Choreography vs Orchestration
3. Implementing Sagas with RabbitMQ and Spring Events
4. Compensating Actions and Rollback Semantics
5. Saga State Machines and Persistence
6. OrderFlow Saga: Implementing an Order Fulfillment Workflow

Chapter 18: Message Ordering and Sequence Guarantees

1. When Ordering Matters and When It Does Not
2. FIFO Queues and Single-Consumer Constraints
3. Partitioning by Key for Ordered Substreams
4. Sequence Numbers and Gap Detection
5. Implementing Order Guarantees in RabbitMQ
6. Ordering Trade-offs: Throughput vs Determinism

Chapter 19: Concurrency, Backpressure, and Flow Control

1. Understanding Throughput, Latency, and Saturation
2. Backpressure Mechanisms: Prefetch, Queue Limits, and Rate Limiting
3. Spring AMQP Flow Control and Consumer Throttling
4. Circuit Breakers and Bulkheads: Protecting Services
5. Implementing Flow Control in OrderFlow
6. Capacity Planning and Load Testing

Chapter 20: Security, Authentication, and Authorization

1. RabbitMQ Security: Users, VHosts, Permissions, and TLS
2. Spring Security with OAuth2 and JWT
3. Service-to-Service Authentication Patterns
4. Secrets Management: Vault, Kubernetes Secrets, and Environment Config
5. Encrypting Data in Transit and at Rest
6. Security Testing and Compliance

Chapter 21: Observability — Logging, Metrics, and Tracing

1. Structured Logging with Micrometer and Logback
2. Metrics with Micrometer: Gauges, Counters, Timers, and Histograms
3. Distributed Tracing with Micrometer Tracing and Brave/OpenTelemetry
4. Correlating Logs, Metrics, and Traces
5. RabbitMQ Metrics and Broker Visibility
6. Implementing Observability in OrderFlow

Chapter 22: Containerization, Kubernetes, and Deployment

1. Docker Images for Spring Boot Applications
2. Docker Compose for Local Development and Integration Testing
3. Kubernetes Deployments, Services, and ConfigMaps
4. RabbitMQ on Kubernetes: Helm Charts and Operators
5. Ingress, Networking, and Service Mesh Considerations
6. Deployment Strategies: Rolling, Blue-Green, and Canary

Chapter 23: Testing Strategy for Distributed Systems

1. Unit Testing Spring and RabbitMQ Components
2. Integration Testing with Testcontainers: RabbitMQ, Databases, and More
3. Contract Testing with Spring Cloud Contract
4. End-to-End Testing in an Isolated Environment
5. Testing Failure Scenarios: Network Partition, Broker Down, Slow Consumers
6. Test Infrastructure and CI Pipelines

Chapter 24: CI/CD, Automation, and Release Engineering

1. CI Pipeline Design: Build, Test, and Quality Gates
2. Container Registry and Image Tagging Strategy
3. CD Strategies and Automated Deployments
4. Environment Promotion and Feature Flags
5. Rollback Procedures and Release Management
6. The OrderFlow CI/CD Pipeline

Chapter 25: Troubleshooting, Maintenance, and Long-Term Evolution

1. Common Failure Modes and Their Symptoms
2. RabbitMQ Troubleshooting: Connections, Queues, Memory, and Disk
3. Spring Boot Troubleshooting: Memory Leaks, Thread Pools, and Timeouts
4. Incident Response and Debugging Production Issues
5. Dependency Management and Version Upgrades
6. Technical Debt, Refactoring, and Architectural Evolution

Chapter 26: The Production OrderFlow Platform

1. Full Architecture: Services, Events, and Flows
2. Production Deployment: Complete Kubernetes and Infrastructure Configuration
3. Operational Runbook: Monitoring, Scaling, and Incident Response
4. Performance Characteristics and Capacity Profiles
5. Evolutionary Roadmap: How the Architecture Could Grow
6. Lessons Learned and Key Takeaways

Conclusion

References