Introduction
Go’s concurrency model is powerful, but building distributed systems requires more than basic goroutines and channels. You need patterns that handle coordination across services, manage failures gracefully, and scale under load.
Beyond Basic Concurrency
Most Go tutorials cover the basics: launching goroutines, sending values through channels, and using select statements. But real distributed systems face challenges like:
- Service coordination: Multiple services need to work together
- Failure handling: Networks partition, services crash, timeouts occur
- Load management: Systems must handle varying traffic patterns
- Resource coordination: Shared resources need careful management
Patterns You’ll Learn
This guide covers advanced concurrency patterns for distributed systems:
- Worker Pools: Managing goroutines efficiently without overwhelming resources
- Pipeline Patterns: Chaining operations for data processing
- Fan-Out/Fan-In: Distributing work and collecting results
- Circuit Breakers: Preventing cascade failures
- Rate Limiting: Controlling request flow
- Distributed Coordination: Consensus and leader election
When to Use These Patterns
These patterns solve specific problems in distributed systems. Use them when:
- Building microservices that need to coordinate
- Processing high volumes of data
- Handling external service dependencies
- Managing shared resources across goroutines
- Implementing fault-tolerant systems
Each pattern includes practical examples and guidance on when to apply it.