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Distributed Systems & Microservices

Build scalable, resilient systems that communicate reliably across the network

Overview​

Building distributed systems requires understanding fundamental constraints that don't exist in monolithic applications. This section covers the core principles, communication patterns, and resilience strategies essential for designing systems that scale horizontally while maintaining reliability.

What You'll Learn​

Distributed Systems Landscape

Three Core Pillars​

1. Fundamentals​

Understand the theoretical constraints and practical realities of distributed systems. The CAP theorem, consistency models, and idempotency form the foundation for all architecture decisions.

Key Concepts:

  • Eight fallacies every distributed systems engineer must reject
  • CAP theorem and PACELC framework for trade-off analysis
  • Consistency models from strong to eventual
  • Failure modes and partition tolerance strategies
  • Idempotency for safe retries

2. Communication​

Design effective inter-service communication that balances latency, throughput, and complexity. Choose between synchronous and asynchronous patterns based on your consistency and coupling requirements.

Key Concepts:

  • REST, gRPC, GraphQL, WebSockets for different scenarios
  • Synchronous vs asynchronous communication trade-offs
  • Message queues, topics, and event streams
  • API gateways for aggregation and routing
  • Service discovery for dynamic environments
  • Service mesh for infrastructure concerns
  • Webhooks and callbacks for reactive systems

3. Resilience​

Build systems that gracefully degrade when failures occur. Implement timeouts, retries, circuit breakers, and other patterns that transform cascading failures into isolated incidents.

Key Concepts:

  • Timeouts, retries, and exponential backoff strategies
  • Circuit breakers to prevent cascading failures
  • Bulkhead isolation for fault containment
  • Rate limiting and throttling for resource protection
  • Load shedding and backpressure handling
  • Health probes for failure detection
  • Leader election and consensus algorithms

Getting Started​

Start with the Fundamentals section to understand the constraints you're operating within. Then explore Communication patterns appropriate for your architecture. Finally, layer in Resilience patterns to handle the inevitable failures that distributed systems encounter.

Core Principles​

  1. Embrace Failure: Distributed systems fail. Design for it, not around it.
  2. Understand Trade-offs: Every architectural decision trades consistency, availability, and latency. Know what you're trading.
  3. Be Explicit About Semantics: Make timeouts, retries, and idempotency explicit in your design.
  4. Observe Everything: You cannot debug what you cannot observe. Invest in observability.
  5. Simplify When Possible: Distributed systems are complex. Eliminate unnecessary complexity first.

Quick Reference​

ConcernPatternUse When
ConsistencyStrong consistencyUpdates must be immediately visible
Eventual consistencyTemporary inconsistency is acceptable
CommunicationSync (REST/gRPC)Low latency, tightly coupled, request-response
Async (Queues/Topics)High latency acceptable, decoupled, event-driven
FailureTimeoutsPreventing resource exhaustion
Circuit BreakerPreventing cascading failures
BulkheadContaining failures to specific services
Rate LimitingProtecting shared resources

Next Steps​

  1. New to distributed systems? Start with Fallacies of Distributed Computing
  2. Designing APIs? Jump to API Styles
  3. Building resilient systems? Explore Timeouts and Retries
  4. Want to understand trade-offs? Read CAP & PACELC Theorems

References​

  • Vogels, W. (2008). "Eventually Consistent". Communications of the ACM.
  • Brewer, E. A. (2000). "Towards Robust Distributed Systems". PODC Keynote.
  • Coulouris, G., Dollimore, J., Kindberg, T., & Blair, G. (2011). "Distributed Systems: Concepts and Design" (5th ed.).
  • Kleppmann, M. (2017). "Designing Data-Intensive Applications".