// Topics / Microservices
Microservices
Definition
Microservices coverage in this archive spans 11 posts from Jan 2016 to Sep 2022 and deals with structural tradeoffs: coupling, failure boundaries, and long-term change cost. The strongest adjacent threads are architecture, go, and monolith. Recurring title motifs include microservices, patterns, probably, and need.
Key claims
- Most pieces recommend choosing the simplest architecture that can be operated confidently.
- Early posts lean on microservices and probably, while newer posts lean on patterns and monolith as constraints shifted.
- This topic repeatedly intersects with architecture, go, and monolith, so design choices here rarely stand alone.
Practical checklist
- Define failure domains and data boundaries before introducing additional services or protocols.
- Start with the newest post to calibrate current constraints, then backtrack to older entries for first principles.
- When boundary questions appear, cross-read architecture and go before committing implementation details.
Failure modes
- Breaking systems into many parts without clear ownership of cross-service behavior.
- Choosing architecture for trend alignment rather than workload constraints.
- Applying guidance from 2016 to 2022 without revisiting assumptions as context changed.
Suggested reading path
- Start here (current state): Testing Microservices Without Losing Your Mind
- Then read (operating middle): Your Monolith Is Probably Fine
- Finish with (foundational context): Why Microservices Aren’t Always the Answer
Related posts
- Testing Microservices Without Losing Your Mind
- Distributed Systems Patterns I Keep Reaching For
- GraphQL Federation: I’m Still Skeptical
- API Gateway Patterns That Actually Work
- gRPC Patterns That Actually Work in Production
- Your Monolith Is Probably Fine
- Istio: Powerful, Painful, and Probably More Than You Need
- Securing Microservices: What Actually Works
References
11 entries tagged “Microservices”