Architecture · 2012–2023 · Cloud Scale
Microservices Everywhere
Independent deployability as religion. Correct for some; ruinous cargo-cult for most. Consolidation and monolith return are the 2020s epilogue.
Why Microservices Everywhere became a costly fad
Microservices failed as a default because network boundaries multiply failure modes faster than team autonomy. Netflix needed it; your CRUD shop needed a modular monolith and sleep. The fad cost was paying senior distributed systems salaries to ship slower.
Cost of the fad
What Microservices Everywhere cost
Teams split 4-person products into 40 services, then hired SREs to babysit the mesh. Many later consolidated — after years of distributed tracing invoices and on-call trauma. See case studies on premature microservices and big-bang cutovers for named failure modes.
Case studies
- Big-bang microservices cutover weekend — Weekend cutover rollback; months of dual-run and incident debt
- Mid-market CRUD shop splits into forty repos — 3× infra spend; velocity flat for two years
- AI codebase rewrite pilots that shipped nothing — Six-figure LLM API and SI costs; production cutover: zero
- Service mesh before the traffic arrived — Platform team of six; product incidents from mesh misconfig outpaced actual load issues
Patterns
Compare with
Related
Architecture · 2003–2015
Enterprise SOA
Reuse via shared services — in theory. In practice: central buses and political ownership fights.
$ ESBs, governance boards, and "service portfolios" burned seven-figure programs. Many orgs got distributed monoliths with worse latency and a permanent integration team.
Platform · 2014–now
Kubernetes
Container orchestration that became the cloud's OS. Overkill for many; unavoidable for many others.
Architecture · 1970–now
Modular monolith
One deployable with clear boundaries. The unfashionable default that keeps shipping while microservices argue about ownership.
Architecture · 2017–2024
Service mesh everywhere
Sidecar proxies for every microservice. Netflix problems with startup headcount.
$ Istio sidecars on three-service startups burned SRE headcount on mTLS ceremonies nobody could debug. Many teams ripped mesh out before the observability dashboard paid rent.