Practice · 2011–2022 · Cloud Scale
Event sourcing everywhere
Store every state change as an eternal log. Audit gold for some domains; operational nightmare as a default.
Why Event sourcing everywhere became a costly fad
Event sourcing everywhere failed because replay, versioning, and snapshot strategies are senior-engineering work disguised as a pattern. GDPR deletes and "what is the current state?" queries hurt when the log is the database. It stuck where audit law mandates it; it failed everywhere else.
Cost of the fad
What Event sourcing everywhere cost
Immutable event logs for domains that needed UPDATE statements. Replay debugging sounded elegant until production needed GDPR deletes and schema migrations on millions of events.
Compare with
Related
Practice · 2010–2020
CQRS everywhere
Command/query separation as default architecture. Right for high-scale event domains; absurd for to-do lists.
$ Teams split read and write models for CRUD apps that never needed separate projections. Double the schemas, double the bugs, double the on-call surface — for a blog admin.
Platform · 2011–now
Apache Kafka
Durable log as nervous system. Event-driven architecture with real operational teeth.
Architecture · 2012–2023
Microservices Everywhere
Independent deployability as religion. Correct for some; ruinous cargo-cult for most. Consolidation and monolith return are the 2020s epilogue.
$ 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.