Practice · 2011–now · Cloud Scale
Event sourcing everywhere
Store every state change as an eternal log. Audit gold for some domains; operational nightmare as a default.
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
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.
Context
Split everything, then pay for the glue
Hyperscale patterns escaped the companies that needed them. Containers unified packaging; Kubernetes became the cloud OS; microservices and NoSQL were sold as defaults. Mobile-first stuck because screens changed. Cargo-cult distributed systems stuck around as invoices. The durable move was packaging and ops maturity — not rewriting every app into a mesh.
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–now
Microservices Everywhere
Independent deployability as religion. Correct for some; ruinous cargo-cult for most.
$ 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.