Distributed Systems
GDPR Deletion in Event-Driven Systems
Deleting a user across many services is a fan-out problem with a nasty twist: what your deletion event means. Requested or executed changes everything.
#distributed-systems
10 articles
Distributed Systems
Kafka Partitions, Retention, and Compaction
Three Kafka settings decide throughput, cost, and whether replay works: partition count, retention, and cleanup policy. How to choose each deliberately.
Distributed Systems
Kafka Topic Naming and Governance
Ad-hoc Kafka topics become an unnavigable mess. A naming convention plus a single canonical registry keeps an event bus legible as it grows past 50 topics.
Distributed Systems
The Transactional Outbox Pattern
Writing to your database and publishing an event are two operations that can't share a transaction. The outbox pattern fixes that, and when to skip it.
Distributed Systems
Structured Logging at Scale
Plain-text logs are ungreppable at scale. Structured logging makes logs queryable, but volume and cost bite back. How to log structured, useful, and affordable.
Distributed Systems
Notification Fanout Architecture
Notification fanout comes down to fan-out-on-write vs on-read, and the celebrity problem that breaks the naive choice. The hybrid design that scales, explained.
Distributed Systems
Kafka Replay Strategy Without Duplicate Events
Replaying a Kafka topic re-delivers events, so duplicates are guaranteed unless consumers are idempotent. The safe replay playbook: dedup, offsets, and isolation.
Distributed Systems
Protobuf Schema Evolution Without Breaking Clients
Protobuf schema evolution has clear rules: keep field numbers stable, reserve removals, add not mutate. The safe-vs-breaking change cheat sheet and why.
Distributed Systems
gRPC Across Languages: Production Lessons
gRPC across languages promises neutral RPC. In production the gaps are real: load balancing, deadlines, status codes, and schema evolution. The fixes.
Microservices
Why Language Boundaries Break Polyglot Microservices
Polyglot microservices break at the seams, not inside services. The 5 cross-language failure modes (deadlines, cancellation, errors, types, connections) and fixes.