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backend
6 postsRate Limiting at Scale: Choosing the Right Throttling Algorithm
Why in-memory rate limiting silently breaks under horizontal scaling, and how token bucket, sliding window and fixed window algorithms trade off in production.
rate-limitingredisdistributed-systemsbackendCache invalidation: solving stale data and stampede problems
An engineering look at TTL, event-based invalidation, versioning and single-flight patterns, and how cache stampede can take down your origin in production.
cachingdistributed-systemsredisbackendRequest Logging: Tracing Production Requests with Correlation IDs
Why correlation IDs and structured logs are essential for request logging. A practical look at Fastify, Express, pino, and AsyncLocalStorage for production debugging.
loggingnodejsobservabilityfastifyWhy LLM Apps Must Be Engineered as Distributed Systems
A production AI app broke under load—not because of the model, but missing queues, caching, retries and observability. Backend engineering is the real differentiator.
ai-engineeringdistributed-systemsllmbackendPostgreSQL Batch UPSERT with CTE: From 90 Seconds to 5
An email sync process with audit history was rewritten from separate queries into a single PostgreSQL CTE, cutting 100k-row processing time from 90 seconds to 5.
postgresqlsqlgodatabase-performanceSolo Dev Built a Sharded Go Library with WAL Instead of Kafka
A solo developer built Flux, a sharded, WAL-backed Go library for batching database writes instead of running Kafka or Redis, ensuring crash safety.
godatabasesconcurrencyperformance