Auto-scaling
Let a control loop add and remove capacity in response to live demand — so you pay for load you actually have, not load you might one day see, and the system rides out spikes without a human awake to notice.
Not another patterns glossary. Each entry tells you when the pattern is the wrong choice, walks through working code, and links a live demo — so you can judge it before you bet a quarter on it.
Let a control loop add and remove capacity in response to live demand — so you pay for load you actually have, not load you might one day see, and the system rides out spikes without a human awake to notice.
Run two identical production environments, deploy to the idle one, and cut over by flipping a router — so release and rollback are a single instant switch, and the database migration is the part that actually bites.
Lazy-load data into a cache the application controls, keep the database as source of truth, and treat invalidation as the hard part — the stampede and the stale-write race — with a correct TypeScript loader.
How services find each other when instances come and go. Client-side vs. server-side discovery, the registry as source of truth, and why health checking is the hard part — with a correct TypeScript client-side resolver.
A single, hardened entry point for your microservices: centralize routing, auth, TLS, and rate limiting so clients stay simple and services stay focused.
Stop cascading failures from taking down your system. How the Circuit Breaker pattern trades slow timeouts for fast, honest failure — with a correct TypeScript implementation.