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.
Ship a new version to a small slice of real traffic, compare it against a baseline on live signals, and promote or roll back on evidence — progressive delivery where the release decision is made by data, not by nerve.
The default data-access pattern as a deliberate choice, not an absence of one: what one shared model buys you, the four failure modes that eventually break it, and the signals you have outgrown it.
Spreading traffic across replicas is easy; choosing well under real conditions is not. Algorithms, L4 vs L7, health checks, session affinity, and why the best-informed strategy often fails worst.
The first resilience pattern everyone writes and the one most often written wrong: why naive retries amplify outages, and how backoff, jitter, budgets, and idempotency turn a retry into a safe one.
The textbook protocol for atomic commit across multiple resources: how prepare-then-commit works, why a coordinator crash can block participants indefinitely, and where 2PC is still the right answer.
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.