Auto-scaling promised to eliminate the guesswork of capacity planning. Set your rules, define your metrics, and let the cloud handle the rest. At least, that’s how it looks on the slide decks. In practice, scaling rules rarely behave the way you expect. They lag,...
GraphQL changed how frontends consume data—and in doing so, it changed how APIs fail under pressure. Unlike REST, where each route defines what data returns, GraphQL inverts control. The client decides what fields to fetch, how deep to traverse, and how often to...
Nobody likes a ticketing crash at 9AM. Yet it happens all the time—concert tickets vanish, airline sites stall, checkout screens freeze. Behind every failed ticket drop or booking surge lies the same culprit: a system unprepared for high concurrency. High concurrency...
When infrastructure disappears, so do the assumptions that performance engineers rely on. Serverless computing—via AWS Lambda, Azure Functions, and Google Cloud Functions—promises infinite scalability and zero operations. But in practice, it replaces the steady-state...
Most load tests measure performance in a vacuum. They run inside pristine cloud networks, milliseconds away from the servers they’re testing. The numbers look great, until users connect from real devices, on real networks, and everything slows down. Latency is the gap...
For years, load testing meant hammering APIs. Tools like JMeter sent thousands of lightweight HTTP requests to measure throughput and latency. And it worked—until applications stopped being simple request/response systems. Modern web apps are now dynamic frontends...
