Most load testing produces a number nobody acts on. A tool is pointed at the busiest endpoint, concurrency is increased until something breaks, and a figure is recorded. The figure is real and almost useless, because it measures a scenario no user will ever create and ignores everything about how the system actually behaves under real traffic.
Start with the question rather than the tool. Useful questions are specific: can we handle the Diwali peak, which is roughly six times a normal Tuesday. What breaks first as traffic grows. Does the system recover on its own after a spike passes. How long can we sustain twice normal load before something degrades. Each of those needs a different test, and none of them is answered by finding the breaking point of one endpoint.
The test has to look like real traffic, and this is where most attempts fall down. Real users move through journeys - browse, search, view, add, check out - in realistic proportions, with pauses between actions, against a spread of data rather than the same row repeatedly. A test that requests one product a million times measures your cache. A test with no think-time between actions applies pressure no real population produces.
Test data matters as much as the request mix. A database with a thousand rows behaves nothing like one with ten million: query plans change, indexes start mattering, and caches stop holding the working set. Load testing against a small dataset is the most common reason a system passes its test and falls over in production.
Watch the system, not only the load generator. The generator tells you response times and errors; the interesting information is inside - CPU and memory per service, database connections in use, connection pool saturation, queue depth, cache hit rate, garbage collection pauses. The point of the exercise is to learn what breaks first and why, and you cannot see that from the outside.
Two tests are worth more than a bigger one. A soak test - moderate load sustained for several hours - finds memory leaks, connection leaks and disk filling, none of which appear in a ten-minute run. And a recovery test: apply load until something fails, then stop, and see whether the system returns to health without intervention. A system that degrades under load and recovers is fine. One that stays broken after the load subsides has a queue or a pool that never drains, and that is the failure that turns a busy hour into an evening.
