Correlating client metrics with server, DB, and JVM evidence to locate a bottleneck rather than guess.
3 questions in QA & Testing.
A launch is a transient, not a steady state: users arrive in the same minutes, against cold caches, mostly doing sign-up writes and retrying as it slows. A typical load test ramps gently, uses a closed workload, stubs third parties, runs a smaller fleet and measures in ways that hide stalls.
Stop the bleeding first by rolling back or disabling the suspect path, then find the cause by profiling the saturated process rather than by reading the diff, because a profile names the hot function directly while forty commits offer forty plausible stories. Use this performance analysis answer to show the decision, trade-off, and evidence rather than a memorised definition.
Read the throughput curve first: if throughput has flattened while latency rises, you are queueing behind a saturated resource, and the job is to find which one by walking utilisation and saturation from the load generator through the app tier to the database.