1.2 seconds per request. Thousands of daily users. No bug reports — but users were feeling it. Here's the exact five-step process I used to cut response times by 87% without a rewrite.
Common causes include unindexed or N+1 database queries, blocking synchronous code, missing caching, and oversized payloads. Profiling each layer is the first step to finding the real bottleneck.
Yes. Caching frequent read queries in Redis removes repeated database round-trips and can cut response times dramatically, especially for data that changes infrequently.
Use APM tools or timing middleware and separate database, external API, and serialization time so you optimize the actual slow part instead of guessing.
Social Media Platform — read the case study
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