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World of Software > Computing > Why “Obvious” Performance Optimizations Often Backfire: Lessons From Systems Serving 50M+ Requests | HackerNoon
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Why “Obvious” Performance Optimizations Often Backfire: Lessons From Systems Serving 50M+ Requests | HackerNoon

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Last updated: 2026/01/26 at 8:57 AM
News Room Published 26 January 2026
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Why “Obvious” Performance Optimizations Often Backfire: Lessons From Systems Serving 50M+ Requests | HackerNoon
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Theoretical optimizations can backfire in practice. We learned this the hard way at DoorDash when a “smart” HashMap change made latency worse. After years optimizing 50M+ monthly requests, here’s what actually works: measure tail latencies not averages, layer your caching with jittered TTLs, profile real workloads instead of trusting Big O, and treat performance as a practice not a project. Your intuition about what’s slow might probably be wrong.

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