DigitalOcean: Many LLM Serving "Wins" Are Noise — One +4% Winner Wasn't Real
AI Engineer · youtube · 2026-11-12
At AI Engineer Code Summit, Rohan Pandey and Balaji Varadarajan of DigitalOcean described an optimization agent running on their AMD MI355 inference servers: it proposes vLLM and Kubernetes configs, rolls them out, measures throughput under real latency targets, and keeps winners or safely reverts.
Key takeaway: most LLM serving "wins" come from tweaking a single knob that barely maps to production hardware — one study found a +4% "winner" was just run-to-run noise. The agent is being extended to disaggregated prefill/decode serving.
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