Learn how to improve the performance of your vLLM deployments with a diagnostic workflow that isolates latency issues and server saturation. Discover the key metrics to monitor and techniques to alleviate memory pressure.

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Red Hat Developer

A diagnostic workflow for triaging vLLM inference performance issues in production. Covers five steps: isolating latency symptoms (TTFT vs ITL), detecting server saturation via queue metrics, evaluating VRAM and KV cache health, analyzing request sequence lengths, and reviewing distributed inference strategies. Includes concrete Prometheus queries, log examples, and remediation paths such as quantization (FP8), speculative decoding, tensor parallelism tuning, and right-sizing models. Emphasizes defining workload goals (throughput vs latency vs bursty) before diving into metrics.

5 steps to triage vLLM performance

Before you start: Define what success looks like