A hands-on loop to learn inference engineering: vLLM in Docker, measuring TTFT and batching
malliktwts · x · 2026-09-15
A quoted post lays out a practical starter path for inference engineering: deploy Kubernetes in Docker, write a vLLM manifest, pull and serve a model through a gateway, then send real requests and measure TTFT and tokens/sec. Add concurrency to watch batching happen, and monitor GPU memory and KV cache under load — changing one variable at a time. The author argues this small loop teaches a surprising amount about serving LLMs.
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