What Nobody Tells You About Running AI Models in Docker
SMRTR summary
A 2 AM outage caused by a 14GB inference container being OOM-killed repeatedly exposed critical mistakes in how ML teams package AI workloads with Docker. Externalizing model weights, separating training and serving images, and writing health checks that verify model loading rather than just process uptime were the real fixes — not just multi-stage builds.
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