Docker Image vs. Container: Blueprint vs. Runtime
A Docker image is a read-only blueprint; a container is a live instance with a writable layer. You build an image once in CI and run many containers from it in production. The footgun is mutating a running container without updating the image recipe.
A Docker image is a frozen blueprint that packages code, dependencies, and libraries into an artifact. A container is a live, isolated process spawned from that image with a thin writable layer on top. In MLOps, you build one training image with pinned Python and CUDA versions, then launch hundreds of ephemeral containers for parallel hyperparameter sweeps. The footgun is treating containers as pets: installing packages inside a running container and never rebuilding the image means your environment drifts and becomes impossible to reproduce.
Read the original → direct-llm://dockerimagevscontainer
- #docker
- #containers
- #mlops
- #infrastructure
- #reproducibility
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