Containerization Fundamentals Questions

Foundational knowledge of container technology, focused on Docker and container workflows. Topics include what containers are and how they differ from virtual machines, container images and registries, building and reading Dockerfiles, running containers, volume and file system mounting, basic container networking, image layering and size optimization, and common use cases such as reproducible deployments for machine learning and microservices. Candidates should be able to explain the container lifecycle, why containerization matters in DevOps, and demonstrate simple hands on tasks like writing a basic Dockerfile and running containers locally.

MediumTechnical

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Explain how Docker build cache and image layering work. Given this Dockerfile snippet, suggest a reordering to speed iterative rebuilds during ML model development:

FROM python:3.9-slimCOPY . /appWORKDIR /appRUN pip install -r requirements.txtCOPY model /app/modelCMD ["python", "server.py"]

HardSystem Design

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Design a CI strategy to ensure images built for ML services are reproducible, scanned for vulnerabilities, and automatically promoted through dev->staging->prod registries. Include steps, gating criteria, and how to handle emergency security patches for base images.

HardTechnical

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Describe how container runtime security features such as seccomp, AppArmor, and user namespaces help harden ML containers. Provide an example of a seccomp profile or a docker run flag that reduces attack surface for model serving containers.

HardTechnical

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A model serving container consumes high CPU intermittently; describe how you would profile and optimize CPU usage both at the application level (model inference code) and container level (cgroups, CPU limits, scheduling). Provide specific tools and configuration flags you would use.

MediumTechnical

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Explain how an image's Dockerfile ordering and use of .dockerignore affect build context size and speed. Provide an example .dockerignore that would be useful in a typical ML project and explain why each entry is included.

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