Docker

Container packaging for reproducible ML and AI deployments.

Maturity level: L3 — Can Deploy

Six perspectives on Docker

Roadmap

First container skill — learn before Kubernetes.

Architecture

Packages models, APIs, and workers into portable units.

Company

Near-universal expectation for backend and platform-oriented roles.

Projects

Dockerize every API and training job you build.

Interview

Explain images, layers, and production Dockerfile best practices.

Career

Foundation for all production AI engineering paths.

What & Why

What: Platform for building, shipping, and running applications in containers.

Why: Eliminates 'works on my machine' — essential for ML model serving and CI/CD.

Build this

Containerize a FastAPI ML service with optimized image layers.

Production reality

  • ! Large images slowing deploys
  • ! Wrong base image
  • ! Secret leakage in layers
  • ! Volume permission issues

Interview preparation

  • Image layering and cache optimization
  • Multi-stage builds for Python ML apps
  • Container security basics

Connected skills

KubernetesLinuxCI/CD

Explore Docker in the interactive universe or train with live cohorts.

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