After this lesson, you will be able to: Explain what containers are, the problem they solve, and how Docker compares to VMs.
Containers ship the entire runtime your app needs, OS libs, dependencies, the binary, as one immutable image. Same image runs identically on your laptop, CI, staging, and prod. That's the deploy story modern engineering is built on.
This is a free introductory lesson. No purchase required.
'Works on my machine.' Software depends on a specific Python version, a specific OpenSSL, a specific environment variable. Every server is slightly different; every deploy risks a mismatch. Containers package the app + every dependency into a single immutable image. The same image runs everywhere; the host only provides the kernel. Bonus: containers boot in seconds vs minutes for VMs; you can run dozens on one machine.
VM: each instance has its own full OS (kernel + userland). Big, slow to start, strong isolation. Hypervisor (VirtualBox, VMware, KVM) emulates hardware. Container: shares the host kernel; only userland is isolated. Tiny (often <50MB), starts in milliseconds, weaker isolation. Docker engine manages them. Use VMs for hard-multi-tenant isolation (running untrusted code). Use containers for everything else.
Pick the path for your laptop. On servers, install via package manager.
macOS / Windows: install Docker Desktop from docker.com (includes Docker engine + CLI + GUI)
Ubuntu: follow docs.docker.com/engine/install/ubuntu (apt with their repo)
Fedora / Rocky: docs.docker.com/engine/install/fedora
After install, verify: docker version ; docker run hello-world
If 'permission denied': sudo usermod -aG docker $USER, then log out + back in
Every modern web stack ships in containers. Every DevOps / SRE / Platform job description names Docker. Kubernetes (the next sub-track) is orchestration on top of containers. AWS ECS / Fargate are container services. CI/CD pipelines build container images. If you skip this sub-track, the rest of DevOps doesn't make sense.
Pick the technical reason.