Containerization with Docker

This topic covers containerization. You write Dockerfiles to build layered images, run and manage containers, distribute images through registries, orchestrate multi-container applications with Compose, and optimise images with multi-stage builds.

Relation 1 —

Write this relation with symbols exactly as in Gene Kim Devops Handbook — Standard reference before substituting numbers. Examiners award partial marks for a correct setup even when arithmetic slips.

Relation 2 —

Write this relation with symbols exactly as in Gene Kim Devops Handbook — Standard reference before substituting numbers. Examiners award partial marks for a correct setup even when arithmetic slips.

Relation 3 —

Write this relation with symbols exactly as in Gene Kim Devops Handbook — Standard reference before substituting numbers. Examiners award partial marks for a correct setup even when arithmetic slips.

Containers solve the "works on my machine" problem by bundling the application with its exact dependencies into an image that runs identically anywhere. The image is built as a stack of read-only layers — each Dockerfile instruction adds one — which are cached and shared across images to save space and speed builds; a container simply adds a thin writable layer on top. Unlike a VM, a container shares the host kernel and is isolated only by namespaces (separate views of processes, network, filesystem) and cgroups (resource limits), making it lightweight and fast to start. Registries distribute images between build and run environments, and multi-stage builds keep the final image small by discarding build-time tooling.

State assumptions explicitly before using any relation for containerization with docker — steady state, uniform properties, linear elastic material, ideal gas, incompressible flow, etc., as applicable.

Wrong assumptions invalidate the entire solution even when the formula is correct. In DevOps viva and GATE descriptive questions, listing valid assumptions often earns separate marks.

1. Read the question and list given data with SI units (common in DevOps papers).
2. Draw a neat labelled diagram where applicable — examiners in Indian universities award diagram marks even when arithmetic slips.
3. Identify which relation from this topic applies to containerization with docker.
4. Use equation 1: .
5. Use equation 2: .
6. Substitute values, compute, and verify units and sign (direction).
7. State conclusion in one line — e.g. safe/unsafe, stable/unstable, feasible/infeasible.

Containerization with Docker appears in modern software delivery. In Indian it software curricula this topic is tested because it connects theory to CI/CD and infrastructure as code.

GATE and semester exams often combine containerization with docker with earlier units — revise prerequisites before attempting mixed problems.

Industry interview panels sometimes ask: "Where did you use containerization with docker?" — answer with a lab, mini-project, or plant visit example if possible.

Students confuse images (immutable templates) with containers (running instances), think containers include a full OS kernel, and write inefficient Dockerfiles that bust the layer cache. Forgetting that container writable-layer data is ephemeral unless a volume is used is a common data-loss trap.

Before attempting containerization with docker problems, confirm you can:

1. Containers isolate via namespaces and cgroups, sharing the kernel
2. A registry stores and distributes images
3. Multi-stage builds shrink the final image

Revise the solved examples in Gene Kim Devops Handbook — Standard reference and one previous-year GATE or university paper for this unit.