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COURSE TOPIC

Docker Containers: Images, Configuration, and Volumes

Learn how container images package an application and how runtime configuration, storage, and networks affect a container.

Part of course Cloud Computing & DevOps Course
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Difficulty Level
Beginner to intermediate
Estimated Learning Time
90 minutes
OVERVIEW

About Docker Containers: Images, Configuration, and Volumes

Containers provide a repeatable way to package an application and its dependencies. Understanding the difference between an image and a running container helps make development and deployment more predictable.

LEARNING OUTCOMES

What You Will Learn

  • Explain images, containers, registries, and layers.
  • Build and run a simple containerized application.
  • Keep configuration and secrets outside the image.
TOPIC GUIDE

Learn Docker Containers: Images, Configuration, and Volumes

Image versus container

An image is a packaged template; a container is a running instance created from that image. A registry stores and distributes images. Tags help identify versions, but production workflows should also consider immutable digests and provenance.

Build small, understandable images

A Dockerfile describes build steps. Keep only necessary runtime dependencies, use a suitable base image, and avoid copying local credentials or unrelated files into an image. Review what each layer contains before publishing.

Configure at runtime

Environment-specific values should be supplied through an approved runtime configuration mechanism. Do not bake secrets into a Dockerfile, image layer, or public repository. Use persistent volumes only when data must outlive a container and backup needs are understood.

Plan lifecycle and resource use

Know how to start, inspect, stop, and remove test containers and images. Containers still consume host resources and require updates, permissions, network boundaries, and monitoring.

PRACTICAL EXAMPLE

Example / Code

Example 
FROM python:3.12-slim
WORKDIR /app
COPY requirements.txt ./
RUN pip install --no-cache-dir -r requirements.txt
COPY . .
CMD ["python", "app.py"]
TRY IT YOURSELF

Practice Task

Apply what you learned with a practical activity.

Containerize a small sample app. Document how to build and run it, which values are supplied at runtime, what data needs persistent storage, and how to remove the test resources safely.

TOOLKIT

Tools & Technologies

  • Docker
  • Dockerfile
  • Container registry concepts
CONTINUE LEARNING

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COURSE TOPICS

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Cloud Computing Foundations and Architecture

Understand cloud service models, deployment choices, regions, reliability concepts, and shared responsibility before designing a deployment.

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Linux and Networking Basics for Cloud Deployment

Use foundational Linux and networking concepts to inspect processes, permissions, DNS, ports, and HTTP request paths.

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CI/CD Pipelines: Tests, Builds, and Safer Deployments

Design a reviewable pipeline with automated checks, build artifacts, environment approvals, deployment validation, and rollback planning.

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Infrastructure as Code with Terraform Concepts

Describe infrastructure as reviewable configuration and understand plans, state, drift, access control, and change approvals.

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Cloud Monitoring and DevOps Capstone

Combine deployment, logs, metrics, alerts, least privilege, backups, and a recovery runbook in a simulated service project.

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READY FOR THE COMPLETE COURSE?

Go Beyond Docker Containers: Images, Configuration, and Volumes

Explore the complete Cloud Computing & DevOps Course curriculum, practical training, learning path and course details.

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