liveBook · Manning

Container image

As explained in Machine Learning Platform Engineering

A Docker image is a packaged, executable filesystem containing an application and its dependencies for creating containers.

A container image is a lightweight, standalone, executable package containing an application, its dependencies, libraries, and configuration. A container is a runnable instance of that image. section 3.2.3

Use images to make application delivery reproducible and operationally manageable:

  • Build an image from packaging instructions in a Dockerfile. section 3.2.3
  • Assign tags such as v1, v2, or a Git commit ID to distinguish versions and deployment variants. section 3.2.3
  • Push the image to a container registry so a server can retrieve and run it. section 3.2.3
  • Customize notebook images with runtimes, dependencies, and configuration compatible with Kubeflow. section 7.1.5

Build and run an application image

Build hello-joker:v1 with `docker build . -t hello-joker:v1`, then run it with `docker run -it -p 8081:8083 hello-joker:v1`. The application becomes available through the host port at localhost:8081. section 3.2.3

Figure 3.3 Process of building the Docker image from the local desktop and pushing it to the container registry, which is where a server retrieves the image and runs it as a container
A diagram of a container register

AI-generated content may be incorrect.

Trace the operational path from local image construction through registry storage to server-side container execution. section 3.2.3

How Machine Learning Platform Engineering covers it

How deep it goes
Explains construction, tagging, execution, registry storage, and notebook-image layers without detailing Dockerfile instructions.
Examples
Uses hello-joker commands, port mapping, registry pushes, and custom Kubeflow notebook layers.
What it assumes
Assumes Dockerfile packaging instructions and introduces image construction, tagging, execution, and registry workflows.
What you can do after
Build and run tagged Docker images, publish them to registries, and configure custom Kubeflow notebook images.
How it connects
Connects Dockerfiles, containers, container registries, Kubernetes, Kubeflow, Jupyter, and code-server.

Also explained in

Compare how 25 books explain container image →

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Machine Learning Platform Engineering. The section links point to the parts of the book it draws on.