Overview of Docker Engine

Docker Engine functions as a hypervisor that enables the creation of virtual machines (VMs), referred to as containers. Essentially, a hypervisor allows for the virtualization of environments, with Docker representing a more advanced form of this technology.

When development teams share applications with testing and production teams, they often face issues related to dependencies. Sending an entire operating system setup with all necessary software is impractical, which is where VMware's virtual machine images become essential.

Importance of Docker Engine

Virtual machines (VM 1, VM 2, and VM 3) draw resources from their host system, utilizing RAM and storage.

For instance, if we aim to create four VMs, each allocated some RAM and storage, and then decide to introduce a fifth VM (VM 5), the existing resources may not suffice.

Docker resolves this resource allocation issue by creating containers instead of traditional VMs. Containers draw resources from the host while running and relinquish them once the task is complete, allowing for the creation of multiple lightweight containers.

Virtualization Through Operating Systems

Containers require an operating system, but they can share the host OS if it is UNIX-based, enabling operating system-level virtualization. Docker operates as a Platform as a Service (PaaS) utilizing this approach, while VMware functions on a hardware-level virtualization basis.

For example, if our host OS is Ubuntu and we want to create a container running Kali Linux, Docker fetches a minimal Kali Linux image from Docker Hub, significantly reducing the overall size of the image due to shared components from the host OS.

What is Docker Hub?

Docker Hub serves as a repository for container images, allowing users to push and pull images to and from their machines, regardless of location.

Docker Architecture

The architecture of Docker revolves around containers crafted by developers, following a layered file system approach.

Installing Docker on Linux and Command Usage

Installing Docker on any server, including Linux, macOS, and Windows, is straightforward. While Docker operates optimally on Linux, it is compatible with other operating systems. When downloading Docker for Windows, it also includes necessary Linux files.

To install Docker on a Linux terminal, use:

yum install docker

After installation, confirm Docker's installation with:

which docker

To check the version of Docker:

docker -V

To monitor the service status:

service docker status

To initiate the service:

service docker start

Verify that Docker is now running.

To check installed images:

docker images

To view running containers:

docker ps

To see both running and stopped containers:

docker ps -a

Containerization, Dockerfile Creation, and Image Generation

To download an Ubuntu image in Docker, run:

docker run -it ubuntu bin/bash

After exiting the container, subsequent attempts to run the Ubuntu image will create a new container with a distinct ID.

You can check the available images in Docker with:

docker images

To examine all Ubuntu images on Docker Hub:

docker search ubuntu

To assign a name to the container when executing the image:

docker run -it --name amitdocker1 ubuntu /bin/bash

To verify the container's name:

docker ps -a

To delete a container, stop and exit it first:

docker rm amitdocker1

Docker Image Creation

To create an image from a container, use:

docker commit amitdocker1 amitimage1

Now, when you run the command, it will pull the image from your local machine rather than Docker Hub:

docker run -it --name amit1 amitimage1 /bin/bash

Advantages and Disadvantages

Advantages

• No pre-allocation of RAM required.
• Docker facilitates the creation of container images that can be utilized throughout the deployment process.
• Cost-effective and lightweight.

Disadvantages

• Lack of cross-platform compatibility; applications designed for Docker on Windows cannot run on Linux, and vice versa.
• Not ideal for applications needing a rich GUI.
• Managing numerous containers can be challenging.
• Best suited when development and testing OS are identical; otherwise, VM is recommended.
• No built-in solutions for data recovery and backup.