Running Docker on Linux: Installation and Configuration

Installing and configuring Docker on Linux requires ensuring that the system is 64-bit and kernel version 3.10 and above, use the command "sudo apt-get update && sudo apt-get install docker-ce docker-ce-cli containerd.io" to install, and verify with "sudo docker run hello-world". Docker uses the namespace and control groups of the Linux kernel to achieve container isolation and resource limitation. The image is a read-only template, and the container can be modified. Examples of usage include running an Nginx server and creating images with custom Dockerfiles. Frequently asked questions such as permissions and network issues can be resolved by joining Docker user groups and checking network configuration. Optimization suggestions include mirror optimization, resource management, and log management.

introduction

Over the past few years, Docker has become synonymous with containerization technology, which greatly simplifies the deployment and management of applications. Running Docker on Linux can not only take advantage of the powerful functions of the operating system, but also give full play to the advantages of Docker. Through this article, you will learn how to install and configure Docker on Linux, learn about some pitfalls I personally have stepped on during use, and how to optimize the Docker experience.

Review of basic knowledge

Docker is an open source containerized platform that allows developers to package applications and their dependencies into a portable container that can run in any Docker-enabled environment. As a native environment of Docker, Linux provides rich functions and tools to support Docker's operation.

On Linux, Docker mainly relies on features of the Linux kernel, such as namespaces and control groups, which enable containers to run independently and limit their resource usage.

Core concept or function analysis

Docker installation and configuration

To install Docker on Linux, you need to make sure your system meets the following conditions:

• 64-bit operating system
• Linux kernel version 3.10 and above

For most modern Linux distributions, such as Ubuntu, Debian, CentOS, etc., installing Docker is very simple. You can install Docker Engine using the following command:

 sudo apt-get update
sudo apt-get install docker-ce docker-ce-cli containerd.io

After the installation is complete, you can verify that Docker is working properly by following the following command:

 sudo docker run hello-world

This command will download and run a simple Docker image, and if everything works, you will see a welcome message.

How Docker works

Docker works based on the containerization technology of the Linux kernel. Each Docker container is a separate process, but it runs in an isolated environment. This environment is provided by Linux namespaces and control groups, ensuring that each container does not affect other containers.

The Docker image is a read-only template that contains the application and its dependencies. A container is a writable layer launched from the image. You can modify the container, but these modifications will not affect the original image.

Example of usage

Basic usage

Let's start with a simple example showing how to use Docker to run an Nginx web server:

 docker run --name my-nginx -p 8080:80 -d nginx

This command starts an Nginx container and maps the container's port 80 to the host's port 8080. You can view Nginx's welcome page by visiting http://localhost:8080 .

Advanced Usage

In actual projects, you may need to create your own Docker image to customize the application's running environment. Let's look at a simple Dockerfile example:

 FROM ubuntu:20.04

RUN apt-get update && apt-get install -y python3 python3-pip
COPY . /app
WORKDIR /app
RUN pip3 install -r requirements.txt
CMD ["python3", "app.py"]

This Dockerfile will start from the Ubuntu 20.04 image, install Python and pip, copy the files in the current directory to the /app directory in the container, set the working directory to /app, install the dependencies, and finally run app.py

Common Errors and Debugging Tips

When using Docker, you may encounter some common problems, such as permissions, network problems, etc. Here are some common errors and their solutions:

• Permissions issue : If you encounter permission errors when running Docker commands, you can add the current user to the Docker user group:

   sudo usermod -aG docker $USER

  Then log in to the system again.

• Network Problem : If the container cannot access the network, it may be due to Docker's network configuration problem. You can use docker network ls and docker network inspect commands to check and debug network configuration.

Performance optimization and best practices

In practical use, it is very important to optimize Docker's performance and follow best practices. Here are some of my personal experiences when using Docker:

• Mirror optimization : minimize the size of the image, which can be achieved through multi-stage builds. For example:

   FROM golang:1.16-alpine AS build
  WORKDIR /app
  COPY . .
  RUN go build -o myapp
  
  FROM alpine:latest
  COPY --from=build /app/myapp /myapp
  CMD ["/myapp"]

  This way can significantly reduce the size of the final image.

• Resource Management : Use Docker's resource limiting function to control the CPU and memory usage of the container. For example:

   docker run --name my-container --cpus=1 --memory=512m my-image

  This limits the container to use no more than 1 CPU core and 512MB of memory.

• Log management : To avoid excessive container logs, you can use Docker's log driver to manage logs. For example:

   docker run --log-driver json-file --log-opt max-size=10m --log-opt max-file=3 my-image

  This limits the log file size per container to 10MB, and keeps up to 3 log files.

  In general, running Docker on Linux can not only take advantage of the power of the operating system, but also give full play to the advantages of Docker. Through the introduction and examples of this article, I hope you can better understand the installation, configuration and usage of Docker, and flexibly apply this knowledge in actual projects.

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