[Summary] Some commonly used Docker image acceleration technologies

Docker is a popular containerization technology and has become an indispensable tool for development and operation and maintenance personnel. Docker Hub is a public image warehouse officially provided by Docker, which stores millions of image files for developers to use. Because Docker Hub is a global public resource, you may encounter performance issues due to network latency or bandwidth limitations when downloading and uploading Docker images. In this case, in order to improve the download speed of the Docker image, we need to use some technical means to speed up the Docker Pull process.

This article will introduce some commonly used Docker image acceleration technologies to help you use Docker Hub faster and more efficiently.

1. The accelerator provided by Docker

Docker officially provides a registry image acceleration function, allowing users to pull Docker images from domestic mirror sites with faster transfer speeds. Users can select the appropriate accelerator address according to their region and then configure it to the Docker client.

First, register an account on the Docker official website and log in, then find "Dashboard" from the navigation menu. On the "Dashboard" interface, click the "Get Started with Docker Desktop" button to enter the installation page.

In the installation page, select the "Linux" system and download and install Docker Client. After the installation is complete, open a terminal and log in to your Docker account

docker login

. After that, you can run the following command to configure the Docker client to use Docker Hub's image accelerator.

sudo tee /etc/docker/daemon.json <<-&#39;EOF&#39;
{
  "registry-mirrors": ["https://<region_id>.mirror.aliyuncs.com"]
}
EOF

Among them, is the image accelerator address provided by Docker Hub. You can find the required image accelerator address from the Docker Hub official website.

Run the following command to restart the Docker client to make the modification take effect

sudo systemctl daemon-reload && sudo systemctl restart docker

2. Alibaba Cloud’s Docker Image Accelerator

The Docker Image Accelerator (Docker Registry Mirror) provided by Alibaba Cloud Supports multiple environments such as public cloud, private cloud, and hybrid cloud, including domestic and global image warehouses. Users can obtain the accelerator address and use its services for free.

After registering an Alibaba Cloud account, visit "Image Accelerator" on the Alibaba Cloud Container Service page to generate a personal accelerator address. Add the following configuration to the registry-mirrors field of the Docker configuration file and restart the Docker client to enjoy the services of Alibaba Cloud Docker Mirror Accelerator.

sudo tee /etc/docker/daemon.json <<-&#39;EOF&#39;
{
  "registry-mirrors": ["https://<random_id>.mirror.aliyuncs.com"]
}
EOF

Among them, is the user's personal Alibaba Cloud acceleration address, which can be found in the "Image Accelerator" on the Alibaba Cloud Container Service page.

3. Third-party Docker Hub image accelerator

In addition to the official and Alibaba Cloud Docker Hub image accelerators, there are many third-party image accelerators to choose from. Among them, the more popular ones include DaoCloud accelerator, NetEase Rabbit Mirror, Azure China, etc.

Different accelerator services use different methods, so you need to check the corresponding documentation to understand how to use them. However, most image accelerators will provide configuration information for the Docker configuration file. You can add this information to the Docker configuration file and restart the Docker service.

Conclusion

Docker is a very useful technology, but you may encounter performance issues when using it, especially when downloading and uploading Docker images. This article introduces several commonly used Docker image acceleration technologies to help you use Docker Hub faster and more efficiently. If you haven't tried these methods yet, feel free to try them and enjoy a better experience with Docker.

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