Rebuilding Docker Containers on File Changes: From Fundamentals to Production Practices

Fundamental Concepts of Docker Containers and Images

In the Docker ecosystem, understanding the distinction between containers and images is crucial. An image is a read-only template containing all filesystems and dependencies required to run an application. A container, on the other hand, is a running instance of an image with a writable layer, enabling application execution in an isolated environment. When developers modify source code, simply restarting an existing container does not automatically incorporate these changes, as the container operates based on the image state at creation time.

Core Issues with File Changes and Container Updates

In continuous integration workflows, such as those using Jenkins to pull updates from a Git repository, a common approach is to copy source code into the image via the COPY instruction in the Dockerfile. However, even if the Docker build process indicates that a new layer has been generated (e.g., COPY src src outputs a new ID), the running container remains in its old state. This occurs because Docker fetches the image only when creating the container; subsequent image rebuilds do not affect existing containers.

Complete Container Rebuild Process

To ensure changes take effect, the old container must be completely removed and a new instance created from the updated image. The following Bash script demonstrates this process:

#!/bin/bash
imageName=xx:my-image
containerName=my-container

docker build -t $imageName -f Dockerfile  .

echo Delete old container...
docker rm -f $containerName

echo Run new container...
docker run -d -p 5000:5000 --name $containerName $imageName

This script first builds a new image, then uses docker rm -f to forcibly remove the old container (ensuring running containers are terminated), and finally creates a new container. This method avoids errors that may arise from docker stop if the container is not running, making it suitable for CI/CD environments.

Data Persistence and Container Independence

Since container rebuilds result in loss of internal data, it is advisable to store application data in external volumes or mounted host directories. For instance, an ASP.NET Core application can save logs or user files in Docker volumes, ensuring critical information is not lost during container updates. This aligns with Docker best practices and enhances system maintainability.

Optimizing Management with Docker Compose

For complex applications, Docker Compose offers a more streamlined management approach. The following docker-compose.yml example defines a single-service configuration:

version: "2.4"
services:
  my-container:
    build: .
    ports:
      - "5000:5000"

Executing docker-compose up --build automatically handles image rebuilding and container updates, supporting multi-container dependency management (e.g., starting a database before the application server), significantly reducing manual operation errors.

Considerations for Production Environments

In development, the --rm parameter can be used to automatically clean up containers, but caution is advised in production to avoid accidental deletion of unnamed volumes. It is recommended to integrate monitoring tools to ensure service health post-update and employ rolling update strategies to minimize downtime.