Docker containers are revolutionary units of software packaging. They bundle applications together with all their dependencies, libraries, and runtime requirements into a single, portable package. This ensures that applications run consistently across different environments, from development laptops to production servers.
A Docker image is a read-only template that contains application code, dependencies, and configuration. Think of it as a blueprint. When you run an image, Docker creates a container - which is a running instance of that image. The key difference is that containers add a thin writable layer on top of the image layers, allowing the application to make changes during runtime.
Docker containers achieve isolation through several key mechanisms. Namespaces provide process, network, and filesystem isolation, making each container appear to have its own system view. Control groups limit resource usage like CPU and memory for each container. The layered filesystem enables efficient storage and sharing of common components between containers while maintaining separation.
The Docker Engine is the core component that manages the entire container lifecycle. It starts by building images from Dockerfiles, which contain step-by-step instructions. These images can then be run as containers. The engine handles starting, stopping, and removing containers as needed. The Docker daemon runs in the background, communicating with the host operating system to manage resources and provide the isolation mechanisms we discussed earlier.
Docker containers provide exceptional portability and consistency. The same container that runs on a developer's laptop will run identically in testing and production environments. This eliminates the common problem of 'it works on my machine'. Containers are also much more efficient than traditional virtual machines because they share the host operating system kernel, requiring fewer resources while providing similar isolation benefits.