Building software tools from scratch often reveals insights that documentation alone cannot. That principle led one developer to question the black box of container runtimes like Docker and containerd. Rather than continuing to use high-level tools without understanding their foundations, they embarked on a project to construct a container runtime using nothing but Linux’s native primitives.
Why rebuild the container wheel
The rise of Docker popularized containerization, but its convenience sometimes obscures the underlying mechanics. Underneath the user-friendly interface, Linux leverages several kernel features to create isolated environments: namespaces for separating resources like PIDs, networks, and mounts; cgroups for resource control; and layered filesystems for efficient image storage.
The developer behind this project wanted to strip away abstractions and see if they could recreate a functional container runtime from these primitives. The result was LXR, a minimal container runtime written in Go that operates without Docker, containerd, or LXC.
How LXR constructs containers step by step
From the outside, starting a container with LXR appears straightforward. A single command like lxr create --name goCon golang initiates the process. Internally, however, the runtime executes a sequence of carefully orchestrated steps to ensure proper isolation and functionality.
First, the runtime pulls image layers from Docker Hub, typically stored as compressed tarballs. These layers are extracted and assembled into a coherent root filesystem. Dependencies required by the image—such as Go tooling for a golang image—are installed into this filesystem.
To enable efficient image reuse and modifications, LXR employs OverlayFS, a Linux filesystem that layers directories on top of one another. This allows multiple containers to share base image layers while retaining their own modifications in temporary upper layers.
Networking setup is another critical component. LXR configures a virtual Ethernet device and bridges it to the host network, assigning unique IP addresses to each container. This ensures network isolation without requiring complex routing rules.
Finally, the container process is launched within its isolated environment. For added convenience, LXR can automatically start code-server inside the container, enabling browser-based access to the isolated environment.
Observing true isolation in action
Once containers are running, LXR provides visibility into their state through commands like lxr ps. Each container maintains its own process ID space, network stack, and filesystem view. Running lxr inspect on a container reveals its assigned IP, active namespaces, and mounted filesystems.
This level of isolation mirrors what production-grade runtimes like Docker offer, but with a fraction of the complexity. The developer’s experiment demonstrates that containerization does not require monolithic runtimes. Instead, it can be achieved through precise use of Linux kernel features.
Challenges on the path to minimalism
Early iterations of LXR revealed unexpected hurdles, particularly around user permissions. Attempting to start containers as a non-root user led to inconsistent behavior and failed process launches.
This issue stemmed from how Linux handles namespace creation and user ID mapping. Without proper configuration, processes inside namespaces could not access required resources or retain sufficient privileges. The developer plans to address this limitation in a future post, outlining solutions for secure non-root container execution.
What LXR teaches beyond containerization
Beyond the practical outcome of a working runtime, this project underscores the value of understanding foundational technologies. Developers who grasp the mechanics of namespaces, cgroups, and networking gain deeper control over their environments. It also highlights the trade-offs between simplicity and convenience in software design.
As containerization continues to evolve, lightweight alternatives like LXR could play a role in education, embedded systems, or environments where Docker’s overhead is prohibitive. The experiment serves as a reminder that even sophisticated tools rest on fundamental principles waiting to be explored.
AI summary
Linux ad alanları, cgroup ve ağ izolasyonu kullanarak Docker olmadan kendi konteyner çalıştırıcınızı nasıl geliştirirsiniz? LXR projesiyle adım adım inceleyin.
