GEMINI.md

Project Overview

This project provides a multi-architecture Docker image for network troubleshooting. It's based on Alpine Linux and includes a wide range of command-line tools for network diagnostics, as well as an Nginx web server. The project also provides a Fedora-based variant. The Docker image is designed to be used in various environments, including standalone Docker, Kubernetes, and OpenShift.

The core of the project is the Dockerfile that builds the image, installing tools like curl, ping, traceroute, tcpdump, and nmap. An entrypoint.sh script dynamically configures the container on startup, setting up an index.html page with container details and allowing for customizable HTTP/HTTPS ports via environment variables.

The Nginx web server runs by default to keep the container alive and serves a simple status page. This makes it easy to run the container and then exec into it for troubleshooting.

Building and Running

Building the Docker Image

To build the Docker image locally, use the following command:

docker build -t local/network-multitool .

Running the Docker Image

To run the container:

# Run in detached mode
docker run -d wbitt/network-multitool

# Exec into the running container
docker exec -it <container-name> /bin/bash

To run with custom ports:

docker run -e HTTP_PORT=8080 -e HTTPS_PORT=8443 -p 8080:8080 -p 8443:8443 -d wbitt/network-multitool

Kubernetes

A DaemonSet is provided to run the multitool on all nodes in a Kubernetes cluster:

kubectl apply -f kubernetes/multitool-daemonset.yml

This will run the multitool on each node with host networking enabled.

Development Conventions

• The project follows a "minimal but useful" philosophy, including only the most essential tools to keep the image size small.
• The Dockerfile is well-documented, with packages listed in alphabetical order for readability.
• The entrypoint.sh script provides flexibility for running the container in different scenarios.
• The Nginx configuration is set up to forward logs to stdout and stderr, which is a best practice for containerized applications.
• Contributions are welcome, but should be for "absolutely necessary" tools that are small and have a large number of use cases.