Colima vs Kubeli

Colima runs container environments on macOS and Linux, with Docker, containerd, Kubernetes and Incus runtime options. Docker compatibility is intended to let existing Docker workflows and tools continue without changes; containerd users can use nerdctl for a Docker-like command line. It can launch a local, single-node k3s cluster, and users can select an exact K3s version. CPU, memory and disk allocations are configurable, and multiple isolated instances can run with different settings. Colima also documents GPU-accelerated AI workloads on Apple Silicon using Krunkit, with model runners supporting Docker AI Registry and HuggingFace; Ramalama also supports Ollama registries. Those workloads require Apple Silicon, macOS 13 or newer, and Krunkit, with at least 8 GB of RAM recommended. The AI containers are isolated from the host filesystem, other containers and network access unless network access is enabled. Colima is free and MIT-licensed, with installation options for macOS and Linux. Incus virtual machines require m3 or newer Apple Silicon.

Kubeli is a native desktop application for managing Kubernetes clusters on macOS, Windows, and Linux. It connects to multiple clusters simultaneously and supports one-click context switching. A topology view nests namespaces, deployments, and pods so cluster structure can be inspected graphically. Pod logs stream with search, timestamps, and error highlighting, and can be passed to a locally running AI assistant. Kubeli maps local ports to pods or services and can open forwarded ports in a browser. Its listed AI integrations include Claude Code, Codex, OpenCode, and Droid. An included MCP server lets VS Code, Cursor, or Claude Code query cluster state. HTTP, HTTPS, and SOCKS5 proxy support addresses clusters behind corporate firewalls. The site lists macOS 10.15+, Windows 10/11, and Linux x64 downloads. Kubeli is free and MIT open source, requires no account or telemetry, and says it does not transfer information to other networked systems unless requested. Support is provided through GitHub Discussions, feature requests, and bug reports.