Dagger is an open-source runtime for composable, containerized workflows, designed for AI agents and CI/CD. It offers repeatability, modularity, observability, and cross-platform support, enabling developers to build complex systems with ease.

How It Works

Dagger transforms code into containerized, composable operations using a universal type system for seamless integration of components across languages. It features automatic artifact caching for faster, cheaper execution and built-in observability with tracing, logs, and metrics for debugging complex workflows.

Quick Start & Requirements

• Install via Dagger CLI: dagger install
• Prerequisites: Docker.
• Setup time: Minimal.
• Links: Dagger for AI Agents, Dagger for CI, Documentation

Highlighted Details

• Native LLM integration for function discovery and usage in agents.
• Interactive terminal for real-time workflow interaction, prototyping, and debugging.
• Universal type system allows mixing components from any language.
• Automatic artifact caching speeds up execution and reduces costs.

Maintenance & Community

• Community server: Discord
• Twitter: @dagger_io
• Community activities: dagger.io/community

Licensing & Compatibility

• License: Apache 2.0.
• Compatibility: Permissive license suitable for commercial use and closed-source linking.

Limitations & Caveats

Dagger relies on Docker for its containerized execution model, which may introduce a dependency on the Docker daemon and its associated resource footprint.