Dagger: The Automation Engine for Programmable Software Delivery
This repository profile is provided by osrepos.com, an open source repository discovery platform.
Summary
Dagger is an open-source automation engine designed to build, test, and ship any codebase reliably and at scale. It transforms your software delivery into a programmable, local-first, repeatable, and observable process. With SDKs in multiple languages, Dagger offers a modern alternative to traditional shell scripts and YAML-based CI/CD.
Repository Information
Topics
Click on any tag to explore related repositories
Use at your own risk
OSRepos shares public repositories for knowledge and discovery only. Any installation, execution, configuration, or use of code from these repositories is the user's own responsibility. Always review the repository, source code, dependencies, licenses, and security implications before running or installing anything. OSRepos is not responsible for issues, damages, or losses resulting from third-party repositories.
Introduction
Dagger is a powerful automation engine that redefines how software is built, tested, and shipped. It provides a complete execution engine and system API, allowing developers to automate complex software delivery workflows with unprecedented programmability. Dagger runs consistently across your local machine, CI server, or directly in the cloud, requiring only a container runtime like Docker.
Installation
Getting started with Dagger is straightforward. You can install it using Homebrew on macOS and Linux:
brew install dagger/tap/dagger
For other installation methods and detailed instructions, please refer to the official documentation.
Examples
Dagger empowers you to define your CI/CD pipelines as code using native SDKs in 8 languages, including Go, Python, and TypeScript. This programmability allows for complex logic, reusable modules, and full type safety, moving beyond the limitations of shell scripts and proprietary YAML. For instance, you can define functions to build a Docker image, run tests, and deploy an application, all orchestrated within a Dagger pipeline.
Why Use Dagger?
Dagger offers several compelling advantages for modern software delivery:
- Programmable: Replace brittle shell scripts and restrictive YAML with a complete execution engine and system API. Dagger provides SDKs for 8 languages, an interactive REPL, and a rich ecosystem of reusable modules, making your delivery pipelines truly programmable.
- Local-first: Automate tasks once and run them reliably anywhere. Dagger ensures identical behavior on your laptop, CI server, or cloud infrastructure, with the only dependency being a container runtime.
- Repeatable: Tools run in isolated containers, orchestrated by sandboxed functions. Host dependencies are explicit, artifacts are built just-in-time, and every operation is incremental by default, ensuring trustworthy and consistent outputs.
- Observable: Gain deep insights into your workflows. Every operation emits a full OpenTelemetry trace, enriched with granular logs and metrics. Visualize traces directly in the terminal or a web view, enabling immediate debugging of complex workflows.
Links
- Documentation: https://docs.dagger.io
- Quickstart: https://docs.dagger.io/quickstart
- Community Discord: https://discord.gg/dagger-io
- GitHub Discussions: https://github.com/dagger/dagger/discussions
- Contributing: https://github.com/dagger/dagger/blob/main/CONTRIBUTING.md
Related repositories
Similar repositories that may be relevant next.
Router: Optimize AI Model Selection and Costs for Agentic Systems
September 28, 2026
The Weave-OS Router is an intelligent model router for agentic systems, optimizing AI model selection for every request. It acts as a drop-in proxy for major AI providers, routing prompts to the most suitable model in under 50ms. This solution helps users significantly cut costs, often by 40-70%, simply by changing an endpoint.
Memoh: An Open-Source Multi-Agent Platform with Dedicated AI Workspaces
September 26, 2026
Memoh is an innovative open-source multi-agent platform designed to provide each AI agent with its own dedicated cloud computer. This includes a filesystem, desktop, browser, network, and persistent long-term memory, ensuring agents remain online 24/7. Users can integrate their own API keys or host existing AI models, fostering a versatile and always-on environment for AI development and deployment.
llm-d Router: Intelligent Orchestration for Multi-Phase LLM Inference
September 25, 2026
The `llm-d-router` is a sophisticated Go service designed as an intelligent entry point for large language model (LLM) inference requests. It orchestrates complex, multi-phase LLM inference pipelines across specialized worker pools, routing requests through an Inference Gateway to disaggregated vLLM workers. By exposing OpenAI-compatible APIs, it simplifies integration and leverages Kubernetes for scalable, efficient deployments.
Inference Gateway: Unifying LLM Providers with a High-Performance API
September 25, 2026
Inference Gateway is an open-source, cloud-native, high-performance proxy server designed to unify access to various language model APIs. It provides a single OpenAI-compatible endpoint, simplifying interactions with multiple LLM providers, from local solutions like Ollama to major cloud platforms. This gateway enables seamless integration and management of diverse AI models, enhancing portability and data privacy.
Source repository
Open the original repository on GitHub.
17 counted GitHub visits