Woodpecker CI

Automate your workflow from GitHub

GitHub's built-in CI/CD and workflow automation platform that runs directly in your repository. Define workflows in YAML triggered by Git events (push, PR, release), schedules, or manual dispatch. Massive marketplace of 20,000+ community-maintained actions for testing, building, deploying, and automating tasks. Supports matrix builds, caching, secrets, environments with approval gates, and self-hosted runners. Free for public repos with generous minutes for private repos.

Built-in CI/CD for GitLab

GitLab's built-in CI/CD pipeline system defined via .gitlab-ci.yml files in your repository. Features multi-stage pipelines, parallel jobs, matrix builds, environments with deployment tracking, merge train for serialized merges, auto DevOps for zero-config CI/CD, container registry, and security scanning (SAST/DAST). Supports self-hosted runners and Kubernetes executors. Tightly integrated with GitLab's merge requests and issue tracking. A leading alternative to GitHub Actions for GitLab users.

Your CI/CD scripts as code. Consistent, reproducible builds.

Build automation framework that combines Dockerfile and Makefile syntax for repeatable, containerized builds. Earthly runs every step in a container so builds produce identical results on dev laptops and CI, augmenting Make/Gradle/npm/cargo with cross-language reproducibility. Features parallel target execution, layer caching, multi-platform builds, and references across Earthfiles or repositories.

Cloud-native CI/CD framework for Kubernetes-native pipelines.

Tekton is a cloud-native CI/CD framework that provides Kubernetes-native pipeline resources. A Linux Foundation / CD Foundation project, it offers reusable, composable building blocks for creating CI/CD systems. Used by Google Cloud Build, Red Hat OpenShift Pipelines, and other platforms as their underlying pipeline engine.

Heterogeneous CPU-GPU inference and SFT for large MoE models

Open-source framework for running and fine-tuning large Mixture-of-Experts models with heterogeneous CPU-GPU execution, optimized kernels, limited VRAM and SGLang or LLaMA-Factory integrations.

Official Kubernetes and Helm reference stack built on the vLLM inference engine

Official vLLM reference implementation for scaling the existing inference engine on Kubernetes with Helm, request routing, KV-cache offload, autoscaling and Prometheus/Grafana observability.

Distributed inference orchestration above vLLM, SGLang and TensorRT-LLM

Open-source, datacenter-scale orchestration layer that coordinates vLLM, SGLang and TensorRT-LLM across nodes with disaggregated serving, KV-aware routing, multi-tier cache management and automatic scaling.

Open-source GPU control plane for scalable AI model serving

Open-source GPU cluster manager that configures vLLM, SGLang, TensorRT-LLM or custom engines, serves models through compatible APIs, and provisions SSH-accessible GPU instances across on-premises, Kubernetes and cloud environments.

Disaggregated KV cache storage and transfer for LLM serving

Open-source infrastructure for disaggregated LLM serving that pools KV caches across prefill and decode workers, with high-performance transfer, distributed storage and integrations for vLLM and SGLang.

Run AI coding agents in GitHub Actions from Markdown

Open-source GitHub CLI extension for defining repository automations in Markdown and running Copilot, Claude Code, Codex, Gemini or custom agents inside hardened GitHub Actions workflows.