Atlantis

Infrastructure as Code

HashiCorp's infrastructure-as-code tool for provisioning and managing cloud resources declaratively using HCL (HashiCorp Configuration Language). Write infrastructure definitions once and deploy to AWS, GCP, Azure, DigitalOcean, and 4,000+ providers. Features state management for tracking resources, plan/apply workflow for safe changes, modules for reusability, and workspaces for environment isolation. The industry standard for multi-cloud IaC with 48K+ GitHub stars.

Infrastructure as Code using real programming languages — TypeScript, Python, Go, C#, Java.

Pulumi is a modern Infrastructure as Code platform that lets teams define cloud infrastructure using familiar programming languages instead of DSLs. Supports TypeScript, Python, Go, C#, Java, and YAML across major clouds, Kubernetes, and a broad Pulumi Registry with Terraform-derived provider coverage. Offers testing, IDE autocomplete, reusable components, and Pulumi Cloud state/governance features.

Cloud cost estimates for Terraform changes in pull requests

Infracost shows cloud cost changes directly in pull requests before infrastructure-as-code changes are deployed. It calculates cost impact across AWS, Azure, and GCP for Terraform, Terragrunt, CloudFormation, and AWS CDK workflows, with diffs in GitHub, GitLab, Bitbucket, and Azure DevOps. 12.4K+ GitHub stars, Apache 2.0 licensed. Used by GitLab, HelloFresh, JPMorgan Chase, BMW, and Accenture.

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.