Infracost

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.

Terraform pull request automation via GitHub/GitLab comments

Atlantis is a self-hosted Terraform pull request automation tool that runs plan and apply operations triggered by GitHub, GitLab, Bitbucket, or Azure DevOps comments. Type 'atlantis plan' on a PR to see infrastructure changes, then 'atlantis apply' to deploy. 9,100+ GitHub stars, Apache 2.0 licensed. Widely adopted as the standard for GitOps-style Terraform workflows, with locking to prevent concurrent modifications to the same resources.

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.

Reusable KV cache infrastructure for scalable LLM inference

Open-source KV cache management layer that persists, offloads and reuses model key-value caches across requests and serving engines to reduce repeated prefill work and improve inference throughput.