Projects sharing features with Skypilot

Spinnaker is a multi-cloud continuous delivery platform designed to automate software releases and deployment pipelines across various public cloud providers and Kubernetes clusters. It functions as a cloud deployment orchestrator and infrastructure delivery tool, coordinating the promotion of software artifacts through multiple environments using visual workflows and directed acyclic graphs. The platform distinguishes itself with a dedicated canary analysis engine that compares performance metrics between new and stable software versions to automate release decisions. It utilizes cloud-agnos

Dask is a parallel computing framework and distributed task scheduler designed to scale Python data science workflows from single machines to large clusters. It functions as a cluster resource manager that orchestrates computational logic by representing tasks and their dependencies as directed acyclic graphs. This architecture allows the system to automate the distribution of workloads across available hardware while managing complex execution requirements. The project distinguishes itself through a lazy evaluation engine that defers data operations until they are explicitly requested, enabl

This project is an infrastructure as code tool designed to automate the lifecycle management of Amazon Web Services resources. It functions as a cloud resource provisioner that enables users to define, version, and deploy infrastructure components through declarative configuration files. The system operates by reconciling the current state of a cloud environment against a desired configuration, calculating the necessary delta operations to achieve convergence. It utilizes a directed acyclic graph to resolve resource dependencies and determine the optimal execution order for changes, ensuring

Algo is a cloud VPN deployment tool and WireGuard orchestrator designed to automate the provisioning and configuration of personal VPN servers across multiple cloud infrastructure providers. It functions as a multi-cloud infrastructure provisioner and a VPN client configuration generator, creating the necessary tunnels and connection profiles for secure device connectivity. The project distinguishes itself by integrating a network ad-blocking DNS server directly into the deployment, filtering advertisements and malicious domains for all connected clients. It further simplifies the onboarding

NNI is an AutoML toolkit designed to automate machine learning lifecycles. It functions as a hyperparameter optimization framework, a neural architecture search tool, and a model compression suite. The project provides a distributed training orchestrator to manage machine learning workloads across local machines, remote servers, and cloud platforms. It enables the discovery of efficient model structures through reinforcement learning and one-shot optimization methods, while utilizing Bayesian and evolutionary algorithms to automate hyperparameter tuning. Additional capabilities include tools

Polyaxon is a Kubernetes-native machine learning orchestration platform and MLOps pipeline orchestrator. It serves as a control plane for managing distributed deep learning workloads, automated machine learning pipelines, and experiment tracking. The platform distinguishes itself through specialized services for distributed training management, including MPI-based coordination for PyTorch and TensorFlow. It provides an automated hyperparameter optimization service utilizing Bayesian, random, and grid search algorithms, alongside managed interactive AI workspaces for launching Jupyter notebook

Meshery is a cloud native management plane used for the orchestration and administration of service meshes and Kubernetes clusters across multiple cloud providers. It provides a centralized interface to configure cloud native components and manage infrastructure through a unified abstraction layer. The platform features a visual infrastructure modeler that translates diagrams into manifests and a simulation engine for dry-running configuration changes. It synchronizes infrastructure state with version control via GitOps workflows, providing visual previews of pull request changes to evaluate

Boto3 is the AWS SDK for Python, providing a programmatic interface for managing and automating AWS cloud infrastructure and services. It serves as a cloud management API client and resource manager for provisioning, configuring, and scaling virtual servers, databases, and storage. The library enables the implementation of infrastructure-as-code through declarative templates and scripts, allowing for the deployment of identical resource stacks across multiple accounts and geographic regions. It also provides a framework for coordinating distributed workflows, serverless functions, and contain

Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis

Coder is a self-hosted platform for provisioning and managing isolated, containerized development environments. It provides a centralized infrastructure for teams to deploy ephemeral workspaces on private cloud or on-premises hardware, ensuring consistent toolchains and dependencies across distributed development environments. The platform distinguishes itself through its focus on secure, infrastructure-as-code governance and autonomous agent integration. It allows organizations to define reusable, versioned environment templates that integrate with existing identity providers and role-based

Salt is an infrastructure configuration management tool and orchestration framework designed for large-scale system administration. It functions as a remote execution engine that enables administrators to manage, provision, and enforce declarative states across distributed fleets of servers from a central control point. By utilizing a high-performance message bus, the platform allows for the simultaneous execution of administrative tasks and the maintenance of consistent software configurations across thousands of nodes. The system distinguishes itself through a flexible architecture that sup

This project provides a framework for managing multi-agent systems, designed to automate complex software development, infrastructure, and business workflows. It functions as a multi-agent workflow orchestrator that routes tasks to domain-specific workers while maintaining state persistence and infrastructure automation. By leveraging large language models, the system decomposes high-level objectives into actionable plans, ensuring that complex operations are executed with consistency and reliability. The framework distinguishes itself through its hierarchical agent registry and policy-driven

Pigsty is a comprehensive database infrastructure orchestration platform designed to automate the full lifecycle of high-availability PostgreSQL clusters. It functions as an infrastructure-as-code framework that manages cluster coordination, node provisioning, and service discovery through idempotent playbooks. By integrating distributed consensus mechanisms, the platform ensures automated failover and consistent state enforcement across diverse environments, including bare metal and virtualized infrastructure. The platform distinguishes itself through a robust suite of operational capabiliti

This project is a command-line interface that bridges local development workflows with remote platform services. It functions as a terminal-based platform client, enabling users to manage repositories, issues, and pull requests directly from their command line through authenticated API interactions. The tool provides a modular environment that supports custom binary extensions and command aliases, allowing developers to tailor their terminal experience to specific project needs. Beyond standard repository management, the tool serves as a remote development manager, offering capabilities to pr

Sglang is a high-performance inference engine and serving system designed for large language and multimodal models. It provides a programmable interface for orchestrating complex generation workflows, enabling developers to coordinate multi-turn dialogues, tool invocations, and reasoning chains through a domain-specific language. The platform is built to support production-scale deployments, offering an OpenAI-compatible API that allows for integration with existing application ecosystems. The system distinguishes itself through a disaggregated architecture that separates compute-intensive pr

lmdeploy is a high-performance inference engine and deployment framework for large language models and vision models. It functions as a multi-modal model server and compression toolkit designed to serve models with high throughput and low latency. The system enables the distribution of model services across multiple machines using request-based load balancing and tensor parallelism. It includes specialized tools for model quantization and compression to reduce the memory footprint of weights and caches. The framework covers broad capability areas including production deployment, distributed

Open WebUI is a self-hosted, web-based platform designed for interacting with local and remote artificial intelligence models. It functions as a unified interface and orchestration suite, enabling users to build, deploy, and manage specialized AI agents equipped with custom instructions, external tool access, and private knowledge bases. The platform distinguishes itself through a modular architecture that supports complex AI workflows. It features a plugin-based framework for custom logic and pipeline-based request processing, allowing developers to filter or transform data streams before th

Llama.cpp is an inference engine designed for the local execution of text-based and multimodal language models on consumer hardware. It provides a core environment for running models that process both text and image inputs, utilizing hardware-accelerated backends to optimize performance across diverse CPU and GPU architectures. The project distinguishes itself by offering a lightweight HTTP server that adheres to standard API specifications, enabling chat completion, embeddings, and reranking services. It includes a suite of tools for model quantization and conversion, which reduces memory us

OpenLLM is a framework for deploying, managing, and scaling open-source large language models

LocalAI is a self-hosted inference server that enables the execution of machine learning models directly on local hardware. By providing a unified interface for text, image, and audio processing, it allows users to maintain full control over data privacy and infrastructure costs while eliminating dependencies on external network services. The platform functions as an API gateway that mimics standard cloud-based artificial intelligence interfaces, allowing existing applications to integrate local models as drop-in replacements. It utilizes a container-based architecture to package runtimes and

LiteLLM is a unified gateway and proxy server designed to centralize access to over one hundred language model providers. It provides a standardized API interface that abstracts vendor-specific schemas, allowing developers to interact with diverse models through a single, consistent format. By acting as a central traffic management layer, it enables organizations to route, secure, and govern model interactions across multiple deployments. The platform distinguishes itself through its policy-driven architecture, which uses configuration-based routing to manage traffic distribution, load balanc

vLLM is a high-throughput inference engine designed for the efficient serving and execution of large language models. It functions as a production-ready distributed model server, providing standard API protocols for online serving while also supporting offline batch processing. The system is built to maximize token generation speed and memory efficiency, enabling both large-scale cloud deployments and local execution on personal hardware. The project distinguishes itself through advanced memory management and request scheduling techniques, most notably its use of non-contiguous key-value cach

Ktransformers is a comprehensive framework designed for the operation, fine-tuning, and serving of large language models. It functions as a heterogeneous inference engine and quantized execution runtime, enabling the deployment of massive models by distributing computational workloads across both CPU and GPU resources. This architecture allows users to bypass local memory constraints, making it possible to run and train models that exceed the capacity of a single device. The project distinguishes itself through specialized support for sparse architectures, particularly mixture-of-experts mode

Airllm is a framework designed to execute and fine-tune large language models on consumer-grade hardware. By employing layer-wise model decomposition and memory-efficient loading techniques, the engine enables the operation of massive models that would otherwise exceed available system or video memory. The project distinguishes itself through a suite of optimization strategies that balance memory footprint with performance. It utilizes block-wise weight quantization and asynchronous layer prefetching to reduce resource consumption and hide data transfer latency. Additionally, the framework su

Terraform is a declarative infrastructure-as-code tool designed to manage the lifecycle of cloud and on-premises resources. It functions as a workflow engine that reconciles a defined desired state against real-world infrastructure, using a persistent state-tracking layer to maintain consistency and visibility across distributed environments. By mapping infrastructure components into a directed acyclic graph, the system calculates the optimal order for provisioning, updating, or destroying resources. The platform is distinguished by its extensible plugin-based architecture, which decouples co

Waypoint is an application delivery platform and multi-cloud deployment orchestrator. It enables the definition of the build, deploy, and release lifecycle as code to manage application resources across multiple target environments from a single interface. The project functions as an infrastructure-as-code workflow tool and self-service portal. It abstracts complex infrastructure configurations into reusable patterns, allowing developers to deploy applications using pre-approved templates and modular infrastructure add-ons. The system provides cloud resource governance through role-based acc

Atlas is a SQL database schema management tool and database infrastructure as code framework. It provides a declarative database migration engine that computes the difference between a desired schema state and the current database state to automatically generate the necessary SQL for transitions. The project distinguishes itself through a comprehensive suite of analysis and visualization tools, including a database schema linter that detects destructive changes and data loss risks. It also features a SQL schema visualization tool capable of generating entity-relationship diagrams from extract