aid: ray name: Ray description: >- Ray is an open-source unified compute framework, stewarded by Anyscale, that scales Python and AI workloads from a laptop to a cluster. It consists of Ray Core (a distributed runtime) and a set of AI libraries (Ray Train, Ray Data, Ray Tune, Ray Serve, RLlib) for training, batch inference, hyperparameter search, and model serving. Ray clusters expose a Dashboard and Jobs REST API on the head node (default port 8265) for submitting jobs, inspecting actors and tasks, and serving deployed applications via Ray Serve HTTP endpoints. type: Index image: https://kinlane-productions.s3.amazonaws.com/apis-json/apis-json-logo.jpg tags: - Distributed Computing - Machine Learning - AI Infrastructure - Python - Model Serving - Open Source - Compute url: >- https://raw.githubusercontent.com/api-evangelist/ray/refs/heads/main/apis.yml created: '2026-05-11' modified: '2026-05-11' specificationVersion: '0.19' apis: - aid: ray:jobs-api name: Ray Jobs REST API description: >- REST API on the Ray head node for submitting, listing, inspecting, and stopping Ray jobs, plus streaming logs. Default base URL is http://:8265/api/jobs/. Open-source clusters are typically unauthenticated; production deployments rely on network controls or Anyscale-managed authentication. humanURL: https://docs.ray.io/en/latest/cluster/running-applications/job-submission/rest.html baseURL: http://127.0.0.1:8265/api tags: - Jobs - Cluster - Submission - Logs properties: - type: Documentation url: https://docs.ray.io/en/latest/cluster/running-applications/job-submission/rest.html - type: Python SDK url: https://docs.ray.io/en/latest/cluster/running-applications/job-submission/sdk.html - type: CLI url: https://docs.ray.io/en/latest/cluster/running-applications/job-submission/cli.html - aid: ray:dashboard-api name: Ray Dashboard API description: >- Internal REST API powering the Ray Dashboard, exposing endpoints for nodes, actors, tasks, placement groups, runtime environments, and cluster events. Same base URL as the Jobs API (http://:8265). humanURL: https://docs.ray.io/en/latest/ray-observability/getting-started.html baseURL: http://127.0.0.1:8265/api tags: - Observability - Dashboard - Cluster State - Actors properties: - type: Documentation url: https://docs.ray.io/en/latest/ray-observability/getting-started.html - aid: ray:serve-api name: Ray Serve HTTP API description: >- HTTP interface for invoking models and applications deployed via Ray Serve. Each deployed application is exposed as an HTTP endpoint on the Serve HTTP proxy (default port 8000); authentication and routing are configured per deployment. humanURL: https://docs.ray.io/en/latest/serve/index.html baseURL: http://127.0.0.1:8000 tags: - Model Serving - Inference - HTTP properties: - type: Documentation url: https://docs.ray.io/en/latest/serve/index.html - type: Production Guide url: https://docs.ray.io/en/latest/serve/production-guide/index.html common: - type: Website url: https://www.ray.io - type: Documentation url: https://docs.ray.io - type: GitHub Repository url: https://github.com/ray-project/ray - type: GitHub Organization url: https://github.com/ray-project - type: Anyscale url: https://www.anyscale.com - type: Slack url: https://www.ray.io/community - type: Forum url: https://discuss.ray.io - type: Blog url: https://www.anyscale.com/blog - type: Issues url: https://github.com/ray-project/ray/issues - type: License url: https://github.com/ray-project/ray/blob/master/LICENSE maintainers: - FN: Kin Lane email: kin@apievangelist.com