📣 The NVIDIA Run:ai docs are moving!
We’ve launched a new documentation site to improve navigation, clarity, and access to the latest features starting from NVIDIA Run:ai v2.20 and above. Visit NVIDIA Run:ai documentation.
Documentation for versions 2.19 and below will remain on this site.
Overview¶
Developers can access Run:ai through various programmatic interfaces.
API Architecture¶
Run:ai is composed of a single, multi-tenant control plane. Each tenant can be connected to one or more GPU clusters. See Run:ai system components for detailed information.
The following programming interfaces are available:
| API | Description | Purpose |
|---|---|---|
| Run:ai REST API | Get and Modify any Run:ai business object | This is the API mostly used by system developers. The API is also used by the Run:ai user interface as well as the new command-line interface |
| Metrics API (deprecated) | Get cluster metrics | Get utilization metrics. |
Run:ai REST API¶
Allows you to Add, delete, modify and list Run:ai meta-data objects such as Projects, Departments, Users. For Clusters of Run:ai 2.18 and above, allows the submitting of Workloasd.
The API is provided as REST and is accessible via the control plane endpoint.
For more information see Run:ai REST API.
Important
The endpoints and fields specified in the API reference are the ones that are officially supported by Run:ai. Endpoints and fields that are not listed in the API reference are not supported.
Run:ai does not recommend using API endpoints and fields marked as deprecated and will not add functionality to them. Once an API endpoint or field is marked as deprecated, Run:ai will stop supporting it after 2 major releases for self-hosted deployments, and after 6 months for SaaS deployments.
For details, see the Deprecation notifications.
Metrics API¶
Retrieve metrics from multiple GPU clusters.
See the Metrics API document.
API Authentication¶
See API Authentication for information on how to gain authenticated access to Run:ai APIs.