API Authentication¶

There are two equivalent methods for call Run:ai APIs:

• REST APIs
• Kubernetes APIs. Using kubectl apply on YAML files, or calling Kubernetes directly via code.

The following document explains how to get the credentials required to call Run:ai REST APIs. By contrast, Run:ai Kubernetes APIs, use the Kubernetes profile and are authenticated by pre-running runai login (or oc login with OpenShift).

Create a Client Application¶

• Open the Run:ai Run:ai User Interface.
• Go to Settings | Application
• Create a new Application.
• Set the required roles:
  • Select Researcher to manipulate Jobs using the Researcher REST API. To provide access to a specific project, you will also need to go to Application | Projects and provide the Application with access to specific projects.
  • Select Editor to manipulate Projects and Departments using the Administrator REST API.
  • Select Administrator to manipulate Users, Tenant Settings and Clusters using the Administrator REST API.
• Copy the <APPLICATION-NAME> and <CLIENT-SECRET> to be used below
• <COMPANY-URL> is app.run.ai for SaaS installations (not <company>.run.ai) or the Run:ai user interface URL for Self-hosted installations.
• Go to Settings | General, under Researcher Authentication copy <REALM>.

Request an API Token¶

Use the above parameters to get a temporary token to access Run:ai as follows.

Example command to get an API token¶

curl -X POST 'https://<COMPANY-URL>/auth/realms/<REALM>/protocol/openid-connect/token' \
--header 'Content-Type: application/x-www-form-urlencoded' \
--data-urlencode 'grant_type=client_credentials' \
--data-urlencode 'scope=openid' \
--data-urlencode 'response_type=id_token' \
--data-urlencode 'client_id=<APPLICATION-NAME>' \
--data-urlencode 'client_secret=<CLIENT-SECRET>'

import http.client

conn = http.client.HTTPSConnection("")
payload = "grant_type=client_credentials&client_id=<APPLICATION-NAME>&client_secret=<CLIENT_SECRET>"
headers = { 'content-type': "application/x-www-form-urlencoded" }
conn.request("POST", "/<COMPANY-URL>/auth/realms/<REALM>/protocol/openid-connect/token", payload, headers)

res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))

Response¶

The API response will look as follows:

{
  "access_token": "...",
  "expires_in": 36000,
   ....
  "token_type": "bearer"
}

Call an API¶

To call APIs, the application must pass the retrieved access_token as a Bearer token in the Authorization header of your HTTP request.

• To retrieve and manipulate jobs, use the Researcher REST API. Researcher API works at the cluster level and you will have different endpoints for different clusters.
• To retrieve and manipulate other metadata objects, use the Administrator REST API. Administrator API works at the control-plane (backend) level and you have a single endpoint for all clusters.