Looking up the endpoint URL of a deployment

To send payload data to a model or function deployment for analysis (for example, to classify the data, or make a prediction from the data) you need to know the endpoint URL of the deployment. This topic describes how to look up the endpoint URL of a deployment in IBM Watson Machine Learning.

 

There are three ways to look up the endpoint URL of a deployment:

 

Option 1: In Watson Studio

  1. From the Deployments tab of your project in Watson Studio, click the deployment to look up
  2. In the Implementation tab of the deployment details page, the deployment endpoint URL is in the “Scoring End-point” row

 

Option 2: Using the Watson Machine Learning CLI

  1. List the deployments by issuing the command: bx ml list deployments
  2. From the row of the desired deployment, copy the value in the “Deployment Id” column and the “Model Id” column
  3. List the details of the deployment by issuing the command: bx ml show deployments <model-id> <deployment-id>
  4. The deployment endpoint URL is listed in the “Scoring endpoint” row

 

Option 3: Using the Watson Machine Learning Python client

  1. List the deployments by calling the function client.repository.list() external link
  2. In the row of the desired deployment, the deployment endpoint URL is listed in the “GUID” column