In the following REST API calls, we use SUBSCRIPTION_ID, RESOURCE_GROUP, LOCATION, and WORKSPACE as placeholders. Create machine learning assetsįirst, set up your Azure Machine Learning assets to configure your job. The following example an online endpoint with the REST API. There are many ways to create an Azure Machine Learning online endpoint including the Azure CLI, and visually with the studio. But first you'll have to register the assets needed for deployment, including model, code, and environment. In this article, you'll create an online endpoint and deployment, and validate it by invoking it. Online endpoints allow you to deploy your model without having to create and manage the underlying infrastructure as well as Kubernetes clusters. export ENDPOINT_NAME=endpt-rest-`echo $RANDOM` For example, there can be only one endpoint with the name my-endpoint in westus2.
Endpoint names need to be unique at the Azure region level.
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