![]() ![]() If you are still using CLI v1, see Create an Azure Machine Learning compute cluster CLI v1). This article shows CLI v2 in the sections below. The job executes in a containerized environment and packages your model dependencies in a Docker container. You can also use a setup script to create the compute instance with your own custom environment.Ĭompute instances can run jobs securely in a virtual network environment, without requiring enterprises to open up SSH ports. ![]() Create a schedule to automatically start and stop the compute instance.Manage (start, stop, restart, delete) a compute instance.As a development environment, a compute instance can't be shared with other users in your workspace. A compute instance can run multiple jobs in parallel and has a job queue. For development and testing, you can also use the instance as a training compute target. Use a compute instance as your fully configured and managed development environment in the cloud. ![]() Learn how to create and manage a compute instance in your Azure Machine Learning workspace. ![]()
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