Amazon SageMaker
Executing individual steps in SageMaker.
Amazon SageMaker
When to use it
You should use the SageMaker step operator if:
one or more steps of your pipeline require computing resources (CPU, GPU, memory) that are not provided by your orchestrator.
How to deploy it
Infrastructure Deployment
A Sagemaker step operator can be deployed directly from the ZenML CLI:
You can pass other configurations specific to the stack components as key-value arguments. If you don't provide a name, a random one is generated for you. For more information about how to work use the CLI for this, please refer to the dedicated documentation section.
How to use it
To use the SageMaker step operator, we need:
The ZenML
aws
integration installed. If you haven't done so, run
There are two ways you can authenticate your orchestrator to AWS to be able to run steps on SageMaker:
Once you added the step operator to your active stack, you can use it to execute individual steps of your pipeline by specifying it in the @step
decorator as follows:
Additional configuration
Enabling CUDA for GPU-backed hardware
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