SageMaker Edge Manager integrates AWS IoT Greengrass version 2 to simplify accessing, maintaining, and deploying the Edge Manager agent and model to your devices. Without AWS IoT Greengrass V2, setting up your devices and fleets to use SageMaker Edge Manager requires you to manually copy the Edge Manager agent from an Amazon S3 release bucket. You use the agent to make predictions with models loaded onto your edge devices. With AWS IoT Greengrass V2 and SageMaker Edge Manager integration, you can use AWS IoT Greengrass V2 components. Components are pre-built software modules that can connect your edge devices to AWS services or third-party service via AWS IoT Greengrass.
You must install the AWS IoT Greengrass Core software onto your device(s) if you want to use AWS IoT Greengrass V2 to deploy the Edge Manager agent and your model. For more information about device requirements and how to set up your devices, see Setting up AWS IoT Greengrass core devices in the AWS IoT Greengrass documentation.
You use the following three components to deploy the Edge Manager agent:
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A pre-built public component: SageMaker AI maintains the public Edge Manager component.
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A autogenerated private component: The private component is autogenerated when you package your machine learning model with the
CreateEdgePackagingJobAPI and specifyGreengrassV2Componentfor the Edge Manager API fieldPresetDeploymentType. -
A custom component: This is the inference application that is responsible for preprocessing and making inferences on your device. You must create this component. See either Create a Hello World custom component in the SageMaker Edge Manager documentation or Create custom AWS IoT Greengrass components in the AWS IoT Greengrass documentation for more information on how to create custom components.
