Download and Set Up the Edge Manager Agent Manually

Download the Edge Manager agent based on your operating system, architecture, and AWS Region. The agent is periodically updated, so you have the option to choose your agent based on release dates and versions. Once you have the agent, create a JSON configuration file. Specify the device IoT thing name, fleet name, device credentials, and other key-value pairs. See Running the Edge Manager agent for full a list of keys you must specify in the configuration file. You can run the agent as an executable binary or link against it as a dynamic shared object (DSO).

How the agent works

The agent runs on the CPU of your devices. The agent runs inference on the framework and hardware of the target device you specified during the compilation job. For example, if you compiled your model for the Jetson Nano, the agent supports the GPU in the provided Deep Learning Runtime (DLR).

The agent is released in binary format for supported operating systems. Check that your operating system is supported and meets the minimum OS requirement in the following table:

Installing the Edge Manager agent

To use the Edge Manager agent, you first must obtain the release artifacts and a root certificate. The release artifacts are stored in an Amazon S3 bucket in the us-west-2 Region. To download the artifacts, specify your operating system (<OS>) and the <VERSION>.

Based on your operating system, replace <OS> with one of the following:

The VERSION is broken into three components: <MAJOR_VERSION>.<YYYY-MM-DD>-<SHA-7>, where:

You must provide the <MAJOR_VERSION> and the time stamp in YYYY-MM-DD format. We suggest you use the latest artifact release time stamp.

Run the following in your command line to get the latest time stamp. Replace <OS> with your operating system:

aws s3 ls s3://sagemaker-edge-release-store-us-west-2-<OS>/Releases/ | sort -r

For example, if you have a Windows 32-bit OS, run:

aws s3 ls s3://sagemaker-edge-release-store-us-west-2-windows-x86/Releases/ | sort -r

This returns:

2020-12-01 23:33:36 0 

                    PRE 1.20201218.81f481f/
                    PRE 1.20201207.02d0e97/

The return output in this example shows two release artifacts. The first release artifact file notes that the release version has a major release version of 1, a time stamp of 20201218 (in YYYY-MM-DD format), and a 81f481f SHA-7 commit ID.

Based on your operating system, use the following commands to install the artifacts:

aws s3 cp s3://sagemaker-edge-release-store-us-west-2-windows-x86/Releases/<VERSION>/<VERSION>.zip .
aws s3 cp s3://sagemaker-edge-release-store-us-west-2-windows-x86/Releases/<VERSION>/sha256_hex.shasum .

You also must download a root certificate. This certificate validates model artifacts signed by AWS before loading them onto your edge devices.

Replace <OS> corresponding to your platform from the list of supported operation systems and replace <REGION> with your AWS Region.

aws s3 cp s3://sagemaker-edge-release-store-us-west-2-<OS>/Certificates/<REGION>/<REGION>.pem .

Running the Edge Manager agent

You can run the SageMaker AI Edge Manager agent as a standalone process in the form of an Executable and Linkable Format (ELF) executable binary or you can link against it as a dynamic shared object (.dll). Linux supports running it as a standalone executable binary and is the preferred mode. Windows supports running it as a shared object (.dll).

On Linux, we recommend that you run the binary via a service that’s a part of your initialization (init) system. If you want to run the binary directly, you can do so in a terminal as shown in the following example. If you have a modern OS, there are no other installations necessary prior to running the agent, since all the requirements are statically built into the executable. This gives you flexibility to run the agent on the terminal, as a service, or within a container.

To run the agent, first create a JSON configuration file. Specify the following key-value pairs:

Your configuration file should look similar to the following example(with your specific values specified). This example uses the default AWS provider("Aws") and does not specify a periodic upload.

{
    "sagemaker_edge_core_device_name": "device-name",
    "sagemaker_edge_core_device_fleet_name": "fleet-name",
    "sagemaker_edge_core_region": "region",
    "sagemaker_edge_core_root_certs_path": "<Absolute path to root certificates>",
    "sagemaker_edge_provider_provider": "Aws",
    "sagemaker_edge_provider_provider_path" : "/path/to/libprovider_aws.so",
    "sagemaker_edge_provider_aws_ca_cert_file": "<Absolute path to Amazon Root CA certificate>/AmazonRootCA1.pem",
    "sagemaker_edge_provider_aws_cert_file": "<Absolute path to AWS IoT signing root certificate>/device.pem.crt",
    "sagemaker_edge_provider_aws_cert_pk_file": "<Absolute path to AWS IoT private key.>/private.pem.key",
    "sagemaker_edge_provider_aws_iot_cred_endpoint": "https://<AWS IoT Endpoint Address>",
    "sagemaker_edge_core_capture_data_destination": "Cloud",
    "sagemaker_edge_provider_s3_bucket_name": "sagemaker-bucket-name",
    "sagemaker_edge_core_folder_prefix": "Amazon S3 folder prefix",
    "sagemaker_edge_core_capture_data_buffer_size": 30,
    "sagemaker_edge_core_capture_data_batch_size": 10,
    "sagemaker_edge_core_capture_data_push_period_seconds": 4000,
    "sagemaker_edge_core_capture_data_base64_embed_limit": 2,
    "sagemaker_edge_log_verbose": false
}

The release artifact includes a binary executable called sagemaker_edge_agent_binary in the /bin directory. To run the binary, use the -a flag to create a socket file descriptor (.sock) in a directory of your choosing and specify the path of the agent JSON config file you created with the -c flag.

./sagemaker_edge_agent_binary -a <ADDRESS_TO_SOCKET> -c <PATH_TO_CONFIG_FILE>

The following example shows the code snippet with a directory and file path specified:

./sagemaker_edge_agent_binary -a /tmp/sagemaker_edge_agent_example.sock -c sagemaker_edge_config.json

In this example, a socket file descriptor named sagemaker_edge_agent_example.sock is created in the /tmp directory and points to a configuration file that is in the same working directory as the agent called sagemaker_edge_config.json.