1. Distributed Model Inference Error Logging via AWS SNS

    Python

    To set up distributed model inference error logging using AWS SNS (Simple Notification Service), we will create an SNS topic to which applications can publish error messages. Subscribers to this topic (such as emails, AWS Lambda functions, or HTTP/S endpoints) will receive notifications when errors occur.

    The process involves creating a topic and setting up permissions that define who can publish or subscribe to this topic. The Pulumi code below will demonstrate how to create an SNS topic using the aws-native Pulumi package.

    Here are the steps we will accomplish in the code:

    1. Import the required Pulumi AWS package.
    2. Create an SNS topic for logging model inference errors.
    3. Optionally, we could create a subscription to the topic (the code for creating an SNS subscription is commented out, as you would need to define an endpoint, such as email or Lambda function ARN).

    The following Pulumi program is written in Python and requires the pulumi_aws_native SDK.

    import pulumi import pulumi_aws_native as aws_native # Create an SNS Topic for logging model inference errors. model_inference_errors_topic = aws_native.sns.Topic("modelInferenceErrorsTopic", tags=[{"key": "Purpose", "value": "ModelInferenceErrors"}] ) # Example of how you could add a subscription to the SNS topic. # This is commented out because you need to have a specific endpoint. # Replace `"<your-endpoint>"` with an actual endpoint (like an email or a Lambda function ARN). # model_inference_errors_subscription = aws_native.sns.Subscription("modelInferenceErrorsSubscription", # protocol="email", # Could be "lambda", "http", "https", "sqs", etc., depending on your use case. # topic_arn=model_inference_errors_topic.arn, # endpoint="<your-endpoint>" # The endpoint that will receive the messages (like an email address or a Lambda ARN). # ) # Export the SNS Topic ARN so that it can be used by other services or stored in configuration. pulumi.export("model_inference_errors_topic_arn", model_inference_errors_topic.arn)

    In this program, we define an SNS topic by instantiating an aws_native.sns.Topic resource. We've added tags to help identify the SNS topic's purpose, but tags are optional and can be removed if not needed.

    If you'd like to subscribe to this topic, you'll need to uncomment the model_inference_errors_subscription section of the code and provide a valid endpoint, such as an email address or an AWS resource ARN. The protocol in the subscription should be modified based on the endpoint type (e.g., email, lambda, http, etc.).

    By exporting model_inference_errors_topic_arn, you make the SNS topic ARN accessible outside this Pulumi stack, which can be useful for integrating with different services or applications.

    To put this into context, whenever an error occurs in model inference distributed across your system, a log would be sent to this SNS topic. Subscribers to the topic, which could be monitoring services or incident management systems, would immediately receive these logs, promoting a quick response to the problem.


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