Any recommended approach to periodically refresh data in sage maker inference endpoint? (from s3/redshift)

Unfortunately SageMaker does not have this functionality built in, however, given the requirements, here's a recommended approach to periodically refresh data in the SageMaker inference endpoint:

Scheduled Updates:

• Instead of manually updating the endpoint configuration, automate this process by scheduling updates.
• Use AWS Lambda functions triggered by Amazon CloudWatch Events to monitor the S3 bucket for new data.
• When new data is detected, trigger a Lambda function to update the endpoint configuration.

More info:

1. Automation via AWS Lambda and CloudWatch Events [1] :

   • Utilize AWS Lambda, a serverless computing service, to automate the process of updating the endpoint configuration.
   • Configure AWS CloudWatch Events to trigger Lambda functions at specific intervals (e.g., daily or weekly).

2. Monitoring S3 Bucket for New Data [2] :

   • Set up the Lambda function to monitor the designated S3 bucket for new data arrivals.
   • You can use the s3:ObjectCreated event to trigger the Lambda function whenever new CSV files are uploaded to the S3 bucket.

3. Endpoint Configuration Update :

   • Once the Lambda function detects new data, it triggers the process of creating a new endpoint configuration.

4. Automated Endpoint Update :

   • After the endpoint configuration is updated, trigger an update to the SageMaker endpoint itself to incorporate the changes.
   • This can be achieved programmatically using the AWS SDK or AWS CLI within the Lambda function.

By implementing scheduled updates through AWS Lambda and CloudWatch Events, you can automate the process of refreshing data in the SageMaker inference endpoint based on the availability of new data in the S3 bucket. This approach reduces manual intervention, improves efficiency, and ensures that your endpoint stays up-to-date with the latest data for inference processing.

References:

[1] Tutorial: Schedule AWS Lambda functions using EventBridge - https://docs.aws.amazon.com/eventbridge/latest/userguide/eb-run-lambda-schedule.html

[2] Tutorial: Using an Amazon S3 trigger to invoke a Lambda function - https://docs.aws.amazon.com/lambda/latest/dg/with-s3-example.html

By following these approaches, you can automate the process of keeping your SageMaker inference endpoint up-to-date with the latest data from S3 or Redshift, reducing manual effort and ensuring consistency and accuracy in your predictions.