A lambda to invoke an AWS SageMaker model endpoint with test data stored within an S3 Bucket. For analyzing a dataset to generate baseline constraints. Allowing for monitoring machine learning (ML) model quality to determine if new model predictions are accurate or not, additionally detect changes in properties

This repository does not create the AWS Simple Queue Service, this is created via Terraform found here terraform-aws-machine-learning-pipeline. Additionally, data uploaded for ML purposes can be found here ml-data-copy-to-aws-s3. For more details on the entire flow and how this lambda is deployed, see aws-automlops-serverless-deployment.

The diagram below demonstrates what happens when the lambda is trigger, when a new message is placed on the SQS.

graph LR
  S0(Start)
  T1(Check endpoint is available)
  T2(Configure Predictor for endpoint)
  T3(Pull test dataset from S3 Bucket)
  T4(Use test data as payload for invoking endpoint)
  E0(End)

  S0-->T1
  T1-->T2
  T2-->T3
  T3-->T4
  T4-->E0

• Python
• Docker for Desktop
• Amazon Web Services

1. Build the docker image locally:

   docker build --no-cache -t aws_lambda:local .
   

2. Run the docker image built:

   docker run --platform linux/amd64 -p 9000:8080 aws_lambda:local
   

3. Send an event to the lambda via curl:

   curl "http://localhost:9000/2015-03-31/functions/function/invocations" -d '{<REPLACE_WITH_JSON_BELOW>}'
   

    {
      "Records": [
        {
          "messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
          "receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a...",
          "body": "{\"endpointName\": \"example\", \"testDataS3BucketName\": \"example-bucket\", \"testDataS3Key\" : \"test-data.csv\"}",
          "attributes": {
            "ApproximateReceiveCount": "1",
            "SentTimestamp": "1545082649183",
            "SenderId": "AIDAIENQZJOLO23YVJ4VO",
            "ApproximateFirstReceiveTimestamp": "1545082649185"
          },
          "messageAttributes": {},
          "md5OfBody": "098f6bcd4621d373cade4e832627b4f6",
          "eventSource": "aws:sqs",
          "eventSourceARN": "arn:aws:sqs:us-east-1:111122223333:my-queue",
          "awsRegion": "us-east-1"
        }
      ]
    }

The GitHub Action "🚀 Push Docker image to AWS ECR" will check out the repository and push a docker image to the chosen AWS ECR using configure-aws-credentials action. The following repository secrets need to be set: