mlapi

preview

Requirements

• AWS CLI
• Python 3
• AWS SAM CLI
• Docker CLI

Create an ECR repository

aws ecr create-repository --repository-name lambda-pytorch-example --image-scanning-configuration scanOnPush=true --region <REGION>

Register docker to ECR

aws ecr get-login-password --region <REGION> | docker login --username AWS --password-stdin <AWS_ACCOUNT_ID>.dkr.ecr.<REGION>.amazonaws.com

Deploying the application

sam build && sam deploy –-guided

Workflow

Here's the architecture of the backend:

• The backend and the frontend communicate with each other over HTTP requests. Here is the workflow:
  • An image is sent from the client through POST request
  • The image is then received via API Gateway
  • API Gateway triggers a Lambda function to execute and passes the image to it
  • The docker image consists of lambda function and dependencies are loaded from AWS ECR
  • The Lambda function starts running: it first fetches the pretrained models from S3 and detects objects from the given image
  • Once the Lambda function is done running, it sends the detection result back to the client through API Gateway.

Reference

• aws:using-container-images-to-run-pytorch-models-in-aws-lambda

aws:Enable CORS on a resource using the API Gateway console