metadata

title: IRIS Classification Lambda
emoji: 🏢
colorFrom: indigo
colorTo: blue
sdk: gradio
sdk_version: 5.5.0
app_file: app.py
pinned: false
short_description: IRIS Classification Lambda

IRIS classification task with AWS Lambda

Workflow: use of AWS lambda function for deployment

Local development

Training the model:

bash

python train.py

Building the docker image:

bash

docker build -t iris-classification-lambda .

Running the docker container locally:

bash

docker run --name iris-classification-lambda-cont -p 8080:8080 iris-classification-lambda

Testing locally:

Example of a prediction request

bash

curl -X POST "http://localhost:8080/2015-03-31/functions/function/invocations" -H "Content-Type: application/json" -d '{"features": [[6.5, 3.0, 5.8, 2.2], [6.1, 2.8, 4.7, 1.2]]}'

python

python3 inference_api.py --url http://localhost:8080/2015-03-31/functions/function/invocations -d '{"features": [[6.5, 3.0, 5.8, 2.2], [6.1, 2.8, 4.7, 1.2]]}'

Deployment to AWS

Pushing the docker container to AWS ECR

Steps:

Create new ECR Repository via aws console

Example: iris-classification-lambda

Optional for aws cli configuration (to run above commands):

aws configure
Authenticate Docker client to the Amazon ECR registry

aws ecr get-login-password --region | docker login --username AWS --password-stdin .dkr.ecr..amazonaws.com
Tag local docker image with the Amazon ECR registry and repository

docker tag iris-classification-lambda:latest .dkr.ecr..amazonaws.com/iris-classification-lambda:latest
Push docker image to ECR

docker push .dkr.ecr..amazonaws.com/iris-classification-lambda:latest

Link to AWS Documention

Creating and testing a Lambda function

Steps:

Create function from container image

Example name: iris-classification

Notes: the API endpoint will use the lambda_function.py file and lambda_hander function
Test the lambda via the AWS console

Example JSON object:

{
    "features": [[6.5, 3.0, 5.8, 2.2], [6.1, 2.8, 4.7, 1.2]]
}

Advanced notes:

Steps to update the Lambda function with latest container via aws cli:

aws lambda update-function-code --function-name iris-classification --image-uri .dkr.ecr..amazonaws.com/iris-classification-lambda:latest

Creating an API via API Gateway

Steps:

Create a new Rest API (e.g. iris-classification-api)
Add a new resource to the API (e.g. /classify)
Add a POST method to the resource
Integrate the Lambda function to the API
- Notes: using proxy integration option unchecked
Deploy API with a specific stage (e.g. test stage)

Example API Endpoint URL: https://.execute-api..amazonaws.com/test/classify