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---
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 <aws_region> | docker login --username AWS --password-stdin <aws_account_id>.dkr.ecr.<aws_region>.amazonaws.com
- Tag local docker image with the Amazon ECR registry and repository
> docker tag iris-classification-lambda:latest <aws_account_id>.dkr.ecr.<aws_region>.amazonaws.com/iris-classification-lambda:latest
- Push docker image to ECR
> docker push <aws_account_id>.dkr.ecr.<aws_region>.amazonaws.com/iris-classification-lambda:latest
[Link to AWS Documention](https://docs.aws.amazon.com/AmazonECR/latest/userguide/docker-push-ecr-image.html)
### Creating and testing a Lambda function
<b>Steps</b>:
- 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 <aws_account_id>.dkr.ecr.<aws_region>.amazonaws.com/iris-classification-lambda:latest
### Creating an API via API Gateway
<b>Steps</b>:
- 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://<api_id>.execute-api.<aws_region>.amazonaws.com/test/classify |