How to deploy FASTAPI to AWS lambda using docker container

In this tutorial, we'll learn how to deploy a FastAPI app to AWS Lambda using a Docker container. We'll start by creating a simple FastAPI app and then containerize it using Docker. Next, we'll deploy our container to AWS Lambda and test it out There are many benefits to deploying FastAPI to AWS Lambda using a Docker container. First, it allows you to package your application and all its dependencies in a single container, which makes deployment and scaling much simpler. Second, using a container also ensures that your application will always be deployed in a consistent environment, which can help reduce issues with compatibility and configuration. Finally, deploying FastAPI to AWS Lambda using a container can also help improve performance

Assuming you have a FastAPI application called, the following steps will show you how to deploy it to AWS Lambda using a Docker container.

Before starting, install docker and AWS cli

Install AWS CLI from here

Step 1. Create IAM user

In AWS console, go to IAM role and create a user which has access to ECR 

On next select attach existing policies and click on AmazonEC2ContainerRegistryFullAccess


It will provide you an access and secret access key. Save it.


Create Repo on ECR

In aws console, go to Amazon ECR and create repository. After creating, click on it and you can see view push command. CLick on it. You can see following

Now go to you system terminal and write aws configure. Enter you keys, and region, you can  leave output blank or put ‘json’ there.

This is very important, other wise you will get following error

Error: Cannot perform an interactive login from a non TTY device

Create app locally 

First i am going to use a simple  fastapi that just take a string input and return that

This is our repo structure

from fastapi import FastAPI
from mangum import Mangum
from fastapi.responses import JSONResponse
import uvicorn
app = FastAPI()
handler = Mangum(app)

def read_item(text: str):
    return JSONResponse({"result": text})

if __name__ == "__main__":, host="", port=9000)







# Copy function code
# Install the function's dependencies using file requirements.txt
# from your project folder.
COPY requirements.txt  .
RUN  pip3 install -r requirements.txt --target "${LAMBDA_TASK_ROOT}" -U --no-cache-dir
# Set the CMD to your handler (could also be done as a parameter override outside of the Dockerfile)
CMD [ "app.handler" ]

Now run command shows in view push command and upload it to ECR

Till this point, it will give a payload error if you curl this. Ignore it and upload it to ECR.

Load the container from ECR to lambda and create a new function. 


Payload on AWS lambda. 

Create aws lambda function, click container image, select your image.

Then click on test. Choose template as apigateway-aws-proxy


Event JSON a payload ic created, now you need to modify few of its line

At line 4 replace path": "/path/to/resource" to path": "/"

At line replace "httpMethod": "POST" with "httpMethod": "GET”

At line 16 replace "proxy": "/path/to/resource" to "proxy": "/"

At line 117  replace path": "/path/to/resource" to path": "/"

At line 117  replace httpMethod": "POST" with "httpMethod": "GET”


Now click save and test you will get a success message


Now click on configuration tab, then function url and click create.

Change the settings as shown in following figure, leave rest as default


Your api is created. Enjoy



  1. Step1 Install docker
  2. Install aws cli 2
  3. Create lambda docker image