Building and Deploying Serverless Functions with AWS Lambda

AWS Lambda is a powerful service that allows you to run your code without provisioning or managing servers. It’s a serverless computing platform that provides automatic scaling, high availability, and pay-per-use pricing. With AWS Lambda, you can build and deploy serverless functions quickly and easily.
In this article, we’ll walk you through the process of building and deploying a Python-based serverless function using AWS Lambda.

Prerequisites

Before you get started, you’ll need to have the following prerequisites:

1. An AWS account
2. AWS CLI installed on your local machine
3. Basic knowledge of Python programming

Creating a Python-based Serverless Function

Let’s start by creating a simple Python-based serverless function that will return a greeting message. Follow the steps below:

1. Open your preferred code editor and create a new Python file named “lambda_function.py”.
2. Add the following code to the “lambda_function.py” file:

def lambda_handler(event, context):
    message = "Hello, world!"
    return {
        'statusCode': 200,
        'body': message
    }

This code defines a function named “lambda_handler” that accepts two arguments: “event” and “context”. It returns a dictionary containing the HTTP status code and a message. 3. Save the “lambda_function.py” file to your local machine.

Packaging Your Code

Next, you need to package your Python code and its dependencies into a zip file. You can use any packaging tool of your choice, such as pip, pipenv, or virtualenv.
For example, let’s say you have a Python file named “lambda_function.py”. You can package your code and its dependencies into a zip file named “lambda_function.zip” using the following command:

$ pip install requests -t .
$ zip -r9 lambda_function.zip lambda_function.py

The “-t .” option in the first command tells pip to install the dependencies in the current directory, while the “-r9” option in the second command tells zip to recursively add files to the zip file.

Deploying Your Function

Once you have packaged your code, you can deploy it to AWS Lambda. Follow the steps below:

1. Open the AWS Management Console and navigate to the AWS Lambda service.
2. Click the “Create function” button.
3. Select “Author from scratch”.
4. Enter a name for your function, select “Python 3.x” as the runtime, and choose an existing execution role or create a new one.
5. Click the “Create function” button.
6. On the function page, scroll down to the “Function code” section.
7. Select “Upload a .zip file” as the code entry type and upload the “lambda_function.zip” file.
8. In the “Handler” field, enter “lambda_function.lambda_handler”.
9. Click the “Save” button.

Configuring Your Function

After deploying your function, you can configure it by setting environment variables, adjusting memory allocation, and configuring triggers.

For example, let’s say you want to set an environment variable named “ENVIRONMENT” to “prod”.
You can set the environment variable by following the steps below:

1. On the function page, scroll down to the “Environment variables” section.
2. Click the “Edit” button.
3. Enter “ENVIRONMENT” as the key and “prod” as the value.
4. Click the “Save” button.

Testing Your Function

You can test your function using the AWS Management Console or AWS CLI. Follow the steps below to test your function using the AWS CLI:

1. Open a terminal and run the following command:

$ aws lambda invoke --function-name <function-name> --payload '{}' outfile.txt

Replace “” with the name of your function. 2. Check the “outfile.txt” file for the output of your function.

Wrapping Up

In this article, we’ve walked you through the process of building and deploying a Python-based serverless function using AWS Lambda. We covered the prerequisites, creating a function, packaging your code, deploying your function, configuring your function, and testing your function. AWS Lambda is a powerful and flexible serverless computing platform that can help you build and deploy serverless functions quickly and easily. With a little bit of knowledge and some experimentation, you can start building your own serverless functions in no time.