A Practical Guide to AWS Lambda

Being able to run your code in the cloud without worrying about the underlying servers, scaling, or maintenance seems like a dream. AWS Lambda does just that — it’s a serverless computing service that lets you run code in response to events, automatically managing the computing resources for you.

In this guide, we’ll dive into the practical aspects of AWS Lambda, stripping away the fluff to focus on what really matters: how you can use Lambda effectively in your projects. Whether you’re building microservices, automating tasks, or preparing for a system design interview, this guide will equip you with the knowledge and examples you need to succeed.

Getting Started with AWS Lambda

To get started, let’s walk through a basic example of deploying a Python function on AWS Lambda using Boto3, AWS’s SDK for Python.

Step 1: Writing the Lambda Function

Let’s say we want to create a Lambda function that processes an image uploaded to an S3 bucket and generates a thumbnail.

import boto3
from PIL import Image
import io

s3_client = boto3.client('s3')

def lambda_handler(event, context):
    bucket_name = event['Records'][0]['s3']['bucket']['name']
    object_key = event['Records'][0]['s3']['object']['key']

    response =…