3.4. Introduction to AWS Lambda and Serverless Computing

A serverless compute service that lets you run code without provisioning or managing servers. You upload your code (called a Lambda function), and Lambda runs it in response to triggers/events. AWS handles all infrastructure, scaling, patching, and administration.

AWS Lambda is a service that allows you to execute your application code without having to worry about the underlying physical servers. When you write a piece of code, you package it as a 'Lambda function' and upload it. This function can then be executed automatically when certain events occur, like a file being uploaded. AWS manages the servers, so you don’t need to maintain or scale them yourself.

Think of AWS Lambda like a chef in a restaurant who only comes to cook when an order is placed. You don’t need to keep the chef sitting there all day just in case someone wants food; he comes in, cooks the meal, and leaves when the job is done. Similarly, AWS Lambda runs your code when it’s needed, and when it’s not needed, it doesn’t run, thus saving resources.

Automatic scaling: Lambda scales precisely with the size of the workload. Pay-per-use: Charged only for the compute time your code actually runs, billed in milliseconds. Supports many languages: Python, Node.js, Java, Go, C#, Ruby.

One of the main advantages of AWS Lambda is automatic scaling. This means if a lot of requests come in, Lambda can quickly allocate more resources to handle them, and when demand drops, it reduces resources automatically. Additionally, you only pay for the time your functions actually run, not for idle time, which is efficient and cost-effective. Lambda also supports various programming languages, giving you the flexibility to use the one you're most comfortable with.

Imagine a utility bill that only charges you for the electricity you actually use, rather than a flat fee every month. If you are running a lot of devices (like when you have guests over), your bill might be higher, but during times you aren’t using much electricity, your bill drops. AWS Lambda works similarly, charging you based on actual usage.

Upload of files to Amazon S3. Changes in a DynamoDB table. HTTP requests via API Gateway. Scheduled events (like cron jobs).

AWS Lambda is flexible in terms of what can trigger its execution. Some common sources of events include uploading a file to Amazon S3 (like when you save a photo to the cloud), changes occurring in a DynamoDB table (such as adding new records), HTTP requests through API Gateway (when your app calls an API), and reminders that run at specific times (scheduled events). Each of these events can automatically trigger a Lambda function to perform tasks.

Think of a home security system that automatically calls the police whenever a sensor is triggered. Just like the security system reacts to specific events (like the sound of glass shattering), AWS Lambda reacts to events like file uploads and changes, executing your code without requiring you to do anything.

Suppose you want to automatically generate thumbnails for images uploaded to S3: Upload an image to an S3 bucket. This triggers a Lambda function. Lambda processes the image and saves the thumbnail back to S3. No need to manage servers or scale manually—Lambda handles everything.

Let’s say you’recreating a web application where users can upload images. You want to provide thumbnails for faster loading. With AWS Lambda, when a user uploads an image to an S3 bucket, it automatically triggers a Lambda function which processes the image to generate a thumbnail and saves it back to S3. This process is efficient and allows you to focus on your application instead of managing server resources.

Imagine a bakery where customers can order cakes. Once an order is placed, the baker jumps into action to create the cake. The baker doesn’t remain on standby; they only work when an order comes in. Similarly, AWS Lambda functions only execute in response to events, allowing developers to focus on building their applications effortlessly.

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