Understanding AWS Serverless: What, Why, and How to Get Started

In today’s digital world, cloud computing is all around us. Over 90% of Fortune 100 companies rely on Amazon Web Services (AWS) to power their applications from Netflix streaming billions of hours of content to Airbnb handling millions of bookings. But beyond these big tech companies, AWS offers powerful tools for developers of all levels to build and deploy applications quickly and easily.

If you’ve ever built a web application locally or deployed it on a traditional virtual machine, you might have run into challenges like managing servers, handling sudden traffic spikes, or dealing with infrastructure failures. Serverless computing eliminates all these concerns, allowing you to focus entirely on writing and deploying code without operational overhead. Put simply, AWS has pioneered serverless solutions, which lets developers quickly deploy their functioning application to the global web while AWS takes care of everything else from provisioning to scaling and maintenance.

Here we’ll go over fundamentals of serverless architecture, explore key services, and provide a step-by-step guide for how to get started.

Benefits of Serverless Computing 🙏

• Automatic Scaling: Applications scale up/down based on demand without manual intervention
• Cost-Effectiveness: You only pay for what you use, such as function execution time and API requests, reducing infrastructure costs
• Reduced Operational Complexity: No need to configure, maintain, or monitor servers, freeing up time for feature development
• High Availability and Fault Tolerance: Applications always remain highly available and resilient to unexpected failures

Key AWS Serverless Services 🗣️

AWS provides several services that power serverless applications. The core ones include:

1. AWS Lambda: Executes code in response to events (e.g HTTP requests, file uploads) without managing servers
2. Amazon API Gateway: A fully managed service for creating, deploying, and managing APIs
3. Amazon DynamoDB: A NoSQL database designed for high performance and scalability
4. Amazon S3: Object storage used for storing + retrieving files
5. AWS Step Functions: Orchestrates workflows for serverless applications
6. Amazon EventBridge & SQS: Event-driven messaging services for decoupling different parts of a project

Server-Based vs Serverless Architecture 👀

When choosing how to deploy applications, developers typically use these two main approaches. Here’s how they compare:

Note: Despite its name, serverless computing is not truly serverless. It still runs on physical servers managed by cloud providers, but just abstracts infrastructure management away from developers.

Real-World Use Cases 💡

• Web Applications: Deploying full-stack applications without managing backend servers, allowing auto-scaling and pay-per-use scaling.
• Data Processing Pipelines: Using Lambda functions to process large volumes of data in real-time for applications like log analysis and event-driven workflows.
• IoT Backends: Managing massive real-time data streams from IoT devices without manually handling infrastructure.
• CI/CD automation: Implementing continuous integration and deployment pipelines using AWS Codepipeline and Lambda.
• Media Processing: Use AWS serverless services for video encoding, image transformations, and content delivery

Setting up Your AWS Environment 🚀

To start working with AWS serverless services, follow these steps. By the end of this section, you’ll have an AWS environment ready to deploy + run your applications effortlessly.

Step 1: Create an AWS Account

• Sign up at AWS console using email address (use free tier as needed)

Step 2: Set up IAM Roles and Policies

Before deploying any serverless function, it is important to set up Identity and Management (IAM) users and roles. AWS services operate under strict access control policies (for good reasons), and without proper permissions, your functions won’t be able to interact with other AWS resources. We need these IAM policies for security, specific access control, and service-to-service authentication. IAM users represent individuals/applications that need access to AWS, and IAM roles are given to AWS services to allow them to perform actions securely without needing long-term credentials.

So to start, create an IAM user with permissions for AWS Lambda, API Gateway, DynamoDB, and S3 (attach the administrator access policy for simplicity or use least-privileged policies for security)

Next, create any necessary IAM Roles with permissions depending on which services interact.

Example Lambda:

At this point, you have successfully created your AWS account, configured IAM users and roles, and defined necessary permissions for your serverless functions. With this environment in place, you can now start deploying AWS Lambda functions, setting up API Gateway endpoints, and integrating storage solutions like DynamoDB and S3 along with hosting web applications on services like Amplify.

Conclusion 🎯

That’s all there really is to start working with AWS serverless! Now that you’ve set up your AWS environment and understand the core services, you’re ready to deploy, scale, and optimize your application with ease. From here, you can start experimenting with all the different features to see how to best build and refine your application to take maximum advantage of the cloud boom.

The world of serverless is constantly evolving and becoming more prevalent in the tech world. I highly recommend learning and getting hands-on-experience with AWS because of the ongoing and future implications that cloud computing has to shape software development. So go ahead and launch your first serverless application and experience the magical benefits of the cloud. Anyways, thanks for reading and I would love to hear your feedback in the comments below!