How Serverless Computing Works: An Architectural Overview

When you hear “serverless computing,” what comes to mind? A computing model without servers? While it may sound counterintuitive, serverless computing does not mean the absence of servers; it simply hides the complexity of server management from developers.

Serverless computing began gaining traction in 2014 with the introduction of AWS Lambda at AWS re: Invent. Since then, its popularity has grown exponentially, with other cloud providers adopting similar services and organizations leveraging serverless to benefit from its flexibility, cost-effectiveness, and scalability.

To understand the benefits of serverless computing, it is important to understand the architecture behind it. This article breaks down the core components of serverless architecture and explains how they work together to enable scalable and efficient application deployment.

What is Serverless Computing?

Serverless computing is a cloud computing model that allows developers to build and run applications without managing servers or infrastructure. In traditional computing models, developers need to set up, scale, and maintain servers that execute their applications. However, with serverless computing, the cloud provider fully manages these tasks which allows developers to focus solely on writing and deploying the business logic of their applications.

In a serverless setup, developers write functions that execute in response to specific events, such as HTTP requests or database changes. These functions can be written in any programming language. Also, they are executed on demand, so you only pay for the actual compute time your function uses.

One of the key benefits of serverless computing is its ability to scale automatically. For example, suppose your application experiences a sudden spike in traffic. In that case, serverless platforms can instantly create more instances of the function to handle the load, without any manual intervention. Conversely, when the traffic drops, the platform scales back down which ensures you are not paying for unused resources.

Serverless computing is ideal for workloads that don’t require constant, predictable resource usage, such as microservices, APIs, or background tasks like image processing or data analysis.

Core Components of Serverless Architecture

Serverless architecture consists of various components that work together to enable seamless application deployment without the need to manage infrastructure. The following are the core elements of a serverless architecture.

1. Function-as-a-Service (FaaS): FaaS is at the heart of serverless architecture. It allows developers to write and deploy individual functions, which are small units of business logic, that execute in response to specific events. Examples of FaaS include AWS Lambda, Google Cloud Functions, and Azure Functions.

2. Event Sources: Serverless architectures are event-driven, meaning that functions are triggered by specific events that occur within the system. An event is any change or action that happens in the system and they serve as the signals that activate serverless functions. Events can come from various sources which include:

   • HTTP Requests: A user accessing a web application triggers a function via an API Gateway.

   • File Uploads: Uploading a file to cloud storage (e.g., AWS S3) triggers a function to process the file.

   • Database Changes: Modifying or adding data to a database triggers corresponding functions.

   • Scheduled Tasks: Cron jobs or scheduled triggers initiate functions at specified times.

3. API Gateway: An API Gateway acts as an intermediary between clients and serverless functions. It routes incoming requests to the correct function, handles authentication, validates requests, and manages rate limiting to avoid overloading the system. API Gateways streamline the process of exposing serverless functions as APIs, providing a uniform interface for interacting with different backend functions. Examples of API gateways include AWS API Gateway, Azure API Management, and Google Cloud Endpoints.

4. Backend-as-a-Service (BaaS): In serverless architectures, Backend-as-a-Service (BaaS) solutions provide essential backend services without the need for developers to set up and manage servers. These services handle functions such as authentication, databases, and messaging. For example, Firebase Authentication can be used for managing user logins, AWS Cognito for identity management, DynamoDB for database management, and Amazon SNS or SQS for message queuing. Other BaaS examples include Azure Functions for serverless backend tasks, Google Firebase for app development, and Twilio for integrating messaging and voice service.

5. Managed Cloud Services: Serverless applications often rely on managed cloud services to handle tasks such as data storage, monitoring, and performance logging. These services are fully managed by cloud providers, allowing developers to integrate them into their applications without the need for infrastructure setup. Some of these cloud services may include:

   • Storage services like AWS S3 or Google Cloud Storage for file management

   • Databases like DynamoDB or Cosmos DB and Google Firestore for managed NoSQL databases. Amazon RDS and Google Cloud SQL for relational databases.

   • Monitoring and Logging tools like AWS CloudWatch or Azure Monitor to track the application’s performance, manage logs, and ensure the system is running smoothly.

How Serverless Architecture Works

Serverless architectures use an event-driven model where specific events trigger small, self-contained functions. Here is a step-by-step overview of how it works:

1. Events and API Gateway: Serverless functions are activated by events. When a user sends an API request, the API Gateway acts as the front door, receiving and routing these requests to the appropriate serverless function for processing. The Gateway manages incoming traffic and ensures requests are properly directed.

2. Authentication Layer: Before any request reaches the actual function, it passes through the authentication layer. This layer integrates with the API Gateway and acts as a security checkpoint, verifying user identities through tokens, API keys, or login credentials. It ensures only authorized users can access specific functions and resources within the application.

3. Function Execution: Once authenticated, the triggered function is executed within an isolated environment, typically a container, managed by the cloud provider. These containers are created on demand, execute the function, and are disposed of once the function completes. This on-demand creation and destruction of containers allow serverless applications to scale automatically without manual intervention.

   What Happens to the Containers After Execution? After the function completes execution, the container is terminated or reused if subsequent invocations are within a short time. This "stateless" nature of serverless containers means that they don’t store data between executions which reduces overhead.

4. Interaction with Managed Services: Serverless functions can interact with other managed services during execution, such as retrieving or storing data in a cloud database, writing logs to a monitoring service, or sending notifications via messaging services.

5. Scaling Automatically: Serverless architecture scales seamlessly. When multiple events occur simultaneously, the platform automatically provisions additional containers to handle the load. Conversely, if no events are generated, no resources are consumed, ensuring cost-efficiency.

6. Response to the Event: Once the function completes execution, it sends the result back to the triggering source. For example:

   • An HTTP request receives a response from the API Gateway.

   • A file processing function uploads the processed file to cloud storage.

A Sample Serverless Architecture Flow

The following diagram illustrates the typical flow of a serverless application using AWS services, demonstrating how different components interact to process a request;

1. Clients send requests through Amazon API Gateway, which serves as the entry point

2. AWS Cognito handles user authentication and authorization

3. AWS Lambda executes the business logic in response to the authenticated request

4. Lambda functions interact with DynamoDB for data storage and S3 for file storage as needed

5. The response flows back through API Gateway to the client

Serverless vs Traditional Architecture

Traditional cloud architecture encompasses models like Infrastructure as a Service (IaaS), such as Amazon EC2 and Google Compute Engine, where developers manage virtual servers, and Platform as a Service (PaaS), like Heroku or Azure App Services, which streamlines deployment but still requires oversight of runtime environments. These architectures demand significant manual intervention compared to the fully managed, event-driven nature of serverless computing.

The following table outlines the key differences between serverless and traditional architectures:

Serverless computing represents a transformative approach to application development and deployment. In this article, you have gained a clear understanding of the architecture, components, and workflows of serverless computing. While it unlocks incredible potential, it is not a one-size-fits-all solution. Choosing between serverless and traditional architectures depends on your unique needs. Consider factors such as the nature of your workloads, budget constraints, and the specific requirements of your application to make the best decision.