What is Serverless Computing?

Maintaining a physical or virtual server comes with its challenges, including significant upkeep costs and the need for skilled personnel. Serverless computing offers a cost-effective solution by enabling developers to build and deploy applications on the cloud without worrying about infrastructure management.

In this article, we’ll explore the concept of serverless computing, its practical applications, and its advantages for developers and businesses. This topic is especially relevant given the serverless computing market exceeded $9 million in 2022 and is projected to grow by 25% over the next decade. Let’s dive in.

Definition and Overview

Imagine if your monthly bills for things like electricity and water were based just on how much you used instead of a flat fee. Serverless computing works similarly—it allows cloud providers to allocate resources based on your application’s demand without requiring you to manage servers directly.

Unlike traditional cloud computing, where servers, storage, and networking need to be set up and maintained, serverless computing abstracts this complexity. The cloud provider handles the infrastructure, automatically adjusting resources as your application needs them. This allows developers to focus on building their applications rather than managing hosting environments.

For instance, if your application typically serves 100-200 users daily, but suddenly spikes to 1 million users, serverless infrastructure will automatically scale to accommodate the surge. In contrast, traditional cloud setups would struggle with such spikes, potentially leading to downtime and the need for manual scaling and additional storage, which could delay performance.

Key Characteristics

Before we discuss what sets serverless computing apart from traditional cloud models, let’s go over some key terms used in serverless computing:

• Function: A small piece of code designed to execute a specific task, such as processing a file upload or handling an HTTP request. Each function works on its own and runs when certain events happen.
• Invocation: This refers to the execution or “calling” of a function, typically triggered by an event.
• Duration: This measures how long a function runs, from the moment it’s invoked until it completes.
• Cold Start: This is the wait time that happens when serverless platforms have to set up resources before they can start running the function.
• Concurrency Limit: The maximum number of instances of a function that can run simultaneously in response to multiple events.
• Timeout: The maximum allowed time for a function to run before being terminated by the serverless platform.

Event-Driven Execution

Serverless computing operates on an event-driven model, often called Function-as-a-Service (FaaS). In this model, applications are broken down into small, independent functions triggered by events like HTTP requests, database changes, or file uploads.

Take the example of an application designed to process images when uploaded to an Amazon S3 bucket. When a user uploads an image, it triggers a function that processes the image and stores the result in another S3 bucket. The function runs only when necessary, making this model both efficient and cost-effective.

Serverless computing allows applications to scale effortlessly, charges based on real usage, and eliminates the need for businesses to manage infrastructure. It’s a game-changing way of doing things that allows businesses and developers to concentrate on creating innovative apps instead of worrying about server management.

Event-driven execution, using file upload as an example. Image by Author

Auto-Scaling

Auto-scaling refers to the automatic adjustment of computing resources in response to fluctuating demand or workload increases. This feature is crucial in serverless computing, as it enhances efficiency and flexibility. By ensuring that resources are only utilized when needed, auto-scaling helps prevent resource wastage during low-demand periods and eliminates downtime during high-demand situations.

For instance, if your application experiences a surge in traffic, instead of facing downtime due to overwhelming requests, the serverless platform automatically allocates additional instances to manage the increased workload. On the flip side, when traffic goes down, the system scales back resources to save money. This dynamic scaling happens without manual intervention, allowing the application to remain both cost-effective and responsive across varying scenarios.

Pay-Per-Use Billing

Serverless platforms use a pay-per-use billing system, meaning you only pay for the actual resources you use instead of what’s allocated. In traditional cloud computing, you might end up paying for unused resources, but in serverless environments, you are billed solely for the compute time that your application actually utilizes.

Costs are metered based on the number of function invocations or the duration of execution, ensuring accurate billing aligned with resource consumption. For example, if your application processes 100 images in a month, you will only pay for the compute time associated with those 100 images rather than for constant server usage.

Abstraction of Server Management

A defining aspect of serverless computing is the abstraction of server management. Developers and businesses are freed from the complexities of provisioning, scaling, and maintaining servers. This allows them to concentrate on addressing core business challenges while leaving server upkeep to cloud providers.

Concurrency Management

Serverless platforms are designed to handle the simultaneous execution of multiple functions efficiently. This capability makes serverless computing significantly faster and more efficient than traditional methods. For example, if users upload images and the serverless provider has a default concurrency limit of 100, any additional requests beyond this limit will be queued and processed in subsequent executions.

Benefits of Serverless Computing

Cost Efficiency

One of the biggest perks of serverless computing is how it saves money. In traditional cloud setups, you usually need to pay for dedicated servers, even when they’re just sitting idle. But with serverless platforms, you only pay for the actual resources you use.

Think of it like using a taxi instead of owning a car. With a taxi, you only pay for the ride, without the extra costs like parking or fuel. Similarly, in serverless computing, you’re charged only for the computing power you actually use. This approach helps businesses save a lot of money and gives them more financial freedom.

Cost efficiency comparison between server types. Source: Cloudflare

Reduced operational complexity

Another great benefit of serverless computing is that it simplifies things. Developers don’t have to spend time setting up and managing servers. Instead, they can focus on what they love—building cool applications! Plus, because applications are made up of separate cloud functions, you can update one function without messing with the others.

Improved scalability

This is one of the most important benefits of a serverless platform and why it is popular among smaller organizations and startups. Serverless platforms make it easy for developers to scale their operations automatically when demand increases. For functions that experience request fluctuations, serverless platforms scale to meet these requests by increasing or decreasing resource allocation, hence ensuring computing resources are optimized.

Faster time to market

With serverless applications, you can launch new features quickly and get feedback from users right away. This is super important for startups, as it means less time and fewer people are needed to build applications.

Reliability

Serverless applications can run from anywhere, which means they often perform better and have lower delays compared to traditional setups.

Serverless Architecture and How It Works

Serverless architecture lets developers build applications without the hassle of managing the servers that host them. There are two main models for building serverless apps:

1. Backend as a Service (BaaS): This model is perfect for creating the backends of web and mobile apps. Developers don’t need to worry about coding backend features like databases or user authentication, which speeds up the development process. Some popular BaaS providers are Firebase, SupaBase, and AWS Amplify.
2. Function as a Service (FaaS): In this model, developers write code that runs on the platform without needing to manage resources. The code is triggered by events, like a user action or a change in a database. Examples of FaaS providers include AWS Lambda, Azure Cloud Functions, and Google Cloud Functions.

FAAS and BAAS serverless cloud architectures. Source: Journal of Cloud Computing

The goal of serverless architecture is to make life easier for developers by taking care of server management. Here’s how it all works:

1. Function Creation: Developers write code in small parts, called functions, that each do a specific job.
2. Function Development: These functions are then packaged and deployed to a serverless platform like AWS Lambda.
3. Event-Driven Execution: Functions are activated by specific events, like database changes or user requests.
4. Auto-Scaling: The platform automatically adjusts resources based on the workload. For example, it allocates more power when a function gets a lot of traffic.
5. Transient Containers: When a function runs, it creates temporary containers to access the necessary resources. Once the task is done, these containers are deleted.
6. Billing: You only pay for the execution time and resources your functions actually use.
7. Statelessness: Each time a function runs, it doesn’t remember past information. Any needed data is saved in a database or stored elsewhere.
8. Logs and Monitoring: Serverless platforms offer tools to help you track how well your applications are running and identify any issues.

You might wonder if serverless architecture is the same as container architecture since both make it easier for developers. They do share similarities, but with serverless, you don’t have to think about scaling when traffic goes up—the platform does that for you automatically. In a container setup, you would need to manage scaling with tools like Kubernetes, which takes away some of the simplicity that serverless offers.

Overall, serverless architecture is great for smaller applications because it allows developers to break them into smaller, manageable parts that can be run as independent functions.

Serverless Computing Platforms

The Evolution of Serverless Computing

Before Google App Engine made its debut in 2008, the first “pay-as-you-go” platform for code execution was Zimki, although it was eventually shut down. When Google App Engine first launched, it only supported Python and featured metered billing for applications, including the popular app SnapChat. By 2010, another platform called PiCloud started offering Function as a Service (FaaS) support specifically for Python applications.

In 2014, Amazon Web Services (AWS) popularized the serverless model with the release of tools like the AWS Serverless Application Model (AWS SAM) and Amazon CloudWatch. This trend continued in 2016 when Google introduced Google Cloud Functions, and Microsoft followed suit with Azure Functions. Since then, various serverless platforms have emerged, including Alibaba Cloud’s Function Compute and IBM Cloud Functions.

To further enhance serverless computing, serverless databases have been developed. AWS provides Amazon Aurora, a serverless database based on MySQL and PostgreSQL, while Azure offers Azure Data Lake, and Google provides Firestore.

Serverless cloud platforms. Source: Network Interview

Practical Applications and Use Cases

Serverless computing is incredibly versatile and can be used for various applications, including:

Websites and APIs

Building web applications and REST APIs is one of the most common uses of serverless computing. With a serverless infrastructure, applications can automatically scale based on user demand, ensuring a seamless user experience.

Media Processing

Serverless architecture simplifies media processing. For instance, users can upload images from different devices, and a single serverless function can handle the processing without compromising performance. Imagine a user uploading an image to an S3 bucket, which triggers an AWS Lambda function to add a watermark or create a thumbnail.

Chatbots

Serverless architecture is ideal for developing chatbots that respond to customer inquiries. Companies only pay for the resources the chatbot uses. For example, Slack employs serverless architecture to handle varying bot requests efficiently, preventing bandwidth wastage.

Webhooks

Serverless platforms can also be used to create webhooks that interact with SaaS vendors via HTTP endpoints. This setup minimizes maintenance costs and offers automatic scaling for webhook functionalities.

IoT Applications

Coca-Cola employs serverless architecture in its Freestyle vending machines, allowing customers to order, pay, and receive payment notifications seamlessly. By shifting to a serverless model, Coca-Cola reduced its annual operational costs from $13,000 to just $4,500.

Data Processing

Major League Baseball Advanced Media developed Statcast using serverless architecture to provide users with real-time sports metrics. Serverless computing processes data efficiently to deliver insights during baseball games.

Event-Driven Applications

Serverless architecture is perfect for event-driven applications. For example, it can monitor database changes and trigger actions based on those changes, ensuring responsiveness and efficiency.

Serverless Edge Computing

Traditional cloud applications can suffer from latency and bottleneck issues due to data traveling long distances from centralized servers. Serverless edge computing addresses this challenge by distributing computing resources across various locations. This setup enables serverless applications to run closer to end-users, enhancing performance and reducing latency.

Here are some use cases for serverless edge computing that optimize user experience:

• Personalized Experiences: Users can receive content tailored to their preferences, location, and device type.
• Video Streaming and Gaming: Processing requests closer to users significantly decreases latency and buffering.
• Security and Authentication: By spreading workloads across multiple edge locations, malicious traffic can be filtered before reaching central infrastructure.
• IoT Devices: Serverless edge computing allows IoT devices to operate efficiently with resources located nearby.

Challenges and Considerations

While serverless computing offers numerous advantages, there are also some challenges to keep in mind:

• Vendor Lock-in: Most cloud providers offer a variety of services that work well with serverless applications. While it’s possible to use services from different vendors, staying within a single provider is often easier for integration.
• Less Control: Users have limited control over the server environment. If an issue arises, such as an outage, the cloud provider is responsible for resolution.
• Cold Starts: When a function hasn’t been invoked for a while, it may take longer to execute, introducing latency that could affect user experience.
• Security Concerns: Trusting a third-party provider with your data can expose applications and user information, especially if servers aren’t configured correctly.
• Debugging Complexities: Testing serverless applications locally can be challenging due to their unique features, making integration tests between frontend and backend difficult

Real-World Applications of Serverless Architecture

Many leading companies have embraced serverless architecture to enhance their operations:

• Netflix: Uses AWS Lambda for data processing tasks, allowing for effortless scaling during peak times.
• Airbnb: Implements serverless functions to handle user authentication and notifications, improving response times without over-provisioning resources.

Conclusion

Serverless architecture revolutionizes how applications are built and scaled. By leveraging automatic scaling, cost efficiency, and improved developer productivity, businesses can quickly respond to changing demands while focusing on innovation rather than infrastructure management. Embracing serverless computing can lead to enhanced performance and user experiences in a variety of applications.

Ready to embrace the future of application development? Start exploring serverless architecture today! Check out our comprehensive guide on getting started with AWS Lambda for more insights!