The Benefits of Serverless Computing Architecture

Traditional server-based architecture revolves around the manual management and operation of servers. With this approach, developers must take an active role in figuring out a solution for application hosting and workload management. This traditional architecture requires continuous (often human-led) monitoring and management to ensure the server environment is secure, efficient, and capable of handling load demands.

When we juxtapose this historical approach with that of the serverless architecture, we see quite clearly how advancements in cloud-native computing bring significant advantages.

In the traditional server architecture, the burden of managing the entire server lifecycle falls on the business — specifically, its engineers. Those management responsibilities include:

• Provisioning hardware, such as physical servers, virtual machines, or API gateways
• Handling operating system and software updates
• Applying security patches

Serverless architecture shifts these responsibilities to the cloud platform provider (such as Google Cloud Platform, Amazon Web Services, or Akamai). Developers no longer need to focus on these concerns; they can focus on their code.

Traditional server architectures typically require manual scaling. Manual scaling requires an organization to predict demand. This may mean pre-provisioning resources to anticipate increased load. It may also mean quickly provisioning more resources after an excessive load has caused availability issues.

Either way, the outcome is suboptimal for businesses. Over-provisioned resources lead to wasteful and costly underutilization. Under-provisioned resources lead to poor performance and a degraded user experience.

In contrast, serverless computing offers automatic scaling. Cloud providers have automated measures in place to adeptly adjust resources in real time to match demand. This ensures optimal resource use without manual intervention. For applications with fluctuating workloads or inconsistent load demands, the flexibility of serverless brings a substantial advantage.

The pricing structure for traditional servers is mostly fixed; businesses pay for the servers they signed up for, whether they’re fully used or not. Keeping costs low with traditional servers requires users to monitor resource use to ensure they’re not paying for more than necessary.

On the other hand, serverless models offer a pay-for-what-you-use approach. When an application is not experiencing any user activity, the hardware that serves the application spins down. Billing is based on actual resource use, which can significantly reduce costs.

Deploying an application to a traditional server architecture can be a tedious process. Setting up and configuring a server is a complex task that many code-focused developers may not have the expertise to perform. Instead, they turn to serverless architectures, which streamline deployment and can significantly accelerate development and deployment cycles.

Managing traditional servers can require significant operational overhead. Servers need to be monitored for availability, security, and compliance. Many businesses don’t have the extra resources available to handle this. Serverless architectures offload this burden to the cloud service provider. By reducing these operational challenges, serverless architecture enables businesses to concentrate on innovation and growth.

Traditional server-based architectures offer control and a sense of familiarity, but this may require resources and expertise that an organization isn’t willing or able to expend. The approach of serverless computing brings efficiency and agility that many businesses value. Organizations can reduce their operational tasks by transitioning to serverless architectures and free up their developers to focus on creating value and fostering innovation.

To better appreciate the efficiency and versatility that serverless computing brings, let’s focus on its inner workings. In this section, we’ll look at key aspects and components of a serverless architecture.

A common use of serverless architecture is function as a service (FaaS), offered by most cloud providers (such as Google Cloud Functions, Microsoft Azure Functions, Akamai EdgeWorkers, or AWS Lambda functions from Amazon). The FaaS serverless technology allows developers to write and deploy an individual function — a small, single-purpose block of code — that is executed on-demand in response to specific events. The function is deployed to a serverless architecture, waiting for some event trigger.

An event trigger can be practically anything — from an HTTP request to a web form submission to the receipt of an SMS message. In the FaaS model, cloud providers host and manage functions. Developers simply need to write the function code and configure the runtime trigger that results in function invocation.

Resource use in the FaaS use case is minimal, making FaaS very attractive to businesses. Computing resources are only used when the function is invoked and executed (which, in many cases, may only be several seconds). Aside from those minimally used computing resources, a small amount of cloud storage is used to store the function code.

Because FaaS is the best-known way of using a serverless computing architecture, the terms “serverless architecture” and “serverless functions” have become practically synonymous.

Serverless architecture is event-driven by nature. Serverless functions are designed to respond to specific triggers or activity in event queues. This means they remain idle until an event occurs, at which point they are instantly executed. The computing resources needed to execute a function are only used when necessary. This is a much more efficient approach than the traditional server model, in which a server constantly runs, even when there is no demand for its computing resources.

When a serverless function is called, the cloud provider dynamically allocates resources to execute the function, managing concerns that include:

• Scaling resources to meet demand
• Load balancing
• Fault tolerance

The cloud provider may use virtual machines, containerization and container orchestration technologies (such as Docker and Kubernetes), or other resources. However, all these infrastructure-related details are abstracted away with a serverless framework.

Developers need only focus on their coding and debugging workflows. Typically, their application code does not need much modification to accommodate a serverless execution. Open source libraries for most major programming frameworks and languages — including Node.js, Python, JavaScript, WebAssembly, and Ruby — make deploying via serverless straightforward. DevOps teams can use their CI/CD pipelines to deploy updated versions of serverless function code.

Serverless architecture has various applications. Common use cases include:

• Facilitating APIs or backend as a service (BaaS)
• Microservices
• Task automation
• Processing real-time data streams
• Web applications (front-end and back-end web apps)
• Handling sporadic or unpredictable workloads

The ability to scale automatically and pay only for the resources used makes serverless architecture ideal for startups and enterprises alike.

We’ve already touched on many benefits of a serverless computing architecture. To review, serverless architecture provides:

• Cost-effectiveness: The pay-for-what-you-use pricing model, in which you pay only for the resources that your serverless functions actually consume, is attractive to many organizations.

• Scalability and flexibility: Serverless architecture automatically adjusts computing resources to match demand, scaling up during peak times and down during periods of low use. This autoscaling and flexibility brings consistent performance regardless of fluctuations in use and without manual intervention.

• Enhanced developer productivity: Your software developers no longer need to handle infrastructure-related management tasks. They can focus on writing code and developing new features. This increases their productivity, accelerates development, and improves time to market.

• Reduced operational overhead: A serverless architecture offloads operational concerns, such as server maintenance, patching, and security, to the third-party service provider. Organizations can instead dedicate their time, human resources, and expertise to more business-critical matters.

Edge computing is a distributed computing approach that brings computation and data storage closer to the location where it is needed (typically, geographically near the end user). Edge computing aims to improve response times and save bandwidth. Edge computing can use a serverless environment, executing serverless functions on resources near the end user.

Integrating edge computing with a serverless computing architecture — such as with Akamai EdgeWorkers — offers improved efficiency for handling high-volume, real-time data processing and delivering an enhanced user experience.

Although serverless computing architecture offers numerous benefits, organizations should also be aware of its limitations, including:

• Cold start problem: The “cold start” issue refers to the latency experienced when invoking a serverless function after a period of inactivity, usually due to initializing the computing resources needed for executing a function. Although many serverless applications may not be noticeably affected, cold starts can impact performance for functions that require extremely quick response times.

• Vendor lock-in: Adopting serverless architecture often means tying yourself to a specific cloud provider's ecosystem. Moving to a different provider may require changes to your application, leading to portability challenges.

• Limited control and customization: In serverless computing with a cloud provider managing your underlying infrastructure, you have less control over your environment and hardware. This constraint can be a drawback for organizations or applications that require specific configurations or customizations.

• Security concerns: Cloud providers generally offer very robust security. However, the shared responsibility model in serverless computing requires a clear understanding of which security aspects the serverless provider manages and which aspects you manage as the serverless customer. 

Serverless architecture provides numerous benefits, but organizations must weigh these against potential limitations, such as cold starts, vendor lock-in, limited control, and security concerns. Understanding these aspects will help organizations make informed decisions about adopting serverless solutions.

When you decide that a serverless approach aligns well with your business needs, it’s time to consider how specific serverless platforms like Akamai can simplify the process of getting started. Embarking on the serverless journey may seem daunting, but adopting the right platform will help you get up and running in no time.

Serverless computing from Akamai centers on Akamai’s edge compute solutions. Akamai allows you to run serverless functions on an edge computing platform that shifts compute and storage geographically closer to your customers. This way, you can optimize the delivery of your serverless applications for low latency, faster response times, improved performance, and enhanced user experience.

Akamai EdgeWorkers allows developers to focus on writing business logic and code whileAkamai handles the executing of functions at the edge on its globally distributed serverless network. With Akamai, end users enjoy serverless computing services that are located closest to them. Organizations get automatic scaling, flexibility, faster cold starts, and a cost-efficient platform to run it all.

Serverless computing architecture is an aspect of cloud computing that has radically shifted how we approach application development and deployment. By abstracting away the complexities of infrastructure management, the serverless approach provides a simple and scalable solution to spinning up infrastructure with a cost-effective, pay-for-what-you-use pricing model. Developers can focus on writing code — and organizations avoid the operational overhead of managing servers.