Serverful vs Serverless: Which One is Right for Your Needs?

Are you a web developer looking to deploy your website, but unsure which approach to take? The world of hosting can be overwhelming, with two major options available: Serverful and Serverless. 

In the old days, there was no serverless approach to computing.

But in recent years, cloud computing has revolutionized the way we deploy and manage web applications. Serverless computing has gained tremendous popularity, with many developers opting for this approach. However, choosing the right option for your project can be challenging, given the fundamental differences between Serverful and Serverless computing.

In this blog post, we'll take a deep dive into both Serverful and Serverless architectures, exploring their key features. We'll provide you with the insights you need to make an informed decision on which approach is the best fit for your specific requirements.

With that said, let’s get started with the Serverful architecture.

Overview of the Traditional Serverful Architecture

Serverful architecture involves the use of long-running physical servers to perform various computing tasks, such as running software programs and storing data. Essentially, it is like having a computer located remotely accessed via the internet or other network connection. 

These servers are responsible for running applications and services required by the business. 

In a serverful architecture, you have complete control over the computing infrastructure, allowing them to customize it to meet their specific needs. This approach provides high levels of performance, security, and reliability because the infrastructure can be tailored to work optimally with the applications and services being run. 

However, serverful architecture can be quite expensive and complex to manage. The servers have to be purchased and maintained, which can be a significant investment, especially for smaller companies & individuals. 

Additionally, the setup and maintenance of the infrastructure require specialized knowledge and expertise that may not be available in-house. Scaling the infrastructure can also be a challenge in a serverful architecture.

And that’s where Serverless Architecture comes into the picture.

What Is Serverless and How Is It Different?

In basic terms, serverless is a serverful alternative that frees developers from maintaining servers. Because of this, developers do not have to be concerned about managing servers.

Behind the scenes, serverless computing still uses servers. The key difference is that users only pay for the computing resources they use, without the need to manage and maintain physical servers themselves. This saves developers from having to manage the underlying infrastructure so they can concentrate on their main skills, such as developing and releasing apps. 

One of the best features of serverless is autoscaling which means that more server space is automatically added when needed, but this can still be expensive if there's a sudden spike in traffic, like from a DDoS attack.

In the model above, you as developers can create events that tell the app what to do when a user takes a specific action. For instance, when a user uploads a CSV file, this is considered an event where you can trigger a specific function to format the data in a certain way. 

And because of this, serverless can also be known as Function-as-a-Service (FaaS).

Serverful vs Serverless

Now, we have a brief idea about what are Serverless and Serverful, let’s compare them to get a complete idea about which one to use, and when.

Performance and scalability

When it comes to how quickly a computer can perform certain activities, using a long-running server, also known as serverful computing, can be quicker than using short-lived functionalities from serverless computing. This is because serverless computing requires the function to be started each time it is used. This is known as a cold start. 

When it comes to scalability, serverful computing may be slow and expensive. This is because it frequently requires more servers and IT staff to keep it working. However, serverless computing is designed to withstand large fluctuations in demand. The business does not need to take any more action because the cloud provider will ensure that there are enough resources to handle the request.

Cost-effectiveness

Overall, serverless computing is a lot more cost-effective. The reason is simple -- you pay for what you use and during the hours when you have low traffic, your serverless cost drops as well.

On the other hand, with serverful, you need to anticipate the traffic and have some of the servers always running even when the traffic is low.

Caching

When users use the internet, they submit requests to servers in order to get information. These requests can be set up in either a serverful or serverless architecture. 

In serverful architecture, the server is always running and processes requests, saves data, and remembers previously used information. This implies that it can operate swiftly and efficiently, which is beneficial to those who use the server. 

Some businesses, however, rely on serverless architecture. In this setup, servers only run for a short time when someone needs them. This might cause issues since the server may not recall previously used information. This can make responding to requests take longer.

One way to fix this is to use a special database called Redis to store information. 

Another way to fix this problem is to store information on the user's computer or phone instead of on the server. The only concern is, it's important to make sure that the information being stored is safe and secure.

Database Connection Pooling 

Connection Pooling is a solution to prevent your application from exhausting all available database connections. It works by keeping some connections to the database open and available to use whenever needed. This also saves time and resources because opening and closing connections takes a lot of effort. 

Because serverful architecture has long-running servers, pooling connections is easier. On the other hand, in a serverless app, each user request usually results in a new function running in an isolated environment, you can easily exhaust all the database connections.

In serverless architecture, cloud providers like Amazon RDS or Azure SQL Database manage the connection pooling. They automatically take care of the connections for the application, making it easier to use a database in a serverless environment.

Moreover, as more apps are moving to serverless, companies like PlanetScale have launched serverless drivers to seamlessly integrate database operations into your serverless apps.

Long-Running Tasks

Since serverful systems have long-running tasks, they can be managed by the server using background threads or worker processes. However, in serverless systems, long tasks can be handled using asynchronous functions. These functions act as mini-programs that can run independently, complete tasks, and not keep the user waiting.

Additionally, cloud provider services such as AWS Lambda or Azure Functions can assist in managing these tasks.

However, if you have long-running tasks, serverful makes more sense.

Which Architecture to Choose?

As discussed in the earlier sections of this post, there are some jobs such as long-running operations that cannot be easily done in a serverless environment whereas jobs such as auto-scaling are difficult to provision in the Serverful approach.

Your decision to choose between serverful and serverless eventually boils down to the needs and requirements of your project. For example, Amazon Prime Video recently switched from a serverless model to a monolithic one, which reduced infrastructure costs by nearly 90%.

Therefore, when selecting the computing architecture, you have to base your decision on serveral important factors such as cost, scalability, performance, and management complexity.

In scenarios where businesses have predictable workloads and require high levels of control over their infrastructure, serverful computing may be a better choice. This is because businesses can optimize their hardware and software configurations for maximum performance, and have greater control over their data and security. 

However, for businesses with unpredictable workloads and the need for automatic scaling, serverless computing may be a more effective solution. Serverless computing allows businesses to scale seamlessly and only pay for the resources they use, resulting in significant cost savings.

Additionally, serverless computing can be an ideal solution for businesses that need to quickly deploy new applications and services without the need for extensive IT management.

Whether you go with serverful or serverless, you still need a frontend ready to be deployed and turned into a full-stack app. For this, you can use the Locofy.ai plugin to generate modular, and highly extensible Next.js apps directly from your design files.

You can use the auto layout feature on Figma to make your designs responsive on the Locofy.ai plugin and even if your designs don't utilise auto layouts, the plugin offers a Design Optimizer feature that uses AI to apply auto layouts to your design files. Once your designs are responsive, you can use the Auto Components feature to split your design elements into working React components, making them easy to extend.

If you want to learn more about how to convert your Figma or Adobe XD designs to React, React Native, HTML/CSS, Nextjs, and more, check out our docs. Or explore our solution pages for an in-depth look at how Locofy helps you build apps, websites, portfolio pages and responsive prototypes effortlessly using our  low-code platform with seamless AI code generation.