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What Is Serverless Computing and Why To Use It

Last Updated : 09 Feb, 2024
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The main ideology behind serverless computing can be seen in our day-to-day lives. Imagine you want to host a party. There are two ways you can make things work. One way is to manage everything on your own by deciding the menu, cooking the food, setting up the table, and serving the food along with ensuring there are no leftovers or shortage of food. But an easier and serverless way to do this would be to hire a catering company and ask them to take care of all the services and in the end you pay for the food consumed at the party.

Serverless Computing

Thus, you do not need to think about the logistics of how the catering company will ensure food management but can easily enjoy the party. In this article, we’ll discuss serverless computing and will answer your question of Why use Serverless Computing, its elements, its pros and cons, comparison to other backend services, and use case and application of serverless computing.

What is Serverless Computing?

Serverless computing is a cloud computing execution model where the provider provides machine resources on demand or an as-used basis. It takes care of the server and the underlying infrastructure for the user so that the user can easily manage application development. The term ‘serverless’ does not mean that no server is used. In this architecture, the cloud service provider uses servers to execute the code in the developer’s place. The vendors charge the services based on need and you do not have to reserve or pay for a fixed amount of service beforehand.

As compared to traditional server-based architecture, serverless provides more security, scalability, and time efficiency. It has proved useful for applications with unpredictable or variable traffic patterns. Whereas, server-based architecture does not provide this flexibility and is more rigid.

The emergence of serverless computing can be traced back to 2008 when Google released the Google App Engine.

Elements of Serverless Computing

1. Functions as a Service (FaaS)

FaaS or Function-as-a-Service is a cloud computing service where customers can execute code in response to events. It is focused on an event-driven paradigm, where application code and containers only run in response to events and requests. Using FaaS, the server can be divided into functions that are independent of each other and automatically scaled. These functions are isolated where each function is lightweight, performs a single task, and can be loaded and executed quickly.

Some popular examples of FaaS are IBM Cloud Functions, Amazon AWS Lambda, Google Cloud Functions, Microsoft Azure Functions, and OpenFaaS.

2. Backend as a Service (BaaS)

BaaS or Backend-as-a-Service is a cloud computing service where customers can outsource the complete backend for the application and focus on creating and managing the front end. They provide backend functionalities like user authentication, database management, push notifications, storage, and hosting. Its key features include fast development time leading to early entry into the market, low cost, and serverless architecture. Using BaaS is advantageous when creating an MVP(Minimum Viable Product) where it provides pre-built backend features and services.

3. Event-driven Architecture

Event-driven architecture enables the detection of events and allows to act on these events in real-time or near real-time. An event can be defined as a change of state or any notable thing by the application. It provides the advantage of decoupling and important features like improved scalability and responsiveness. Serverless computing uses event-triggered stateless containers to host your services.

Pros of Serverless Computing

  1. Cost Efficiency – Serverless Computing proves to be cost-effective as the services provided follow a pay-per-use model. The customer only needs to pay for the services it uses and does not need to reserve or pay for resources beforehand. This dynamic scaling option in serverless computing reduces the cost as compared to a server-full architecture where resources have to be reserved beforehand. Also, the cost of the hardware of the server and its maintenance and labor costs are reduced as the customer does not need to monitor and maintain the server.
  2. Scalability – Automatic Scaling is one of the biggest characteristics of serverless computing. Applications using a serverless architecture whenever face a sudden hike in traffic, the vendor ensures that it will provide the scaling required to handle all the requests as done for a single request. A server-full application on the other hand may be overwhelmed and gradually fail if traffic levels exceed its limits.
  3. Simplified Deployment – When using a serverless architecture, the customer does not need to worry about uploading the code to the server and making configurations to complete the deployment process. Developers can upload code all at once or function by function for rapid development and easily run them. The vendor takes care of all the configuration management processes so that the main aim and focus of developers is on the code and not the underlying infrastructure.
  4. Enhanced Developer Productivity – Serverless computing takes the hardware management and monitoring resources tasks off the shoulders of the developers so that their main goal remains code for a better application. Thus, with reduced administrative tasks and faster development cycles, developer productivity increases.

Cons of Serverless Computing

  1. Cold Start Latency – Due to the energy efficiency and pricing model, ideal resources are released. This process is called scaling to zero. Whenever a new function arrives at resources scaled to zero, some time is required for the resources to be processed. This latency is called cold start latency. This leads to delayed response, inconsistent performance, and poor user experience. This has a great impact on real-time applications.
  2. Vendor Lock-in – When using serverless computing, all the operations for maintaining the server are handled by the vendor. Thus, over time the customer becomes dependent on a specific service provider. Thus, migrating to another cloud platform comes with a lot of challenges in a serverless computing environment.
  3. Limited Control Over Infrastructure – A major advantage of serverless computing is that it abstracts away the underlying infrastructure. But this abstraction also means that you have less control over the infrastructure. Thus, in a serverless environment, you do not have customization options. Thus, a tradeoff is present in the performance of the application as it might require fine-tuned changes in requirements and operating systems that cannot be handled.
  4. Security Concerns – With a serverless architecture, you face the problem of a shared environment that develops security concerns. In case of external attacks, the security of the application falls on the head of the service provider. The limited visibility into the infrastructure security is also a point of concern.

Comparison to Other Backend Services

1. Traditional Server-Based Models





In a serverless architecture, you follow a pay-per-use model which is a cost-effective solution. Maintaining servers leads to a cost overhead due to constant server maintenance and monitoring.


Vendor lock-in is a major drawback, i.e. migrating to other service providers is difficult. In a service-based model, you can easily move applications between various cloud providers or on-premise servers.


Serverless architecture provides the provision of automatic scaling where resources are added or released based on the traffic. Service-based models require manual intervention to scale up or scale down the application.


Serverless architecture leads to variable performance in case of cold and warm starts. Service-based models have a consistent performance.

2. Microservices Architecture





Serverless architecture centers around individual functions. Microservices architecture centers around independently deployable services.


In a serverless architecture, you follow a pay-per-use model which is a cost-effective solution. Setup, development, and management of microservices is costly as it relies on in-house resources and support.


Serverless functions have limited run time based on the resource allocation done by the vendor. Microservices do not have a limited run time as they do not rely on the vendor’s requirements/

Use Case

Serverless architecture can be used for event-based tasks. Microservices can be used for complex systems with multiple functional components.

Use Cases and Applications

Serverless computing can be used for the following scenarios:

Some real-life examples are:

  • Netflix has been using serverless since 2017 and it handles the platform’s modification, provisioning and user-delivery in real time. It also uses AWS Lambda for its backup mechanism.
  • Slack uses a serverless, cloud-based architecture based on AWS Lambda.
  • Autodesk’s tool Tailor used to build custom Autodesk accounts with all the specifications was built using serverless architecture.
  • Coca-Cola uses a serverless and cloud-based vending machine called Freestyle.

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In conclusion, serverless computing comes with both pros and cons of its own. It is cost-effective, scalable, simplifies deployment, and increases productivity but at the same time makes the migration, testing, and debugging difficult. The limited control over the infrastructure raises many security concerns and also lacks customization. As compared to other backend services, serverless is more efficient and agile. We’ve also discussed various elements of serverless computing like Function-as-a-Service, Backend-as-a-Service, and Event-driven architecture. Thus, it might not be the best solution but has proved to be a good option in various domains with the right tools to leverage its strengths in the application.

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