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VOOZH | about |
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VOOZH | about |
Serverless computing simplifies managing digital services, similar to hiring a catering company for a party. Instead of handling all the details yourself, like cooking and serving, you can delegate tasks to a service provider and pay only for what's used. This means less hassle and more enjoyment for you. In this article, we'll explore serverless computing: what it is, why it's useful, and its advantages and disadvantages compared to other backend services. We'll also dive into real-life examples of how serverless computing is applied, giving you a clear understanding of its impact and benefits in the digital world. Whether you're a business owner or a developer, understanding serverless computing can help you make informed decisions about your digital infrastructure and maximize efficiency in managing your online services.
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.
Table of Content
Serverless computing offers backend services based on usage, eliminating the need for users to manage infrastructure. With a serverless provider, users can develop and deploy code without concerns about underlying systems. Companies using serverless vendors are billed according to their computational needs, without the requirement to reserve or pay for fixed bandwidth or server quantities, as the service adjusts automatically. Despite the term "serverless," physical servers remain in use, though developers are shielded from this detail.
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.
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.
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.
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.
Aspects | Serverless Computing | Server-Based |
|---|---|---|
Cost | 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. |
Portability | 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. |
Scalability | 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. |
Performance | Serverless architecture leads to variable performance in case of cold and warm starts. | Service-based models have a consistent performance. |
Aspects | Serverless Computing | Microservices |
|---|---|---|
Granularity | Serverless architecture centers around individual functions. | Microservices architecture centers around independently deployable services. |
Cost | 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. |
Runtime | 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. |
Serverless computing can be used for the following scenarios:
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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.
