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What are the Benefits of Serverless Computing?

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Function as a service (FaaS)

FaaS is an implementation of serverless architecture, also known as serverless functions. These are small snippets of dedicated code or simply functions that have to be deployed. They are treated as independent working pieces which are triggered by specific pre-defined events. The FaaS provider then executes, scales and bills function as isolated instances based on demand.

Applications of Serverless Computing

With all the advantages discussed above, it is evident that the serverless computing architecture can enhance many applications and can be used to create new ones. Let’s take a look at some applications highlighted in a survey by Hossein Shafiei, Ahmad Khonsari, and Payam Mousavi.

Urban Management systems

Due to its efficiency and cost-effectiveness, serverless computing can be used to deploy many public sector projects such as:

  • smart waste management:

This smart bin solution is part of a garbage collection system that involves several IoT (Internet of Things) sensors connected to waste cans which stream data to the cloud where analytics are performed to suggest the most efficient route for the waste collection department.

  • oil and gas field management systems:

A federation of serverless edge computing which allows reliable and flawless green oil and gas extraction based on real-time analytics.

  • serverless platforms for land valuation:

This GIS (Geographic Information System) platform is based on a serverless cloud open source geospatial software stack, which allows authorities to store, view, analyse, and share real estate data and maps on the web.

Artificial Intelligence and Deep Learning

The survey also highlights how deep learning or machine learning models performance can be enhanced with the help of serverless architecture as it simplifies complex training mechanisms and increases efficiency.


Serverless computing is a type of cloud computing which is easy to maintain and is cost-efficient due to a pay-as-you-go model and auto-scaling of resources based on-demand. This paradigm can not only improve existing frameworks but also make new avenues possible in a wide range of applications involving IoT such as land and resource monitoring systems. It can also solve problems faced by very crucial integration of artificial intelligence in smart cities, homes and industry. 

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