Why Do We Need Serverless Computing? Detailed Explanation of Everything
Serverless computing is a form of cloud execution in which a cloud provider dynamically allots the computational and storage resources necessary to carry out the execution of a particular piece of code, and then bills the customer for only those resources. There are still servers involved, but their deployment and maintenance are managed entirely by the provider. From the perspective of the team writing and deploying the code, there are no servers to provide or manage. This includes nothing that is bare metal, virtual, or containerized. In the serverless future, you should not be required to perform anything that needs you to manage a host, patch a host, or deal with anything on an operating system level.
When people talk about serverless computing or serverless architecture nowadays, they are talking to function-as-a-service offerings, in which a customer creates code that only addresses business logic and uploads it to a provider. This supplier manages everything related to the supply of hardware, management of virtual machines and containers, and even multithreading, which is typically implemented directly into application code.
Serverless functions are event-driven, which means the code is only executed when triggered by a request. The service provider does not charge a flat monthly price for operating a real or virtual server; rather, they only charge for the amount of compute time that is required by that execution. These functions can be chained together to form a processing pipeline, or they can be used as components of a larger program, connecting with other code running in containers or on traditional servers.
The many benefits of computing without servers
The ability for developers to concentrate on the business goals of the code they write rather than on infrastructural issues is one of the most significant benefits of serverless computing. Another benefit is that organizations only pay for the compute resources they actually use in a very granular manner, as opposed to purchasing physical hardware or renting cloud instances that sit idle for the majority of the time. For example, you may have an application that is dormant most of the time but must process a huge number of event requests at once under certain conditions.
Alternatively, you may have an application that processes data received from IoT devices with occasional or limited Internet connectivity. In either scenario, the traditional method would involve putting in place a huge server that is capable of managing peak work capabilities; however, this server would spend the most of its time being underutilized. Using a serverless architecture would result in you only having to pay for the server resources that you actually employ. Serverless computing could also be advantageous for certain forms of batch processing. A serverless architecture use case that uploads and processes a sequence of individual image files before transferring them to another section of the application is an example of a classic use case for this type of architecture.
The drawbacks of using a system without servers
The fact that serverless services are intended to be temporary makes them unsuitable for activities that need to be carried out over a prolonged period of time. This is the most evident downside of using serverless computing. When using the majority of serverless providers, your code will only be able to run for a few minutes at a time, and if you re-run a function, it will lose all of the stateful data it has previously stored. Another problem is that it could take a few seconds for serverless code to begin running once it has been executed. This is not a major issue in the vast majority of circumstances; nonetheless, you should keep this in mind if your application has particularly stringent latency requirements. One of the most significant drawbacks is that customers cannot easily switch suppliers.
In spite of the fact that open source alternatives are readily available, we are going to discuss the reasons why the big commercial cloud providers have cornered the market on serverless computing. Because of this, the majority of developers end up using the tooling that is offered by the vendor even if they are dissatisfied with it. Incorporating serverless code into in-house development and testing procedures can be difficult because serverless computing is so dependent on the infrastructure provided by the vendor.
