In this article, we are going to explain the term Serverless computing. What it is and much more so let’s start.
Serverless computing is a method by which the backend service is provided. it is based on an experiment.
If you use server-less computing you don’t need to worry about the underlying substructure all you need to do just write and deploy the code.
But here one thing is important to remember that is Serverless computing uses a physical server that’s why this service is known as serverless.
What Is Serverless Computing?
Serverless computing is one type of architecture where the execution of code is fully managed by cloud providers instead of the traditional method of developing an application and place them on the server.
Meaning of it that developers don’t need to worry about managing and maintaining the server at the time of code deployment.
but previously developers have to specify how much storage and database capacity was needed at the time of pre-deployment.
Basically server-less computing is an approach of cloud computing in which the customer makes a request for container PaaS ( Platform As A Service) and in return, providers start and stop the service (PaaS) according to customer’s requirements.
Accordingly, customers are no need to require renting or buying servers in advance. The few top serverless including are given below.
- OpenWhisk
- Lambda
- AWS
History Of Serverless Computing
When the internet was first launched at that time it is compulsory to required one physical hardware to run the server.
This will allow you to create web applications, but the initiative was tedious and it was also costly as well.
After that, a cloud came into an eminence, in which one can take a certain amount of server space and fixed the number of servers.
If anyone takes a fixed number of server space that gives the result of the high purchase.
Companies and developers do this to ensure that when the traffic is very high at that time their application doesn’t break and also it will not go beyond its limit as well.
But this is a drawback a large section of server space has wasted to overcome this issue cloud vendors introduce a scaling model.
Arrival Of Serverless Computing
Serverless computing is the best option among a lot of options.
In this developers purchase backend server and pay by using pay as you go
(Pay As You Go is a method of computing billing that is implemented by cloud computing and which is prepared for organization and end-users.) basis.
There are many types of backend services are provided by serverless computing such as database and storage service.
In some situations they have Function-as-a-Service (FaaS) platform and the example of this is Cloudflare workers. FaaS platform executes code they don’t store the data.
Serverless Computing Architecture
In serverless computing architecture, it runs an application that depends on the external function like service and backend services as a service provider.
In the architecture of serverless computing three main components are included that are given below.
- API gateway: This is purely a managed service that is used to define, post, and maintain APIs. For identification of APIs, developers use standard HTTPS request, that connects their presentation level with the function that they write on the serverless platform. For example, amazon serverless service provider offers its own API gateway for its clients.
- Function as a Service (FaaS): This is the layer that accomplishes the application code(business logic ) by using multi-protocol triggers.
- Backend as a Service (BaaS): It is a cloud computing model that is worked as a cloud-based distributed database, that removes the need for the administrative overhead. BaaS service benefits include cloud storage, push notification, server code, user and file management, and many other backend services. so that developers can easily use and integrate into their application.
Real Impact Of Serverless Computing On Big Data
Serverless word in serverless computing is becoming more popular in the world of big data because the whole workload of big data is handled by serverless computing platforms so that there is no need for any extra team form to manage our Hadoop, spark clusters.
- As we know when we are working on many ETL(ETL is one type of data integration refers to three steps that are extracted, transform and load used to blend data from multiple resources.) and analytical platforms,
- we realize that we need many peoples who can set up the Hadoop clusters.
- So it takes lots of effort and time for monitoring and scaling the resources.
- The serverless computer makes it very easy for developers as they don’t need to worry about big data.
- The serverless platform regularly monitors our deployed code and scales up and down as per our usages so the developer doesn’t need to worry about the scalability.
Advantagess Of Serverless Computing
There are several advantages of serverless computing that are listed below.
- Reduced Cost: Serverless computing is one of the profitable alternatives to go for.
- As in the other alternatives here user does not need to required to pay for idle CPU time or unused space.
- Scalability is easier: In this by using serverless architecture developers do not worry about the policies for scale up their code
- because the serverless vendors take care of all the scaling based on pay as you basis.
- Backend codes are simplified: In this developers can easily do simple functions and they can perform single tasks independently.
- and the example of doing this is making an API call.
- Lower time to market: When you using serverless architecture time in the market is reduced
- and to achieve bug fixing and new features there is no need for any complicated process to be deployed.
Disadvantages Of Serverless Computing
The Disadvantages Of Server-less Computing are given below.
- In Serverless Computing there is no access to a virtual machine, operating system, and runtime environments.
- Executing serverless computing is very time-consuming.
- For Example, Lock-In Effect means when you change providers you have to modify all your event-based functions.
- In serverless computing complex monitoring and debugging and bug analysis are not possible.
