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What Is Serverless Computing and Whay It's Important
The term serverless grew in popularity as Amazon first launched AWS Lambda in 2014. Since then it has grown in both usage and reference, as more and more retailers enter the market with their own solutions.
Serverless Computing is a computing code execution model where the developers are relieved of several time-consuming activities so that they can focus on other important tasks. This trend is also known as Function as a Service (FaaS) where the cloud vendor is responsible for starting and stopping a function's container platform, check infrastructure security, reduce maintenance efforts, improve scalability, so on and so forth at low operational costs. The aim is to develop microservice oriented solutions to help decompose complex applications into small, easily manageable and exchangeable modules.
This brings us to the question - are there really 'serverless' computing services?
Of course, it is only logical that there should be servers in the background, but developers need not bother about the operation or provisioning of these servers; the entire server management is done by the cloud provider. Thus, the developer can devote more of his time to creating effective and innovative codes.
Here is how it works:
- Being serverless, the developers are relieved from the tension of server operation and maintenance and hence, can focus on the codes.
- The developer gets access to a framework with which he can create codes, which are adaptable for IoT applications as well, and that means handling the exodus of inputs and outputs. The cause and effect of the code will be reflected in the framework.
- It takes on the role of a service, by providing all requisites for a functioning application.
The upsides and downsides of serverless computing
Serverless computing has the following benefits:
It Saves Time and Overhead Costs
Many large companies like Coca- Cola and The Seattle Times are already leveraging the benefits of serverless computing to help trigger code in response to a series of pre-defined events. This helps them to manage their fleet of servers without the threat of overhead costs.
One of the main attractions of serverless computing is that it is a 'pay as you use' model. You just need to pay for the runtime of your function - the duration your code is executed and the number of times it's been triggered. You don't have to incur the cost of unutilized functions as seen in a cloud computing model where even 'idle' resources must be paid for.
Nanoservices takes Serverless Computing to a Whole New Level
Serverless architecture gives you the chance to work with several architectures including nano-services. It is these architectures that help you structure your serverless computing application. You can say that Nanoservices is the first architectural pattern because each functionality comes with its own API endpoint and its own separate function file.
Each of the API endpoints points to one function file that implements one CRUD (Create, Retrieve, Update, Delete) functionality. It works in perfect correlation with microservices, another architecture of serverless computing, and enables auto scaling and load balancing. You no longer have to manually configure clusters and load balancers.
Enjoy an Event-based Compute Experience
Companies are always worried about infrastructure costs and provisioning of servers when their Functions call rate become very high. Serverless providers like Microsoft Azure are a perfect solution for situations like this as they aim to provide an event-based serverless compute experience to aid in faster app development.
It is event-driven, and developers no longer have to rely on the ops to test their code. They can quickly run, test and deploy their code without getting tangled in the traditional workflow.
Scaling as Per the Size of the Workload
Serverless Computing automatically scales your application. With each individual trigger, your code will run parallel to it, thereby reducing your workload and saving time in the process. When the code is not running, you don't have to pay anything.
The charging takes place for every 100ms your code executes and for the number of times the code is triggered. This is a good thing because you no longer pay for an idle compute.
Developers can Quit Worrying about the Machinery the Code Runs on
The promise given to developers through IaaS (Infrastructure as a Service)- one of the service models of cloud computing and serverless computing is that they can stop worrying about how many machines are needed at any given point of time, especially during peak hours, whether the machines are working optimally, whether all the security measures are offered and so on.
The software teams can forget about the hardware, concentrate on the task at hand and dramatically reduce costs. This is because they no longer have to worry about hardware capacity requirements nor make long-term server reservation contracts.
Downsides of serverless computing
Performance can be an issue.
The model itself means you'll get greater latency in how the compute resources respond to the requirements of the applications. If performance is a requirement, it's better instead to use allocated virtual servers.
Monitoring and debugging of serverless computing is also tricky.
The fact that you're not using a single server resource makes both activities very difficult. (The good news is that tools will eventually arrive to better handle monitoring and debugging in serverless environments.)
You will be bound to your provider.
It's often hard to make changes in the platform or switch providers without making application changes as well.
The serverless architecture is an innovative approach to deploying as well as writing an application that enables the developers to focus on code. This kind of approach can decrease time to market, system complexity and operational costs. While the third-party services like AWS Lambda are leveraged by AWS to eliminate the need to set up as well as configure virtual machines or physical servers, it also locks in the application as well as its architecture to the particular service provider. In the near future, more movement towards the unification of FaaS frameworks or APIs like IronFunctions can be expected. This will help to eliminate vendor lock-in and allow us to run serverless applications on various cloud providers or even on-premises