Why Should You Go ‘Serverless’? | Pros And Cons Of Serverless

The prominence of the “serverless ” term started to grow when Amazon launched AWS Lambda in 2014. Ever since, we've seen the term rapidly flourish in use and reference, with more vendors entering the market with their solutions (Azure recently went GA with Functions, for example).

What is it all about, and how does the new trend impact how people write and deploy apps? Is "serverless" a paradigm shift or merely a normal evolution of infrastructure as a service (IaaS) and as a service platform (PaaS)? In this post, let’s learn and discuss Whats Server-less Computing?, How it evolved?, What are the benefits/disadvantages of using in business solutions?, Top providers and technology stack with comparisons and some other significant points as well.

What is serverless computing and how it evolved?

"Serverless" refers to a special kind of software architecture in which application logic is executed without visible processes, operating systems, servers or virtual machines in an environment. This is worth mentioning that such an environment runs on top of an operating system that uses physical servers or virtual machines, so it is purely up to the service provider to be responsible for providing and managing the infrastructure. So a software developer focuses on writing code.

Depending on their computation, a company that receives backend services from a serverless vendor is charged and do not have to reserve and pay for a fixed amount of bandwidth or number of servers, as the service is autoscaling. Note that although called serverless, it does use physical servers, but developers do not have to be aware of them.

Then came the cloud, where fixed server numbers or server space amounts could be rented remotely. Developers and business owners that rent these server space set units generally over-purchase to ensure that a spike in traffic or activity would not exceed their monthly limits and break their applications. This meant that much of the paid server space usually went to waste. Cloud vendors have tried to introduce auto-scaling models to address the issue, but even with an unexpected spike in an activity such as a DDoS Attack auto-scaling could end up being very expensive.

Anyone who wanted to build a web application in the early days of the web had to own the physical hardware required to run a server, which is a cumbersome and expensive undertaking.

Major Benefits and Drawbacks of “Serverless”

As we have already mentioned, the main benefits of "serverless" are:

• Reduced time to market, and helps the quicker release of the software.
• Moderate operational and development expenses.
• A much lower scale cost – developers do not need to incorporate scale-up code, and administrators do not need to upgrade existing servers or add additional ones.
• Works with agile development, which allows developers to focus solely on code and deliver much faster.
• Perfectly fits microservices, which could be implemented as functions.
• Brilliantly reduces Software Complexity.
• Simplifies packaging and deployment, and does not require system administration at all.
• Focus on business needs. Abstracting Server-side developers allows your team to concentrate on the application 's business logic.
  

Now, let’s discuss some of the drawbacks of serverless computing:

Vendor lock-in: You should perform by their rules when giving a vendor the reins to control your operations. Also, porting your application to Azure is not accessible if you already set it up on Lambda. The same concern involves coding languages: currently, only Node.js and Python developers can choose between existing serverless options.

Learning curve: You may soon find out that the learning curve for FaaS tools is pretty steep, despite the comprehensive documentation and community resources. Even, if you want to move painlessly to serverless, you may want to break your monolith into microservices, another complicated task to solve. Which is why support from professionals experienced in serverless tools are preferable.

Unfit for long-term tasks: Lambda gives you five minutes to execute a task, and you will need to call another function if it takes longer. Serverless is excellent for short processes in real-time or near-real-time, like sending out emails. Yet long-term operations such as uploading video files would require additional FaaS functions, or be better with architecture that is "server-full."

An Overview Of  Top Serverless Architecture Providers

AWS Lambda

In 2014 a FaaS offering was introduced which belongs to Amazon Web Services. Since its release, Lambda has become synonymous with what serverless means, with the broadest range of services available holding the position of the leading product on the market. Netflix is perhaps the best-known example of public serverless adoption.

Azure Functions by Microsoft

The service launched and began to compete with AWS Lambda in 2016. Azure Functions offers a similar set of services to Amazon, with an emphasis on languages and tools in the Microsoft family.

Functions at Google Cloud (GCF)

Only in 2017, Google launched its solution, one of the four largest. GCF service used to lag behind Azure and Lambda but, as evidenced by GCF release notes, Google managed to fix earlier mistakes during 2018.

IBM Cloud Functions

Relatively new to the serverless genre, with a compelling range of services to deliver, IBM joined the game. OpenWhisk's only managed infrastructure solution within their cloud services is IBM Cloud Functions. But if you want an open-source solution, a more appropriate option would be Apache OpenWhisk.

Is “Serverless” The Future?

Going serverless not only does mean a technical change but also a shift in mindset. The migration will be painful for many companies running on legacy infrastructure and not as cost-effective as it is promised to be for starting organisations. When you already have an established workflow, it is hard to justify adopting FaaS tools to get rid of servers to manage completely.

Wrapping Up

Our team of experts predicts that Serverless/FaaS, along with machine learning, VR and IoT, will reach their productivity plateau in 2-5 years since the technology is already available. *But the real fight here is to determine the breadth of possible use cases and wait for all vendors to have the broader language and functionality pool.

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