Serverless Computing: Moving from DevOps to NoOps

Source – devops.com

While some organizations do better than others when it comes to implementing DevOps, almost everyone agrees it’s a concept easier penned to paper than pinned to reality. The idea of integrating development and operations is smart, but the implementation proves troublesome. A replacement option is thus largely welcomed by developers everywhere.

Enter the new concept of NoOps, which means dropping operations from any consideration during the development cycle. It’s not that operations are being ignored; that would be a foolhardy step backward. Rather, NoOps means never having to worry about where the code runs and, thus, developers are freed from giving operations another thought.

“Serverless computing allows users to run code without provisioning or managing any underlying system or application infrastructure, and they automatically scale to support increasing or decreasing loads,” explained Gartner serverless analyst, Arun Chandrasekaran, in a blog post.

Amazon sparked interest in serverless computing when it announced AWS Lambda at its re:Invent conference in 2014.

“I’d argue that the precursor to serverless computing is cloud IaaS, where the complexity of underlying resources—servers, storage and network—was hidden from the users, and with IaaS providing flexibility to provision unlimited compute, storage and network resources on-demand, Chandrasekaran said.

Serverless: To Use a Server or Not? ‘Tis Not the Question

Serverless computing is a developer’s dream not only because there is no longer a need to worry about where the code is going to run, but also because there is no need for direct access to the operating system to manage that code. The result: Developers can focus solely on coding—the very thing they do best!

That statement would be easier for some to understand if it were not for the utterly confounding term “serverless.” Obviously, anything requiring computing involves servers, so saying this process is serverless is simply nonsensical. While the term is unfortunate and bordering on meaningless, the concept is solidly real and more than a little familiar.

For all practical purposes, serverless is just another word for cloud but with a bit of a twist—pricing is based on the actual amount of resources consumed by an application, rather than on pre-purchased units of capacity.

Deploying Code with NoOps in a Serverless Environment

Additionally, the term “serverless code” can be used either in conjunction with code deployed in traditional styles such as microservices, e.g. loosely coupled/SOA. Or, code can be deployed in the form of full applications that can be written to require no provisioned servers.

In serverless environments, jobs are scheduled on-demand, meaning as data comes in and is available. It can be automated so that a job runs once data is received. This means that jobs run only when data exists and otherwise sit idle, where they can’t burn resources.

Economies of scale also completely change in serverless computing. That’s because serverless delivers the ability to put some intelligence behind when and where jobs run, so that they can be spun up and spun down as quickly and economically as possible.

Bottom Line

Opting for NoOps, meaning working in a serverless environment, is really a choice to be more intelligent about how resources—hardware, software and people—are being utilized. It is about cutting resource waste and associated costs, while enabling talent to focus on writing innovative code.

No job will sit there burning resources and waiting for the data to come in. Rather, the job runs on demand, as you need it, in milliseconds and without distracting you from other tasks.

“NoOps still requires connectivity so beef up your connectivity to your cloud providers, if you haven’t already. And you’ll eventually have to troubleshoot slow serverless functions as a ‘network problem,’” said Andrew Lerner, an analyst at Gartner in his post.

To gain even more advantages in serverless computing, and perhaps to make up for time lost in network troubleshooting, no matter how small, look for and use reusable code everywhere you can. Drag-and-drop interfaces that enable fast use of reusable code frees developers further, so they can shorten both the development and testing cycles. Time economy is important in modern day continuous release cycles. A NoOps and reusable code strategy can dramatically improve your time and resource economies of scale.

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