Digital Transformation Process: The Evolving Role of IT

There has never been a better time to be an IT professional. IT professionals must handle multiple digital transformation projects and the complexities of artificial intelligence, cloud strategy, and more. Modern IT professionals must also deal with more self-healing technology and autonomy. 

So who is in charge of the digital transformation?

IT in the Traditional Sense

In the past, IT operations managers used several dashboards to monitor issues like performance and availability. Many events would occur from various unrelated dashboards as they finished their last problem.

 Each issue required several hours, if not days, of work. There were no warning indicators that things were about to go awry.

This Is Where DevOps Comes In

You can accelerate software development by eliminating bottlenecks between Dev (the programmers) and Ops teams through DevOps (the fixers). Goldratt Manufacturing revolutionized manufacturing in the 1990s using a similar method. 

Both cases aim to bridge the gap between development and operations.

This year, cloud migrations increased, open-source technology multiplied, microservices took root, and DevOps took off. Streamlining the DevOps process has gotten increasingly difficult as the number of tools, applications, and systems has grown. 

It is no longer the responsibility of the operations teams to fix problems that arise after a deployment has taken place; instead, this responsibility is shared by everyone.

The Vision of NoOps

NoOps is a method of governance in which developers (or, more generally, DevOps practitioners) are not responsible for maintaining ongoing operational duties. Instead, the operations are automated to reduce the possibility of human error, freeing the ITOps personnel to focus on their primary tasks: technology-related duties.

NoOps means that everything one can automate has already been automated, thus freeing ITOps personnel to spend their time on technology-related duties or to work with DevOps to improve and enhance the automation.

DevOps’ Value in  Size and Complexity.

Developers with DevOps projects can no longer be treated as Ops deployment targets. The infrastructure has been replaced by code, and the code itself is now the infrastructure itself. 

Because testing is done in the cloud, resources are always available and may be reclaimed when they are no longer required. This implies that you can do your work faster and more efficiently than someone else.

What does it take to get a piece of code to work? Many people are involved in setting up and maintaining platforms, some of whom write code while others don’t. 

They support the platform by learning how it works and doing tests to ensure that everything is running as expected.

In Predictive AIOps, the Focus Is on Transformation

Artificial intelligence for IT operations, called AIOps, is a concept created by Gartner in 2017.

Using artificial intelligence to manage data and information in IT workflows (AI), AIOps refers to a system that can proactively monitor and diagnose IT operations.

Well-known data, machine learning (ML), and pattern recognition algorithms are used to do this. 

The IT department becomes more efficient by not waiting for users or applications to report a problem.

AIOps can find an issue before it grows more severe without asking the user to find the problem. With a broader model, an IT Ops staff can effectively delegate digital transformation initiatives across the firm.

An AIOps setup with predictive capabilities would allow IT Ops to concentrate on guiding digital transformation across the board. We’ve seen trends in this area in the past. According to ServiceNow’s study team, IT Ops should be focusing on the following three areas:

  • Incorporating data visualization to show the business impact
  • Ensuring that alerts are being handled without procedures needing to be manually adjusted
  • Ensuring that services stick to their SLAs and incident response loops close properly after issues are resolved. 
  • Predictive AIOps are the key to future IT operations, regardless of your selected approach.

Conclusion

It combines artificial intelligence, information technology, and IT operations. “Preventative maintenance” is a term commonly used to describe technologies that can identify problems in an IT system before they occur and help IT operations. 

The IT infrastructure is monitored and managed using artificial intelligence, which improves the accuracy of choices and problem response.

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