The application of artificial intelligence (AI) is profoundly altering our understanding of DevOps. Most importantly, it is providing the latest form of DevOps that acknowledges the need for intelligently designed applications supported by robust defence (DevSecOps). By now, most organizations understand that DevOps is a substantial discipline they must adopt to ensure consistent levels of productivity, efficiency and service delivery, all of which hold weight in these times of heightened uncertainty. AI-powered DevOps allows businesses to provide new value to their consumers rapidly, enabling them to mature and transform their digital images. Without DevOps, it is impossible to keep up with the competition and respond to industry events and consumer requests promptly.

Supervising and managing a DevOps environment can be complex. The proliferation of data has made it challenging for DevOps teams to effectively absorb and implement information to evaluate and tackle customer issues. Imagine a team navigating through data in exabytes to search for important events that triggered an event; they would end up investing hundreds of hours in identifying the issue. A lot of such critical issues can be resolved with artificial intelligence (AI)-powered technologies. Organizations can transform their DevOps environment by deploying AI systems.

With data being added every minute, it is impossible to manage all of them without the help of technology. Especially, monitoring a DevOps environment involves a high degree of complexity. The exploding amount of data is giving a hard time to DevOps teams to effectively absorb and apply information to address and resolve customer issues. However, when artificial intelligence (AI) and DevOps work together, they can boost their productivity by saving a lot of time. DevOps is a set of practices that works to automate and integrate the processes between software development and IT teams, so they can build, test, and release software faster and more reliably.

The telecom giant CenturyLink created a federated program to scale automation efforts, where one dedicated team curated standards and best practices that were then rolled out across the company. CenturyLink -- a facilities-based communications company with 40,000 full-time employees, based out of Monroe, La. -- wanted to achieve automation at scale and blend the best characteristics of application development, scripting, and robotic process automation (RPA) tooling, said Troy Ferrence, senior manager of automation solutions architecture at CenturyLink. For the past several years, Ferrence's team has focused on scripting and application development, but its efforts accelerated when CenturyLink introduced RPA software that used the UiPath platform. CenturyLink expanded its work to more than 19 teams dedicated to this project, referred to as center of excellence teams, in the last year and developed over a thousand different automations. "We have a lot of legacy applications where we don't have any type of interface or availability for enhancement which are perfect candidates for RPA," Ferrence said.

Developers need to understand the intersectionality between DevOps technology and machine learning. Machine learning algorithms can significantly improve the effectiveness of DevOps applications. It is important to be aware of the different ways that machine learning can be applied to DevOps. Before you begin implementing DevOps practices, it is important to carefully define your objectives and recognize the biggest shortcoming of traditional DevOps environments. DevOps processes are invaluable for generating massive data sets for different applications. They can be useful for streamlining various methodologies and handling troubleshooting queries.

Rob Bollard, CIO at IP Australia, the government's intellectual property department, is proud to say that he heads up Australia's first fully digital service delivery agency. In just the space of four years, IP Australia has gone from receiving just 12% of its IP applications online – the rest coming through on paper – to now receiving 99.6% through digital channels. Not only his, but Bollard is overseeing the decommissioning of old systems, a move to the cloud, has implemented agile working, created a DevOps environment that focuses on continuous delivery, ensures systems are designed with the user in mind, and is even deploying AI technologies to improve experiences for employees and citizens. I got the chance to sit down with Bollard at Pega's annual user event in Las Vegas this week, as IP Australia has implemented the Pega platform as its case management system. Our vision is really to become a world-class IP office and to try to support the prosperity of Australians in the system.