Artificial intelligence is rewriting the book on IT operations
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There is high complexity in adopting new hybrid and virtualized technologies, becoming more agile, efficient and responsive. In this article, Bishnu Nayak will give you some insight into IT modernization and legacy transformation, the challenges that come with it and the value of AI.
Businesses need to introduce new applications and adopt new hybrid and virtualized technologies to become more agile, efficient, and responsive. And I had a first-hand experience in how complex that can be.
In my previous job as an executive architect at AT&T, I was spearheading the IT modernization and legacy transformation program. During the migration from legacy to virtualization, we had to assemble a big, cross-functional team to manually extract significant amounts of data from various systems to understand existing applications’ footprints and the dependencies across the infrastructure stack to determine business impact, plan for migration, and ensure that the performance of mission-critical applications wouldn’t be impacted post-migration.
The IT infrastructure team had an equally tough task on their hands: workload allocation and placement and making sure there were adequate data points and visibility that would help them properly manage the multi-tenant virtualized environment. We successfully migrated a massive number of business applications from legacy to virtualization on VMWare technologies, but it took a huge number of man-hours as we were lacking a platform that could automate the planning, execution, and validation activities.
Why was it so complex?
Modernization projects are employing cloud-based solutions, microservices architectures, virtualization and containers. But they are creating challenges of their own. In the past, each application lived on its own dedicated server. So ensuring the desired performance level was relatively simple.
In today’s highly distributed world, however, that’s simply no longer the case. Here’s why. Some business applications today live in public clouds. And enterprises tend to have no, or very limited, visibility into those clouds. Other businesses take advantage of more distributed hybrid cloud models.
Applications run on virtual machines, rather than physical, fixed servers. So that adds another level of complexity. As if that wasn’t enough, containers often exist alongside, or within, VMs. And the use of containers – and number of containers themselves – is quickly proliferating.
Gartner predicts that by 2020, more than 50 percent of global organizations will be running containerized applications in production, up from less than 20 percent today. Containers move around a lot. And they appear and disappear in the blink of an eye. So that multiplies the number of moving pieces exponentially.
Indeed, millions of data points are now flowing to the IT operations team in real time. This data deluge will only accelerate as the adoption of containers, microservices, and virtualization grows. In the last year, enterprises collected 88 percent more data than the prior year. Containers alone generate 18 times more data than traditional IT environments.
All that makes for a very dynamic – and complex – environment. Because this environment is very different than what came before, legacy tools built for the legacy environment no longer apply. So organizations need new solutions that can address the dynamic nature of today’s applications and networks. These tools must collect and correlate information about the application itself and about the underlying infrastructure in near real-time. They need Artificial Intelligence solutions to modernize IT Operations (AIOps).
Gartner recognizes AIOps as a strategic segment:
Artificial intelligence for IT operations (AIOps) platforms are software systems that combine big data and AI or machine learning functionality to enhance and partially replace a broad range of IT operations processes and tasks, including availability and performance monitoring, event correlation and analysis, IT service management, and automation.
Gartner – “Market Guide for AIOps Platforms”
AIOps solutions provide the correlation and machine learning capabilities across millions of data points in near real-time, enabling IT Operations to accelerate the adoption of hybrid and virtualized environments.