Explaining what AIOps is and why it matters to developers
|Richard Harris in DevOps Monday, March 13, 2017|
Algorithmic Intelligence Operations (AIOps) is new category defined by Gartner research that is an evolution of ITOA.
It seems we have reached a point where data science and algorithms are being successfully applied to automate traditionally manual tasks and processes in IT Operations. Now, algorithmics are incorporated into tools that allow organizations to streamline operations even further by liberating humans from time-consuming and error prone processes, such as defining and managing an endless sprawl of rules and filters in legacy IT Management systems.
The technologies introduced to the market over the past several years, utilizing data science and machine learning in response to the increasing complexities of enterprises undergoing digital transformations, have led to the birth of the term ‘AIOps’ (Algorithmic IT Operations).
ADM: What problems for IT does AIOps solve?
Tee: With the technological advancements of AIOps, what typically takes humans hours to accomplish can now be done in just seconds in an automated manner and with much better results. Traditional IT Ops teams manage high alert volumes, leading to major distractions and time spent doing mundane work instead of innovating. These problems are solved when IT teams start using AIOps to supplement operators as they sort through seas of alerts and noise. The benefits of AIOps adoption are being recognized by leading Fortune 500 enterprises, who are rapidly on-boarding these technologies to improve their customers’ digital experience across industries - including banking, entertainment, transportation, retail and even government.
ADM: Give us a real world example of AIOps in use?
Tee: HCL Technologies, for example, is one of the premiere global providers of managed services, and is known for transformational outsourcing, focusing on innovation and adding value to large enterprises. To assure the best service for their clients, HCL uses Moogsoft’s AIOps technology to help their clients maintain proactive, real-time insight across their entire infrastructure; and collaborative, team-based workflows to quickly and efficiently remediate issues as they arise.
Since HCL started recommending AIOps to their customers, they have told us that by ingesting data from over 30 different IT tools, Moogsoft AIOps effectively correlates and contextualizes large volumes of information. It also helps HCL achieve a 62 percent reduction in trouble ticket generation and a 33 percent reduction in MTTR (Mean Time to Remediate). This massively impacts efficiency and cost savings, never mind the amount of groundbreaking, innovative projects these teams can achieve now that they have been freed up from the misery of traditional IT operations.
ADM: How does it make things better in an IT environment for DevOps administrators?
Tee: Modern IT environments are incredibly (and increasingly) complex and ever-changing, leading to large amounts of time and resources devoted to monitoring, troubleshooting and course correcting. It’s a reactive position for most companies, but when teams use AIOps technology they can leverage change-tolerant algorithms and access indexed information. This allows them to spend more time focused on proactive, meaningful work rather than fixing the same problems repeatedly or spending time managing rules and filters.
ADM: How can AIOps help developers?
Tee: With the widespread adoption of DevOps in the enterprise, we’ve seen a decentralization of the Operations function and a distribution of the responsibility to development teams. DevOps is all about automation and being agile so that the business can move faster. Over the years, companies have spent billions automating server provisioning, release management and the configuration of monitoring tools. With AIOps we see automation within the troubleshooting of applications using algorithms and data science. DevOps teams are finding that AIOps technology is the key to managing the complexity, scale and change of the applications they not only develop, but now support.
ADM: Tell us about Moogsoft and what you offer?
Tee: Moogsoft was founded by myself, Phil Tee, and my co-founder, Mike Silvey, in 2011 as we were frustrated by a lack of innovation in the space. This technology was born out of research being conducted at the University of Sussex around data science, machine learning, natural language processing and other academic subjects. We saw early on how this science could be applied to IT operations management and to improve service assurance, so we developed a product out of it. Since the beginning, our mission has been to help modern operations - whether that be IT Operations or DevOps teams - become smarter, faster and more effective, by providing technological supplementation that automates mundane tasks, enables scalability and frees up humans to do what they do best - ideate, create and innovate.
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