Data has always been the fuel behind successful businesses. However, with more and more data exploding in modern times, traditional tools and processes are failing to store, analyze and manage them to gain meaningful insights. Not only has this caused data chaos across the enterprise, but it has also put tremendous pressure on the IT teams, to provide speed, security and reliability, within the complex, manual and siloed legacy solutions, paving the way for AIOps.
What is AIOps?
Though a relatively new term, AIOps is garnering attention from across industries, especially in the last couple of years. As the name suggests, AIOps is the application of Artificial Intelligence (AI) in Information Technology (IT) operations. Largely used to automate common IT issues, enterprises are highly dependent on AIOps for a successful digital transformation, as it empowers IT to operate at the speed of today’s business demands.
AIOps platforms are defined as software systems, which combine big data with AI functionalities such as Machine Learning to scale and improve IT operations. It is a collaborative platform wherein continuous integration and deployment of core IT functions take place. Transforming operations from a siloed approach to a more dynamic approach, AIOps is quite critical for the digital journey of an enterprise. It is a new step taken towards changing the traditional IT operations and performance monitoring to let the businesses focus on more innovative and strategic decisions within the digital enterprise. In fact, a recent research predicted that by 2022, 40% of all large enterprises will combine big data and machine learning functionalities to support and partially replace monitoring, service desk and automation processes. This clearly makes AIOps the next big thing in an enterprise’s digital transformational journey.
How does AIOps work?
The key function of the AIOps platform is to enhance the traditional IT tools and process the different kinds of data, to meet today’s industry demands. Unlike traditional businesses, which worked in siloes, today’s enterprises focus on collaborative and interoperability to reduce costs, while improving productivity. To achieve this, AIOps applies cutting edge AI and ML capabilities such as predictive analytics, prediction and forecasting, event management and analytics, clustering, adaptive and statistical thresholding, anomaly detection, root cause determination to make sense of the humungous data and empowers enterprises to get value, which is otherwise not possible with human analysis alone.
AIOps as future of IT Operations
With time, businesses also need to change the way they operate. AIOps can help accelerate this change while keeping the costs under control, by utilizing its capabilities. It enables collaboration of multiple data sources and IT resources and also helps the IT teams with the right tools to achieve this. As it aligns the data resources and optimizes processes, there’s a great improvement seen in the quality of data that is fed into the machine learning systems.
According to Gartner, the use of AIOps by large enterprises is set to increase from 5% in 2018 to 30% in 2023, making AIOps the next big thing in IT management and AI-led correlation. A successful AIOps implementation can forge a series of change in IT operations leading to excellence in overall business performance. Although still quite early in its deployment, the AIOps platform is slated to play a pivotal role in enabling the enterprises to overcome the current operational challenges and accelerate towards a quick and successful digital transformation by converging AI and IT ops changing the face of IT management.
