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The digital transformation, changes and evolution of technology, new initiatives that are emerging in terms of customer experience and the rapid growth in the volumes of data generated, pose challenges to IT operations. Similarly, the need for real-time decision making has increased due to the large volumes of data and analysis.
These challenges make traditional information parameterization, monitoring, IT operations management, and tracking obsolete and inadequate, rendering the process of extracting value from data unusable.
IT operations need help to reduce the noise of daily operations, quickly identify and fix problems, automate repetitive tasks to increase efficiency, and focus on value-added activities. To do this, IT organizations need a new kind of technology to modernize their processes, and this is where AIOps technology that has been developed in recent years comes in.
Traditional IT management techniques have been deemed unable to cope with the digital transformation of the business. This digital transformation encompasses DevOps, the migration of enterprises to the cloud, an increase in the pace of innovation and implementation and the acquisition of new digital users (IoT, APIs, etc.) that organizations previously did not need to serve. All these new technologies and users are forcing traditional service and performance management strategies and tools to the point of total obsolescence. AIOps is the ITOps paradigm shift needed to solve these digital transformation problems.
Interest in and adoption of AIOps has increased exponentially in recent years as organizations have improved their innovations, tried to compete with disruptive businesses, and attempted to manage the speed, volume and variety of digital data.
In fact, according to the data, the market size for AIOps is estimated to be increasing by $300 million to $500 million per year, and its use will grow from 5% in 2018 to 30% in 2023, primarily because more and more organizations plan to invest in this technology.
AIOps stands for Artificial Intelligence to improve IT operations. Specifically, AIOps uses Big Data, data analysis and Machine Learning capabilities to do the following:
By replacing the use of multiple IT operations tools with a single, intelligent, automated tool such as AIOps, IT teams can respond more quickly and proactively to potential problems.
This technology solves problems that were beginning to emerge in the changing and complex IT landscape and meets user expectations for performance and availability disruptions. Most experts see AIOps as the future of IT operations management.
The main, and most obvious, benefit of AIOps technology is that it enables IT operations to identify, address and resolve problems, slowdowns and disruptions more quickly than would be possible manually or through the use of multiple IT operations tools. This results in a number of specific benefits:
Despite all the benefits that AIOps offers, the implementation of this type of tool is not perfect. As with any system that introduces significant changes to IT processes and transforms the responsibilities of team members, AIOps can appear to be a threat to workers. And this idea of job loss or reassignment can lead to organizational challenges that companies must address:
As Information Technology overcomes the barrier of what humans can do, IT tools must adapt. Organizations that adopt AIOps will see the potential challenges it must address as an opportunity to grow, evolve and innovate. In addition, they will see their business transformed, over the next five years, in the following way:
By combining Big Data, machine learning, data visualization and programmable process automation with IT operations management, AIOps adoption is the key indicator of the digital enterprise’s path.