Data is the buzz word these days. In IT domain, enterprises are often venturing and experimenting to find best practices for their business. Crunching more numbers for data driven insights means necessity for an environment where both operations and software development teams work in sync to boost efficiency and overall productivity. Most of the leading companies have a cloud partner where they build software-based services that foster innovation and engagement. However, the problem with cloud is that it brings challenges in terms of scalability, complexity, and frequency of change. DevOps is an increasingly popular approach to software development that integrates the previously separate roles of IT operations and software management. And to augment the offerings of DevOps, we have artificial intelligence tools that can be used to automate and improve IT operations: AIOps. Analytics Insight forecasts that the global AIOps Market is expected to grow at a CAGR of 43.7% during the period 2020 to 2025. The AIOps Market is estimated to be worth US$ 3127.44 million in 2025, rising from US$ 510.12 million in 2019.
AIOps merges artificial intelligence algorithms and human intervention to provide full visibility into the performance of the IT systems. Generally, DevOps emphasizes on a change in culture and process. AI powered DevOps in IT ecosystem can ensure greater speed, better accuracy, consistency, reliability, and multiplies the number of deliveries made. It minimizes the chances of manual errors and failure by expediting automated testing procedures and managing other tasks across the cross-project requirements. However, in scenarios where IT team needs to derive value from data aggregated from sources like cloud infrastructures, third party systems, IoT devices, and mobile systems, relying only on DevOps based automation is not possible. This is where AIOps comes to rescue. It not only improves automation but also offers IT operations teams a real-time understanding of issues affecting the availability or performance of their systems. AIOps can analyze data about the current IT processes in the DevOps workflow and extracts significant events related to slow-downs or outages, using big data analytics and machine learning while also providing actionable and contextual intelligence.
As per a recent Harvard Business Review article, a recent global survey of CIOs from large enterprises highlights why AIOps have become critical part for managing modern IT environments:
In the same survey, 70% of CIOs believe that automation could have saved their teams time spent on doing manual tasks, as compared to only 19% of all repeatable IT processes which have been actually automated.
By leveraging AIOps to remove noise and distractions, it can enable IT personnel to focus on essential issues rather than distractions from irrelevant alerts. It will also free them by analyzing data to discover and resolve issues automatically along with preventing outages, maintaining uptime and attaining continuous service assurance. It also helps manage scattered, heterogeneous, and dynamic IT environments.
Apart from these, AIOps also allows remote collaboration and simplifies incident management, thus, helping remote Ops teams (NetOps, SecOps, DevOps, BizOps and ITOps) communicate and collaborate effectively in virtual NOCs (network operations centers). It also eliminates silos and provides a holistic, contextualized vision across the entire IT environment. Some of the AIOps vendor offer full-stack observability into the digital experience (mobile, web, crash, journeys, funnel), app-to-network monitoring as well as support for cloud-native architectures.
In coming years, AIOps features is predicted to extend into the realm of cybersecurity. When this happens one can expect AIOps to bridge the gap between IT operations and security operations teams too.
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