With the aggressive onset of digital transformation, global organizations are finding themselves with an increasingly complex set of data to manage and process. This translates to organizations spending a huge amount of time, money and manual effort on processing such large volumes of data.
AIOps mitigates the risk of operational fatigue and maintenance issues, reducing metrics like the Mean Time to Detect and the Mean Time to Repair by about half.
IT operations (ITOps) is now at the sharp end of this transformation, where IT teams have to wade through a sea of complex datasets to drive and sustain their business. However, due to the dynamic nature of business applications, distributed architecture, and services, there has been a visible increase in data loads over the last few years. Having said that, there should be a way for ITOps teams to keep up with business trends, demands and aggressive digitization of IT infrastructure.
The Paradigm Shift: Artificial Intelligence for IT Operations (AIOps)
Coined by Gartner, AIOps platforms use smart, self-learning algorithms backed by machine learning (ML) to automate mundane IT tasks. Not only that, but they also identify and preempt any possible incidents via behavioral and historical data analysis. AIOps also leverages big data analytics for cognitive analysis of data. In other words, it helps derive meaningful relationships from data for intelligible and comprehensive processing.
This integration with AI means ITOps teams are capable of real-time data correlation, continuous cause, and effect analysis, normalizing multi-dimensional data, prioritizing incidents based on severity, and building predefined response plans to mitigate future events. This ability to derive actionable insights from raw data with zero false positives can help build a responsive ITOps infrastructure.
Business Benefits of AIOps
The advent of AIOps platforms brings with it four important business benefits: cohesive agility, efficient data processing, faster Digital Transformation, and better decision-making.
It goes without saying that data is scattered across business verticals; AIOps helps build a cohesive connection between these verticals through algorithms based on ML while staying agile. Accumulating and processing this scattered data requires almost zero manual effort, as automated algorithms will do their due diligence. In other words, AIOps establishes meaningful connections from siloed data to deliver intelligent and actionable business insights. This way, business teams can always work at their own pace, while staying connected with each other.
Efficient Data Processing
The need for AIOps stems from the very fact that it’s extremely daunting for humans to process large volumes of data. However, AIOps, owing to its smart algorithms powered by ML and big data, can masterfully derive cognitive insights from raw data sets.
AIOps mitigates the risk of operational fatigue and maintenance issues, reducing metrics like the Mean Time to Detect and the Mean Time to Repair by about half. This intrinsic capability to process data at lightning speed will certainly pave the way for automating mundane and repetitive tasks, saving ITOps teams a considerable amount of time and effort.
Faster Digital Transformation
If Digital Transformation is all about innovation through new technologies, then AIOps complements that change. Courtesy of AIOps, advanced algorithms aid in detecting and, more impressively, reacting to events in real time, providing organizations with greater control over their business applications and IT infrastructure. ITOps teams can bid goodbye to those late night emergency calls because AIOps has got IT covered.
Data-driven Business Decisions
AIOps leverages advanced algorithms that employ ML techniques, such as pattern matching, predictive analysis, historical data analysis, and causal analysis. As a result, AIOps solutions deliver purely data-driven automated responses to all incidents, with zero false positives. This not only helps eliminate human error and data noise but also builds a strong base for preemptive and responsive IT infrastructure. From a business point of view, this strategy yields a surplus ROI with minimal effort.
Embrace the Change
Data has become the lifeline of ITOps. The complexity of IT infrastructure data, however, is increasing along with its significance, while the human capacity to comprehend this data remains the same. On the bright side, AIOps helps build a scalable ITOps strategy to foresee and preempt any possible issues in the future. An intuitively responsive IT infrastructure puts enterprises at the forefront of a tech revolution, and AIOps definitely aids in this transformation.
From providing real-time insight about potential security incidents to using predictive analysis to offer preemptive solutions to users’ problems and providing conversational assistance for efficient management of help desk requests, AI continues to prove its worth in ITOps.