What is AIOps? A high-level overview
Big data, artificial intelligence (AI), and other technologies present a modernisation challenge for businesses — and the various departments therein. The IT department is no different. But, just as technology has presented this challenge, so too is it helping to address it.
For your IT operations team, the need to leverage artificial intelligence technologies (and those adjacent to them) has resulted in an emergent field that’s come to be known as AIOps.
But what exactly is AIOps? Here’s a high-level overview.
What is AIOps?
AIOps was originally shorthand for ‘Algorithmic IT Operations’. Now, it stands for Artificial Intelligence for IT Operations. It’s an emergent field, meaning its definition is still widespread.
A good place to start, then, is with the origins of the term. The term AIOps was coined by Gartner, who defined it as follows:
“AIOps platforms utilize big data, modern machine learning and other advanced analytics technologies to directly and indirectly enhance IT operations (monitoring, automation and service desk) functions with proactive, personal and dynamic insight. AIOps platforms enable the concurrent use of multiple data sources, data collection methods, analytical (real-time and deep) technologies, and presentation technologies.”
Put simply, AIOps is the use of artificial intelligence technologies — such as machine learning — to boost your IT operations.
Core elements of AIOps
Having defined AIOps, it’s also useful to look at its core elements — that is, the technology and tasks that it encompasses.
Huge, complex data sets full of handy information waiting to be leveraged.
A branch of artificial intelligence that allows machines to learn from data and improve over time.
- Advanced analytics
An umbrella term for numerous analytical methods aimed at making the most of data. Advanced analytics enables data-based predictions and inferences that provide extra insight.
- Performance monitoring and proactive responses
AIOps allows IT teams to proactively manage performance challenges, addressing issues before they become system-wide problems.
- Event correlation and analysis
A huge part of AIOps is analysis. It analyses data for relationships and patterns. This analysis can also aid predictions, identify issues, and trigger actions.
AIOps isn’t just about analysing the data, applications and processes involved in your IT operations. You can then use that analysis to define triggers and automate responses to a given input. For instance, auto alerts when an issue gets detected.
Why adopt it?
So, why is AIOps worth adopting? What are the benefits?
- Enable better decision making
With real-time and deep analytics, the IT operation team can make better use of data, without your team having to sift through the mountains of information collected by the business.
- Productivity boost
Automation handles routine tasks, AI analyses and alerts you to issues and opportunities, and IT teams have more time to focus on the high-value and unpredictable issues. The result is a supported IT team, and more mental energy to push your productivity.
- Lower operational costs
The increased efficiency and productivity thanks to AI support, along with replacing some legacy applications used by the IT operations team, can result in lower costs.
- Discover unknown issues
With advanced analytics, AIOps can help teams find unknown issues within their systems. This will help IT teams improve their processes — and proactively solve problems before they become catastrophic.
To summarize, AIOps is where you augment your IT operations with artificial intelligence technology. It’s a new field, and one that’s set to grow and improve alongside AI functionality.