When the term AIOps first came into vogue, it stood for Algorithmic IT Operations. In just a couple of short years, the market has moved on considerably, and it’s now widely accepted to stand for Artificial Intelligence for IT Operations. The underlying core idea is similar; using big data and machine learning to enhance and even replace IT operation processes such as performance monitoring and analytics.
This change is being watched closely by industry experts Gartner, who recently published their Market Guide for AIOps Platforms, which features Correlsense amongst their representative vendors in the field, providing 8 out of the 11 capabilities which were listed. In their report, Gartner estimate that “by 2022, 40% of all large enterprises will combine big data and machine learning functionalities” in areas such as monitoring, service desk and automation. This is a dramatic rise from only 5% today.
So how can you get in on the ground floor? And what benefits are there for you in making AIOps part of your digital transformation strategy?
Improve Data Analytics
The Gartner report has looked at how AIOps can take data analysis to the next level. The right tools can help you capture, ingest and access real time information with streaming data, wherever it is coming from. As the leading Application Performance Management (APM) system, Correlsense was included in the report as one of only a handful of companies who can automatically provide not just pattern discovery, but also anomaly detection and causal analysis of this data as it is coming in.
This is a new era of data analytics, more powerful and seamless than anything which has come previously. With one glance at your dashboard, you can identify bottlenecks and solve performance issues, as well as find real-time problems and isolate any potential problems, even before they affect the end user. You can look at application or transaction behavioural changes and understand how usage is split between infrastructure and shared services.
These analytics tools are becoming more than just helpful, they are moving towards being essential to keep your head above water. SDTimes reports that “Without these insights into the application — from code creation to user experience and closing the feedback loop — companies will not be able to keep up with the market’s pace, nor will they be able to go to that next level of agility.”
Understand Customer Intent
In their market guide, Gartner stress that the more data types which is being analysed, the stronger the analytics provided will be. Modern IT systems are complex, and require a multi-perspective approach. But this sounds overwhelming for enterprises who are trying to hear the messages beneath the noise. By grouping together alerts and notifications with the help of semantics, language, trend and topic, alerts are helpful rather than obtrusive, and give an accurate understanding of the real time issues which need resolution.
A data driven approach to monitoring also gives your business a better understanding of what your end user is really saying. Not only can you use the patterns you pick up from multiple sources to get actionable analytics for success, but you can also listen to the questions your users are asking, and watch the real-time user experience they are having, even across multiple applications or channels. As you’re tracing transactions across the entire IT stack, you can see exactly where and how problems are arising, improving customer experience from the ground up, at code level and beyond.
Notifications and alerts are immediate, so problems are already being fixed before you get calls from your customers, and you can even set up reports which can be shared with the team members who need to know. Simply put, you’re talking significantly shortening the time it takes to detect problems, and to fix them.
Enhance Visibility, at a Granular Level
But that’s not all. There are internal improvements to be gained as well. Historically speaking, businesses often function within silos which make communication and collaboration difficult. AIOps like Correlsense aim to combat this by using machine learning to view all applications side by side, tearing down those silos and providing true visibility, what we call granular visibility. This can be used to identify anything from the minutiae of internal IT costs, to filling specific information gaps.
The bottom line is moving from an emphasis on legacy first to digital first. Instead of looking at what you’ve always done, using APM and AIOps to move from what Gartner call “backward reporting to forward-looking predictive analytics, combined with data-led experimentation.” We couldn’t agree more that “digital business success requires starting with a digital information and technology mindset.”
If you’re looking for a way to enhance your businesses digital transformation, AIOps is a great place to start. AIOps can use analytics and artificial intelligence to give you the edge against your competition, regardless of the industry you’re in. Providing you superior visibility, powerful analytics, and an insight into the real user experience, this may well be the future of Application Performance Management.
About the author: Daniela Morein Bar joined Correlsense as the Director of Marketing in March 2015. She has over 15 years’ of international experience in marketing, advertising, branding, strategy development, social media, and digital marketing.