The future of IT monitoring lies in AIOps

By Daniela Streng
There is one continuing variable that will always be dependable: IT infrastructures are becoming increasingly complicated...

Trends in tech innovation can be difficult to predict, but there is one continuing variable that will always be dependable: IT infrastructures are becoming increasingly complicated. Enterprise IT systems now rely upon a range of intertwined assets that have to work in perfect synergy –  infrastructure that lies across multiple clouds, on-premises, the connections in between, and Software-as-a-Service (SaaS) applications, only to name a few.

In a perfect world, these tangled systems would always work in harmony, each intricate piece performing its specified role in a manner that impacts varying layers of the system. However, this is seldom the case. It is up to IT teams to keep these labyrinthine mechanisms ticking, and thereby prevent outage and brownout events that could disrupt company operations. 

After all, when outage events do occur, the damage can be far-reaching. Not only does disruption to company operations inevitably waste time and money, but outage events are liable to make headlines in the media, resulting in irrevocable brand damage. Inconvenienced customers will also simply choose competitors if they are unable to properly engage with a company’s service or product.

The responsibility of IT monitoring and preventing outages falls upon beleaguered IT teams, who alone must navigate the ever-more complex enterprise IT environment and spot issues before they result in major problems. The task is one of monitoring and interpreting issues in the data, but the data produced by modern IT infrastructure is vast and teams are often undermanned.

AIOps to the rescue

Fortunately for IT teams – and the enterprises that depend on them – there is a natural solution to this issue: AIOps. True to its name, AIOps is the combination of artificial intelligence (AI) and IT operations. AIOps technology combines data science and machine learning (ML) to identify, troubleshoot and resolve issues developing in the IT ecosystem. Traditionally, AIOps involves automation and has the capacity to reduce manual work for stretched IT teams.

A key functionality of AIOps within complicated IT enterprise systems is its ability to process and interpret vast pools of data without manual input from IT teams. AIOps monitoring solutions can also remediate issues before they result in the problems that cause outages and brownouts.

Given the massive benefits of an AIOps approach to IT monitoring, the trend towards AI solutions is already becoming clear. Gartner, coiner of the term “AIOps,” predicts that large enterprise use of AIOps and digital experience monitoring tools used to monitor applications and IT infrastructures will increase to 30 percent by 2023. Gartner further predicts that the global AI-derived business value will reach nearly $3.9 trillion by 2022.

This is a change that will come to benefit overstretched enterprise IT teams. Instead of having to pore over the complicated IT environment, and the vast deluge of data it emits, teams can put their trust in AI-enhanced monitoring solutions. This will not only prevent the company from suffering an embarrassing outage event, but will leave IT teams with more time for innovation and improvement of the IT infrastructure.

By Daniela Streng, LogicMonitor VP & GM EMEA

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