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  • Writer's pictureAppCentrix

Seven AI-Ops considerations

Updated: Jul 14, 2020

Gartner predicts that large enterprise exclusive use of AIOps* and digital experience monitoring tools to monitor applications and infrastructure will rise from 5% in 2018 to 30% in 2023.

The long-term impact of AIOps on IT operations will be transformative, says Gartner in a recent paper. “IT operations are challenged by the rapid growth in data volumes generated by IT infrastructure and applications that must be captured, analyzed, and acted on,” says Padraig Byrne, Senior Director Analyst at Gartner.

“Coupled with the reality that IT operations teams often work in disconnected silos, this makes it challenging to ensure that the most urgent incident at any given time is being addressed.”

IT operations can use artificial intelligence (AI) to monitor data and reduce outage times.

According to Byrne, the long-term impact of AIOps on IT operations will be transformative. He recommends seven considerations for including AIOps:

  1. Don’t wait. Become familiar with AI and ML vocabulary and capabilities today, keeping current with vendors or service providers who are already working in this space.

  2. Choose initial test cases wisely. Transformation initiatives benefit from starting small, so look for areas which can be good test cases and a service provider or solution with proven returns.

  3. Develop and demonstrate your proficiency. Demystify AIOps for your colleagues and leadership by demonstrating simple techniques, using small wins and examples from the market to prove your case.

  4. Experiment freely. A great deal of open-source and low-cost ML software is available to enable you to evaluate AIOps and data science applications and uses. Go the extra mile and set up demo’s and evaluations to evaluate against your full business and IT strategy.

  5. Look beyond IT. Leverage data and analytics resources that may already be present in your organization. As with all IT Ops, dovetailing with overall business strategy and across silo’s is essential.

  6. Standardize where possible, modernize where practical. Prepare your infrastructure by gaining a clear understanding of what you have, its capabilities, and where legacy states may need to be improved.

  7. Visualize full adoption. Ensure that AIOps is part of a full roadmap, and you are empowered to implement through a disciplined approach, including AIOps as maturity evolves.

By using AI to provide IT operations with actionable insights, leading companies are leveraging the most powerful trend of the decade – using real-time data to inform meaningful business decision-making to pivot their organizations during uncertain times.

SmartICT uses AIOps to support and serve our customers during these challenging times. Let us know how we can help support your mission. These seemingly small interventions can make a massive impact on the higher demand that is being placed on IT infrastructure, collaboration tools, networks.

For more on how AppCentrix SmartICT gives SMARTER VISIBILITY FOR SMARTER SECURITY AND PERFORMANCE, visit or have one of our skilled consultants contact you by responding to this email.

*What is AIOps?

Put simply, AIOps is the application of machine learning (ML) and data science to IT operations problems. AIOps platforms combine big data and ML functionality to enhance and partially replace all primary IT operations functions, including availability and performance monitoring, event correlation and analysis, and IT service management and automation. AIOps platforms consume and analyze the ever-increasing volume, variety and velocity of data generated by IT and present it in a useful way.

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