How AI can deliver eye-opening insights for IT
No matter what your newsfeed may be, it’s likely peppered with articles about the wonders of artificial intelligence. And rightly so. But even as we remember 2023 as the year when generative AI went ballistic, AI and its ML (machine learning) sidekick have been quietly evolving over several years to yield eye-opening insights and problem-solving productivity for IT organizations.
It’s called AIOps, Artificial Intelligence for IT Operations: next-generation IT management software.
The pairing of AI/ML with IT telemetry and other monitoring and management functions, known as AIOps, has a projected market size of about $2.1 billion in 2025 with a compound annual growth rate of around 19% according to recent research from Gartner®1. And putting it bluntly, Gartner® says “There is no future of IT operations that does not include AIOps.”1
Just as GenAI-powered tools like ChatGPT promise to accelerate insights and processes in increasingly complex business environments, AIOps does the same for IT as infrastructure and application architecture scales and gets more complex across core, edge, co-location, and multicloud environments.
AIOps yields measurable results
In my experience working with IT decision-makers, many say they expect AIOps to increase IT/DevOps efficiency by reducing cycle times, improving resource utilization, and ultimately helping them increase market penetration and make more money.
Our customer surveys2 show that AIOps help resolve IT issues 2 to 10 times faster and save operations specialists the equivalent of one day per week on average. As one such customer, Cloud Operations Manager for leading SaaS ERP service provider Plex System, Darrel Schueneman said, AIOps “helps improve productivity, and that frees us to spend more time on performance tuning and on R&D for new products.”
That just about covers all the bases.
What’s inside AIOps
AIOps’ software engine is all about accelerating IT/DevOps. Faster time to insights yields faster time to resolution, often proactively, so organizations can minimize or outright avoid IT and business impact.
A key attribute of AIOps is observability, an apt term that’s been gaining ground in recent years. Traditional IT monitoring software tells you what is happening via metrics, logs, traces, alerts, etc. Observability applies AI/ML and related algorithms to tell you what’s happening, what’s unusual, why, and what to do about it. Observability can go further to tell you what will happen and what to do about it ahead of time.
Rather than overwhelming IT with reems of telemetry data and endless rows of key performance indicators, charts, and graphs, AIOps intelligence acts on telemetry to show you behavior that’s within as well as outside expected ranges, visually correlates graphical data for making root cause conclusions, rolls up KPIs into discernable scores that indicate impact and provides recommendations.
3 primary use cases
AIOps addresses three areas of concern: IT health, cybersecurity, and sustainability.
Health scores for systems (servers, storage, data protection, hyper-converged appliances, and network) and cloud services that AIOps provides are a giant step beyond traditional monitoring. “Good,” “fair” and “poor” scores take into account the weighted value and impact of each system’s component, configuration, capacity, performance, and data protection status. You’re not trolling data for insights; instead, they are more or less packaged for you. AI/ML derives insights, such as capacity is reaching full, performance will top out soon, and latency anomalies that are impacting your systems, virtual machines, and, therefore, applications. AIOps intelligence points you to the cause and spells out a recommendation.
Cybersecurity risk level indicators – normal, low, medium, and high – which AIOps derives are giant steps ahead of manual methods of checking systems for security lapses and vulnerabilities. For example, IT systems can have dozens of security configurations unlocked daily for legitimate system administration. But are they locked up correctly after the work is done? A single server can have up to 31 cybersecurity settings, and it can take six minutes to manually inspect just half of them. Nobody has the time to do that for every server every day. AIOps automates the investigation and recommends how to securely reconfigure the systems – and it extends its intelligence to uncover other kinds of vulnerabilities.
Sustainability is also a growing IT concern – from energy cost and emission standpoints. AIOps absorbs power consumption telemetry and calculates energy usage and carbon footprint at the organization, system, and workload levels. By applying AI /ML, it forecasts energy and emissions so you can be proactive about meeting your sustainability goals. At a glance, you’ll see which systems need to be replaced with more energy-efficient systems. Combining these analytics with AIOps health analytics, cybersecurity assessments, and system metadata, gives you insights to make the best sustainability decisions about workload consolidation to reduce your IT footprint and lower emissions and energy costs.
Bridging the gap across IT organizations
Since the early days of ITIL (Information Technology Infrastructure Library) best practices, we’ve recognized that IT is about people, processes, and technology. AIOps’ broad scope of intelligence and high-level application programming interfaces address all three.
By covering infrastructure health, cybersecurity, and sustainability in one user interface, AIOps provides a common observability platform – one source of truth – for IT system administrators, virtualization administrators, site recovery engineers, sustainability engineers, cybersecurity specialists, and DevOps teams. By pushing its notifications to popular messaging, ticketing, and incident management applications, it engages IT service management processes with greater speed and efficiency. And by integrating its insights with infrastructure-as-code tools, it automates actions to remediate issues faster.
To see AIOps in action and learn more about how it can empower your future, visit www.dell.com/cloudiq.
1Gartner, “Market Guide for AIOps Platforms,” Pankaj Prasad, Padraig Byrne, and Gregg Siegfried, May 30, 2022
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
2Dell Technologies survey of CloudIQ users, 2021.
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About the Author
Carol Wilder leads the cross-platform software/solutions product management team for Dell’s Integrated Systems (IT infrastructure) Group. Most recently, she headed the product team at Puppet, the infrastructure automation software company, and previously held a variety of roles in strategy, engineering, and marketing at Intel and Amazon. Her career began in the semiconductor test industry. She devotes time to Chief, a network for supporting women executive leaders, and to Rose Haven, Portland, Oregon’s shelter and community center for women, children, and gender-diverse people.
