Next Steps for ITOA - Part 3

APMdigest asked experts across the industry — including analysts, consultants and vendors — for their opinions on the next steps for ITOA. These next steps include where the experts believe ITOA is headed, as well as where they think it should be headed. Part 3 covers monitoring and user experience.

Start with Next Steps for ITOA - Part 1

Start with Next Steps for ITOA - Part 2

MONITORING INTEGRATES WITH ITOA

Advanced analytics and machine learning will become table stakes in monitoring tools. Initially this will create a flurry of unsubstantiated rebranding efforts by vendors eager to catch up, but these will eventually either acquire their way into ITOA or exit the market.
Trace3 Research 360 View Trend Report: IT Operations Monitoring & Analytics (ITOMA)

USER EXPERIENCE

As powerful as APM tools are, they have always been application- or infrastructure-centric and have therefore missed a very important piece of the puzzle: the actual users. I predict that IT departments, with the encouragement of corporate management, will not only begin to recognize the value of understanding user experience and behavior, but will take the lead in leveraging these analytics to improve the quality of service they deliver. They will begin integrating user analytics as a core capability within their toolset to see exactly what happens when users enter information and navigate through screens. These unique insights will help them improve problem resolution, system performance, process optimization, employee efficiency and more.
Brian Berns
CEO, Knoa Software

DIGITAL EXPERIENCE MONITORING

In a customer-centric age, empowered users are accustomed to getting extremely high levels of service, a reality that is forcing companies to evolve traditional performance monitoring into what Gartner now calls digital experience monitoring (DEM). DEM treats the user experience as the ultimate metric, and identifies how the myriad of underlying services, systems and components influence it. DEM is far more multi-dimensional than past end user experience monitoring approaches. IT Operations Analytics will evolve concurrently with DEM, handling more complexity (ingesting and analyzing more data from more sources), and increasing diagnostic accuracy and speed.
Dennis Callaghan
Director of Industry Innovation, Catchpoint

MONITOR WHAT MATTERS

We will see a significant shift away from "monitor everything", and a return to "monitor what matters." But this time, "what matters" will be determined algorithmically, not by policy, and consequently the performance data will be more adaptive and relevant.
Richard Whitehead
Chief Evangelist, Moogsoft

PREDICTABILITY

IT Operations Analytics (ITOA), in relation to performance management has yet to deliver the first promise of analytics: predictability. Although there are a number of interesting solutions around that are that advanced, especially in areas like network management (in combination with vertical/domain problems), the market has yet to witness an easy-to-use, intelligent solution that can see within the crystal ball and predict outages, failures and problems.
Goran Garevski
VP of Engineering, Comtrade Software

Read Next Steps for ITOA - Part 4, covering automation and dynamic IT environment.

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Next Steps for ITOA - Part 3

APMdigest asked experts across the industry — including analysts, consultants and vendors — for their opinions on the next steps for ITOA. These next steps include where the experts believe ITOA is headed, as well as where they think it should be headed. Part 3 covers monitoring and user experience.

Start with Next Steps for ITOA - Part 1

Start with Next Steps for ITOA - Part 2

MONITORING INTEGRATES WITH ITOA

Advanced analytics and machine learning will become table stakes in monitoring tools. Initially this will create a flurry of unsubstantiated rebranding efforts by vendors eager to catch up, but these will eventually either acquire their way into ITOA or exit the market.
Trace3 Research 360 View Trend Report: IT Operations Monitoring & Analytics (ITOMA)

USER EXPERIENCE

As powerful as APM tools are, they have always been application- or infrastructure-centric and have therefore missed a very important piece of the puzzle: the actual users. I predict that IT departments, with the encouragement of corporate management, will not only begin to recognize the value of understanding user experience and behavior, but will take the lead in leveraging these analytics to improve the quality of service they deliver. They will begin integrating user analytics as a core capability within their toolset to see exactly what happens when users enter information and navigate through screens. These unique insights will help them improve problem resolution, system performance, process optimization, employee efficiency and more.
Brian Berns
CEO, Knoa Software

DIGITAL EXPERIENCE MONITORING

In a customer-centric age, empowered users are accustomed to getting extremely high levels of service, a reality that is forcing companies to evolve traditional performance monitoring into what Gartner now calls digital experience monitoring (DEM). DEM treats the user experience as the ultimate metric, and identifies how the myriad of underlying services, systems and components influence it. DEM is far more multi-dimensional than past end user experience monitoring approaches. IT Operations Analytics will evolve concurrently with DEM, handling more complexity (ingesting and analyzing more data from more sources), and increasing diagnostic accuracy and speed.
Dennis Callaghan
Director of Industry Innovation, Catchpoint

MONITOR WHAT MATTERS

We will see a significant shift away from "monitor everything", and a return to "monitor what matters." But this time, "what matters" will be determined algorithmically, not by policy, and consequently the performance data will be more adaptive and relevant.
Richard Whitehead
Chief Evangelist, Moogsoft

PREDICTABILITY

IT Operations Analytics (ITOA), in relation to performance management has yet to deliver the first promise of analytics: predictability. Although there are a number of interesting solutions around that are that advanced, especially in areas like network management (in combination with vertical/domain problems), the market has yet to witness an easy-to-use, intelligent solution that can see within the crystal ball and predict outages, failures and problems.
Goran Garevski
VP of Engineering, Comtrade Software

Read Next Steps for ITOA - Part 4, covering automation and dynamic IT environment.

Related Links

Hot Topics

The Latest

Closing the Gap in Modern Tech and the Tools Meant to Monitor Them

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

MEAN TIME TO INSIGHT Podcast - Episode 23: NetOps Labor Shortage

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Why FinOps Rewrote Its Mission and What It Signals for Technology Management

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Clearing the Path to AI: Why Vendor Consolidation Matters Now

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Cold Data, Hot Problem: Why AI Is Rewriting Enterprise Storage Strategy

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

Observability at a Crossroads: AI, Economics, Complexity and the Enduring Power of Open Source

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

Explainability Is the New Battleground in AI-Powered Observability

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

Empowering the Human Side of the Autonomous IT Age

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI Scale Is Outpacing Infrastructure - and IT Leaders Are Running Out of Time

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

No Escalations ≠ No Work: Why Visibility in DevOps Matters More Now That AI Is Accelerating Everything

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...