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Data Center Success Relies on Performance Analytics and IT Optimization

Pete Goldin
APMdigest

Of those surveyed, 95% of IT managers said the success of their data centers relies on proper performance analytics and IT optimization, with close to half reporting their data center is “extremely reliant” on these benefits. according to TeamQuest's Global IT Management survey, conducted by Kelton Research.

IT optimization and data center performance were seen as critically important to solving a range of issues including capacity management for big data, cloud outages and workplace productivity.

However, less than one in four managers (22%) describes their IT organization as able to predict the timing and/or consequences of a forecasted scenario; and as able to identify the action steps to remedy it.

Efficiency in IT systems was the top concern. 93% of respondents indicated that proper IT optimization and performance analysis would improve IT efficiency. 73% think their organizations overall IT risk would decrease due to these advantages.

Nearly three in four (74%) IT managers who use IT optimization and/or proper performance analysis solutions report that improved IT efficiency has benefited their company. Reduced outages (62%), better productivity (61%) and fewer resources spent on unexpected issues (53%) were among the advantages cited.

Other Key Findings:

■ On average IT managers deal with eight unexpected IT issues per week each requiring seven staff members to resolve.

■ Amongst the most common IT issues are network slowdowns or outages (42%), poor performing applications (37%), availability issues (37%), equipment failures (36%), and unanticipated change requests (34%)

■ 83% of IT managers said their organization lacks proper virtual machine management

■ 74% of IT managers believe IT risk would shrink if they had proper virtual management

■ 90% of IT managers believe that without the proper planning, virtual machine management is risky

■ 63% of IT managers have experienced cloud outages and 65% of those believe it could have been prevented. Nearly half (49%) believe that improper capacity planning was to blame

■ 89% of managers said IT optimization or performance analysis would improve overall business productivity

■ 88% said IT optimization or performance analysis would improve workforce productivity

“IT professionals around the globe seem to agree that their data centers are more reliant on IT optimization tools, proper capacity planning and the ability to use analytics. Not only are they proving to have a significant impact throughout the enterprise, delivering on everything from preventing cloud outages to improving overall business productivity, but they are also allowing IT the time they need to focus on improvements rather than incidents, ” said Per Bauer, TeamQuest Director of Global Services.

Survey Methodology: The TeamQuest Global IT Management survey was conducted between October 29, 2014, and November 16, 2014, among 419+ IT managers in 10 countries, working in companies with 1,000+ employees.

Pete Goldin is Editor and Publisher of APMdigest

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Data Center Success Relies on Performance Analytics and IT Optimization

Pete Goldin
APMdigest

Of those surveyed, 95% of IT managers said the success of their data centers relies on proper performance analytics and IT optimization, with close to half reporting their data center is “extremely reliant” on these benefits. according to TeamQuest's Global IT Management survey, conducted by Kelton Research.

IT optimization and data center performance were seen as critically important to solving a range of issues including capacity management for big data, cloud outages and workplace productivity.

However, less than one in four managers (22%) describes their IT organization as able to predict the timing and/or consequences of a forecasted scenario; and as able to identify the action steps to remedy it.

Efficiency in IT systems was the top concern. 93% of respondents indicated that proper IT optimization and performance analysis would improve IT efficiency. 73% think their organizations overall IT risk would decrease due to these advantages.

Nearly three in four (74%) IT managers who use IT optimization and/or proper performance analysis solutions report that improved IT efficiency has benefited their company. Reduced outages (62%), better productivity (61%) and fewer resources spent on unexpected issues (53%) were among the advantages cited.

Other Key Findings:

■ On average IT managers deal with eight unexpected IT issues per week each requiring seven staff members to resolve.

■ Amongst the most common IT issues are network slowdowns or outages (42%), poor performing applications (37%), availability issues (37%), equipment failures (36%), and unanticipated change requests (34%)

■ 83% of IT managers said their organization lacks proper virtual machine management

■ 74% of IT managers believe IT risk would shrink if they had proper virtual management

■ 90% of IT managers believe that without the proper planning, virtual machine management is risky

■ 63% of IT managers have experienced cloud outages and 65% of those believe it could have been prevented. Nearly half (49%) believe that improper capacity planning was to blame

■ 89% of managers said IT optimization or performance analysis would improve overall business productivity

■ 88% said IT optimization or performance analysis would improve workforce productivity

“IT professionals around the globe seem to agree that their data centers are more reliant on IT optimization tools, proper capacity planning and the ability to use analytics. Not only are they proving to have a significant impact throughout the enterprise, delivering on everything from preventing cloud outages to improving overall business productivity, but they are also allowing IT the time they need to focus on improvements rather than incidents, ” said Per Bauer, TeamQuest Director of Global Services.

Survey Methodology: The TeamQuest Global IT Management survey was conducted between October 29, 2014, and November 16, 2014, among 419+ IT managers in 10 countries, working in companies with 1,000+ employees.

Pete Goldin is Editor and Publisher of APMdigest

The Latest

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 ...

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

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 ...

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 ...

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 ...

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 ...

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 ...

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 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.

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 ...