Skip to main content

ITOA Delivers Powerful Insights

Sasha Gilenson

IT Operations professionals are now facing overwhelming amounts of infrastructure-related changes - such as hardware upgrades, OS patching, software upgrades, and server consolidations.

Based on the results of a recent survey conducted by Evolven, The IT Operations Analytics Report offers valuable insights into the challenges facing IT Operations, and how IT Operations Analytics (ITOA) can address these issues .

How Many of Your Incidents are Related to Changes?

With IT systems becoming more complex and more critical to keeping the business available, how are companies prepared to make sure performance does not suffer?

82% of IT professionals surveyed experienced at least one unplanned outage in the past 24 months due to changes that were difficult to investigate.

Between applications, environments, and individual instances, mistakes and unauthorized changes happen, demanding that IT Ops spend significant amounts of time managing configuration values.

The more complex the environment, the longer it takes to rectify or recover from downtime, with one of the first questions usually asked being “What changed?”

For many in IT Operations, as we saw from our survey, the answer to this question is difficult to reach, requiring detailed information. IT teams find themselves in a never-ending chase to keep up with the pace of change across the IT landscape. IT organizations are increasingly recognizing, as the survey results show, that a proactive approach to risk identification is more effective for outage prevention than playing catch-up.

What Tools are Key to Achieving IT Operations Excellence?

Today’s increasingly complex environments simply can’t be managed effectively through traditional processes. Likewise, information should not be siloed, and enterprise systems should not be disparate and disconnected. Looking to increase efficiency and minimize errors caused by change, IT organizations are looking to enhance their configuration management.

76% of IT professionals surveyed say tools that analyze IT configuration issues are the key to IT operations performance.

Configuration inconsistencies and unauthorized changes cause the most extreme challenges in IT. At the same time, the pressures faced by IT are only increasing. On one hand, IT teams are being asked to hold down spending, while expected to improve service quality.

Organizations have seen the following issues result from poor configuration management:

■ Increased reactive support issues and lower availability

■ Inability to determine user impact from changes

■ Increased time to resolve problems

■ Higher costs due to unused components

What Use Case Types Would You Find Most Valuable for Leveraging ITOA?

As companies face increased IT complexity, which is slowing progress and placing strain on IT staff, they are seeking to get the most value out of their day-to-day IT operations.

88% of IT professionals surveyed see the value of IT Operations Analytics as being applied to common IT Operations use cases.

The vast majority of the IT professionals surveyed consider IT analytics to be the best solution for addressing IT’s big data challenges.

IT Operations Analytics can be effectively applied to many common use cases in IT Operations, such as:

Change Management: Perform sanity checks to determine the probability of success before any change is executed.

Configuration Management: Detect discrepancies from desired configuration (drift) and reduce risk to environment stability.

Incident Management: Reduce incident response time and help eliminate incidents from occurring, transforming the investigation process by automatically analyzing all changes that occurred since the system worked fine, applying pattern and statistics based algorithms to identify an incident’s root-cause.

Problem Management: Reach root cause, or a probable cause, identification faster.

IT Operations Analytics Helps

IT Operations Analytics can end the chronic change and configuration challenges facing IT Operations today. The takeaway is that analytics are crucial to IT evolution and business success.

Sasha Gilenson is the Founder and CEO of Evolven Software.

Hot Topics

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.

ITOA Delivers Powerful Insights

Sasha Gilenson

IT Operations professionals are now facing overwhelming amounts of infrastructure-related changes - such as hardware upgrades, OS patching, software upgrades, and server consolidations.

Based on the results of a recent survey conducted by Evolven, The IT Operations Analytics Report offers valuable insights into the challenges facing IT Operations, and how IT Operations Analytics (ITOA) can address these issues .

How Many of Your Incidents are Related to Changes?

With IT systems becoming more complex and more critical to keeping the business available, how are companies prepared to make sure performance does not suffer?

82% of IT professionals surveyed experienced at least one unplanned outage in the past 24 months due to changes that were difficult to investigate.

Between applications, environments, and individual instances, mistakes and unauthorized changes happen, demanding that IT Ops spend significant amounts of time managing configuration values.

The more complex the environment, the longer it takes to rectify or recover from downtime, with one of the first questions usually asked being “What changed?”

For many in IT Operations, as we saw from our survey, the answer to this question is difficult to reach, requiring detailed information. IT teams find themselves in a never-ending chase to keep up with the pace of change across the IT landscape. IT organizations are increasingly recognizing, as the survey results show, that a proactive approach to risk identification is more effective for outage prevention than playing catch-up.

What Tools are Key to Achieving IT Operations Excellence?

Today’s increasingly complex environments simply can’t be managed effectively through traditional processes. Likewise, information should not be siloed, and enterprise systems should not be disparate and disconnected. Looking to increase efficiency and minimize errors caused by change, IT organizations are looking to enhance their configuration management.

76% of IT professionals surveyed say tools that analyze IT configuration issues are the key to IT operations performance.

Configuration inconsistencies and unauthorized changes cause the most extreme challenges in IT. At the same time, the pressures faced by IT are only increasing. On one hand, IT teams are being asked to hold down spending, while expected to improve service quality.

Organizations have seen the following issues result from poor configuration management:

■ Increased reactive support issues and lower availability

■ Inability to determine user impact from changes

■ Increased time to resolve problems

■ Higher costs due to unused components

What Use Case Types Would You Find Most Valuable for Leveraging ITOA?

As companies face increased IT complexity, which is slowing progress and placing strain on IT staff, they are seeking to get the most value out of their day-to-day IT operations.

88% of IT professionals surveyed see the value of IT Operations Analytics as being applied to common IT Operations use cases.

The vast majority of the IT professionals surveyed consider IT analytics to be the best solution for addressing IT’s big data challenges.

IT Operations Analytics can be effectively applied to many common use cases in IT Operations, such as:

Change Management: Perform sanity checks to determine the probability of success before any change is executed.

Configuration Management: Detect discrepancies from desired configuration (drift) and reduce risk to environment stability.

Incident Management: Reduce incident response time and help eliminate incidents from occurring, transforming the investigation process by automatically analyzing all changes that occurred since the system worked fine, applying pattern and statistics based algorithms to identify an incident’s root-cause.

Problem Management: Reach root cause, or a probable cause, identification faster.

IT Operations Analytics Helps

IT Operations Analytics can end the chronic change and configuration challenges facing IT Operations today. The takeaway is that analytics are crucial to IT evolution and business success.

Sasha Gilenson is the Founder and CEO of Evolven Software.

Hot Topics

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.