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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.

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Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

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The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

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Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...

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

Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...