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Taking IT Operations Beyond Firefighting with ITOA

Sasha Gilenson

Today's infrastructure and operations (I&O) leaders are in a tight spot. On the one hand under constant pressure to lower operating costs, while on the other hand the business expects them to reinvent themselves, improve their capabilities, and directly impact the company's bottom line. To take control in a complex world of business and IT services, I&O leaders must adapt to doing more with less, balancing the demands of business groups with available IT resources, troubleshooting more effectively.

Chasing vs. Preventing Problems - IT Firefighting

IT is mandated to build and maintain IT environments with the highest possible availability (within budget and available resources). Challenges faced by IT Operations have intensified due to both the rapid growth in performance and event monitoring data volumes. As a result, for many IT organizations, especially with limited resources and with specialists wearing many hats, they often spend too much time fighting fires with “maintenance & support” and not enough time proactively avoiding issues like performance or availability problems.

The amount of time IT Ops spends firefighting not only hurts the IT department, but innovation across the entire company. With the magnitude of solutions in today's organization requiring input from IT, business opportunities are missed - from mastering proper new tech developments to better addressing the agile demands of the business. So how can the IT pro, who is fed up with just handling crisis after crisis, better leverage limited resources and get onto the important issues?

Old Approaches Don't Help

To keep up with the complexity of its IT environment IT Operations team's management practices, like the ITIL process approach, need to evolve and address the abundant data and complexity continuing to confront operations teams. In the past, while trying to stick to processes that were intended to make IT more efficient, these processes haven't been able to evolve fast enough, as evidenced by how the average team is burdened with bad practices that don't just slow down investigation efforts, but waste resources and really hamper innovation.

Furthermore, in many cases, traditional IT management tools were not designed to deal with today's volume, complexity and dynamics, leaving IT teams burdened when facing performance issues. While these tools may be able to provide IT Operations teams with lots of raw data, they lack insights or actionable information, leaving IT Operations without a successful way to pursue these issues.

Managing highly complex IT environments while trapped in a reactive mode leaves IT managers at a loss for how to understand all causes and effects happening amongst the hundreds of thousands of technologies in use across the enterprise. IT Operations needs to step back and take a more comprehensive approach, breaking the “reactive” cycle.

Break the Reactive Cycle

IT Ops teams have to cope with the reality of decreasing amounts of firefighters, while facing growing amounts of fires.

A prime example of what ignites these fires is change, which still remains a major blind spot for IT Operations and exposes business systems to risk each time a change happens in an application, infrastructure, data or workload. If some parameter somewhere in the application configuration was changed in a way that results in a critical issue, then it can take several days for the assembled IT firefighting team just to identify and find this "needle in the haystack" cause. Between planned applications or infrastructure updates, and individual emergency hotfixes, mistakes and unauthorized changes often happen (as has been seen with some high profile outages such as with Google), demanding that IT Ops spend long amounts of time fighting fires on IT systems.

This imbalance cannot continue forever. So the best solution for IT operations is to break the reactive cycle and move towards fire prevention to finally proactively detect situations that can cause problems early enough and quickly and easily resolve them. Where can IT Operations turn to be in prevention mode instead of reaction?

Preventing Fires with IT Operations Analytics

In complex environments, operations management needs more than the automation of mundane tasks to actually prevent issues. One of the approaches that can enhance automation is IT Operations Analytics (ITOA).

In the same spirit of business intelligence (BI), ITOA can blend operational data from the various silo-sourced data like machine events recorded in logs, APM metrics, security events, configuration changes etc. IT Operations Analytics can take a complex IT environment overflowing with data and transform it, turning operational data into a competitive tool that provides IT staff with the right information at the right time. Applying such techniques as complex-event processing, statistical pattern discovery, behavior learning engines, unstructured text file search, topology mapping and analysis, and multidimensional database analysis, IT Operations Analytics can sift through terabytes of operations data in real time, spotting risks and then presenting them in an understandable context.

Manage IT via a Prism of Change

With change requests and changes coming at a blinding pace, IT Operations teams need to use ITOA solutions to carry out a top down analysis blending and reviewing the diverse IT Operations data via changes as they occur, instead of reverse engineering a problem's root cause from low level machine events and metrics.

ITOA gives IT managers the ability to analyze IT operations through a prism of change that drives a single point of view of operations, allowing effective prevention and resolution of issues. ITOA helps IT specialists uncover why environments are not operating as they should, correlating various metrics into the context of the changing state of the environment (release, infrastructure update, user workload change etc.), allowing operators to successfully remediate and more importantly prevent issues.

Get More from Less Resources with Automation

Increased automation can enable IT Operations to identify such harmful changes while they happen and effectively remediate them, overcoming the changes that pose risk to stability and performance. Automation can ensure the error-free execution of mundane tasks, increasing the quality, consistency and availability of services delivered by IT Operations, dramatically lowering the cost per unit of management; for example, patching thousands of physical servers or virtual machines with no human involvement.

While automation can provide IT Operations teams with more time to focus on innovation and deployment of new applications, it's really just a first step for helping IT Operations managers proactively understand what is happening in their environments.

New IT Operations Analytics tools take a fresh perspective on the abundant data and complexity confronting operations teams, automatically generating actionable insights that current tools don't offer, to help IT stay ahead of the curve. These solutions enable IT organizations to address a broader set of tasks, making problem resolution and root cause analysis easier and faster.

Sasha Gilenson is the Founder and CEO of Evolven Software.

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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 ...

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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 ...

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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.

Taking IT Operations Beyond Firefighting with ITOA

Sasha Gilenson

Today's infrastructure and operations (I&O) leaders are in a tight spot. On the one hand under constant pressure to lower operating costs, while on the other hand the business expects them to reinvent themselves, improve their capabilities, and directly impact the company's bottom line. To take control in a complex world of business and IT services, I&O leaders must adapt to doing more with less, balancing the demands of business groups with available IT resources, troubleshooting more effectively.

Chasing vs. Preventing Problems - IT Firefighting

IT is mandated to build and maintain IT environments with the highest possible availability (within budget and available resources). Challenges faced by IT Operations have intensified due to both the rapid growth in performance and event monitoring data volumes. As a result, for many IT organizations, especially with limited resources and with specialists wearing many hats, they often spend too much time fighting fires with “maintenance & support” and not enough time proactively avoiding issues like performance or availability problems.

The amount of time IT Ops spends firefighting not only hurts the IT department, but innovation across the entire company. With the magnitude of solutions in today's organization requiring input from IT, business opportunities are missed - from mastering proper new tech developments to better addressing the agile demands of the business. So how can the IT pro, who is fed up with just handling crisis after crisis, better leverage limited resources and get onto the important issues?

Old Approaches Don't Help

To keep up with the complexity of its IT environment IT Operations team's management practices, like the ITIL process approach, need to evolve and address the abundant data and complexity continuing to confront operations teams. In the past, while trying to stick to processes that were intended to make IT more efficient, these processes haven't been able to evolve fast enough, as evidenced by how the average team is burdened with bad practices that don't just slow down investigation efforts, but waste resources and really hamper innovation.

Furthermore, in many cases, traditional IT management tools were not designed to deal with today's volume, complexity and dynamics, leaving IT teams burdened when facing performance issues. While these tools may be able to provide IT Operations teams with lots of raw data, they lack insights or actionable information, leaving IT Operations without a successful way to pursue these issues.

Managing highly complex IT environments while trapped in a reactive mode leaves IT managers at a loss for how to understand all causes and effects happening amongst the hundreds of thousands of technologies in use across the enterprise. IT Operations needs to step back and take a more comprehensive approach, breaking the “reactive” cycle.

Break the Reactive Cycle

IT Ops teams have to cope with the reality of decreasing amounts of firefighters, while facing growing amounts of fires.

A prime example of what ignites these fires is change, which still remains a major blind spot for IT Operations and exposes business systems to risk each time a change happens in an application, infrastructure, data or workload. If some parameter somewhere in the application configuration was changed in a way that results in a critical issue, then it can take several days for the assembled IT firefighting team just to identify and find this "needle in the haystack" cause. Between planned applications or infrastructure updates, and individual emergency hotfixes, mistakes and unauthorized changes often happen (as has been seen with some high profile outages such as with Google), demanding that IT Ops spend long amounts of time fighting fires on IT systems.

This imbalance cannot continue forever. So the best solution for IT operations is to break the reactive cycle and move towards fire prevention to finally proactively detect situations that can cause problems early enough and quickly and easily resolve them. Where can IT Operations turn to be in prevention mode instead of reaction?

Preventing Fires with IT Operations Analytics

In complex environments, operations management needs more than the automation of mundane tasks to actually prevent issues. One of the approaches that can enhance automation is IT Operations Analytics (ITOA).

In the same spirit of business intelligence (BI), ITOA can blend operational data from the various silo-sourced data like machine events recorded in logs, APM metrics, security events, configuration changes etc. IT Operations Analytics can take a complex IT environment overflowing with data and transform it, turning operational data into a competitive tool that provides IT staff with the right information at the right time. Applying such techniques as complex-event processing, statistical pattern discovery, behavior learning engines, unstructured text file search, topology mapping and analysis, and multidimensional database analysis, IT Operations Analytics can sift through terabytes of operations data in real time, spotting risks and then presenting them in an understandable context.

Manage IT via a Prism of Change

With change requests and changes coming at a blinding pace, IT Operations teams need to use ITOA solutions to carry out a top down analysis blending and reviewing the diverse IT Operations data via changes as they occur, instead of reverse engineering a problem's root cause from low level machine events and metrics.

ITOA gives IT managers the ability to analyze IT operations through a prism of change that drives a single point of view of operations, allowing effective prevention and resolution of issues. ITOA helps IT specialists uncover why environments are not operating as they should, correlating various metrics into the context of the changing state of the environment (release, infrastructure update, user workload change etc.), allowing operators to successfully remediate and more importantly prevent issues.

Get More from Less Resources with Automation

Increased automation can enable IT Operations to identify such harmful changes while they happen and effectively remediate them, overcoming the changes that pose risk to stability and performance. Automation can ensure the error-free execution of mundane tasks, increasing the quality, consistency and availability of services delivered by IT Operations, dramatically lowering the cost per unit of management; for example, patching thousands of physical servers or virtual machines with no human involvement.

While automation can provide IT Operations teams with more time to focus on innovation and deployment of new applications, it's really just a first step for helping IT Operations managers proactively understand what is happening in their environments.

New IT Operations Analytics tools take a fresh perspective on the abundant data and complexity confronting operations teams, automatically generating actionable insights that current tools don't offer, to help IT stay ahead of the curve. These solutions enable IT organizations to address a broader set of tasks, making problem resolution and root cause analysis easier and faster.

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.