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Is IT Operations Going Away or Is It Enjoying a Renaissance?

The answer depends in part on how you define “IT operations”
Dennis Drogseth

It's safe to say that the role of IT Operations is changing, but beyond that there are countless opinions about just why and how. Lately I've been hearing a growing number of doomsday prophecies about how operations professionals are going away as they shrink in importance to managing an infrastructure already being replaced by cloud.

Others see only reactive, siloed professionals desperately in need of overlay teams (without strong operations roots) emerging somewhere between myth and reality.

Others see a dwindling role for operations in the age of microservices and containers, as development magically ascends to deliver full lifecycle application support.

And finally, and perhaps the most incontrovertible, for those environments with converged or hyper-converged solutions, the operations overhead is seriously reduced.

On the other hand, I speak to about 40-50 deployments a year centered on optimizing IT for service delivery. And in these dialogs I see a strong and consistent trend that isn't a move away from operations, but rather a deliberate transformation of how IT Operations teams work. These transformations include multi-dimensional IT service management (ITSM) integrations with the rest of operations, investments in advanced analytics and automation, team-directed approaches to improved process efficiencies, better data on governance and performance, and a psychological shift toward cross-domain, service-aware thinking.

These, in other words, follow in the tradition of the now much maligned term "Business Service Management" but are central in enabling a newly popular term "digital transformation" and ultimately impact all of IT, including development and the executive suite, as well as business stakeholders.

So which vision is correct? Gloom and doom or new levels of empowerment and rebirth?

As always, the answer is: it depends.

So let me examine this in a series of questions:

Question 1: What is IT Operations?

As I see it most often, IT Operations includes management for change, performance and service delivery across the full IT infrastructure and includes all domains except security, while sharing application performance issues with application owners and development. It also includes ITSM teams that typically report to the VP of Operations. Security interdependencies are on the rise, and EMA is planning a unique Q1 investigation of SecOps trends as my data and our security analyst indicate that operations and security teams are finally beginning to bridge the divide.

One of the "official" missions of IT Operations has always been to "run itself as a business." In parallel, EMA's research on digital transformation indicated that after the IT executive suite, "IT Operations as a whole" was most likely to oversee IT and digital transformation initiatives.

Question 2: What is the impact of cloud on IT Operations?

Generally, cloud, in all its various forms, has forced IT Operations teams to accelerate their directions toward more cross-domain awareness, superior investments in automation and analytics, and actually promoted more dialog with business stakeholders. (Of course cloud can have an opposite effect for operations teams unable or unwilling to recognize that they live in a new world order.)

Question 3: What about the growing role of overlay teams — are they reducing the role of IT Operations or enhancing it?

There should be little debate about the fact that "overlay" teams are on the rise, albeit once again they are defined in various ways by various constituencies. The mission of these overlay teams varies, of course, which is part of the challenge. It can range from "unified digital experience management across the full application lifecycle," to "cross-domain IT OpEx and CapEx asset optimization" or simply "optimizing the move to cloud" just to name three of the more prevalent. (By the way, EMA is about to get a lot of hard data on "unified digital experience management.") Moreover, these overlay teams typically are driven from the IT executive suite and include business stakeholders ranging from digital services managers and marketing, to LOB service consumers, to enterprise procurement, just to name a few examples.

In my conversations, these teams are critical in enhancing the role of IT Operations and helping it evolve into our "new age." However, this isn't to say these new directions are painless, smooth rides on chariots in the clouds. I routinely hear of staff being let go when they are unwilling to change how they think and work to support a full range of challenges from cloud, to mobile, to agile, to digital transformation. So I guess the answer here is a little bit of both, with the weight, as I see it, still solidly on "enhancement."

Question 4: What technologies most apply in supporting these "operational transformations?"

This of course could be a blog, or rather a book, in itself. But a very short answer would be to highlight advanced IT analytics, more effective levels of automation, multi-dimensional integrations between ITSM and operations, and advanced levels of user, customer and digital experience to inform on business outcomes and optimize IT operational performance.

I would also add that I see a strong tie between service modeling (in various forms) and analytics as a key growth area. At this point I'd like to mention a webinar I'll be doing on December 6: A Realistic Approach to Transforming IT Operations: Analytics + Automation + Common Sense. Please listen in if you can.

Question 5: Why did I write this blog?

While the webinar might seem to be the obvious answer, the original spark came from a whole host of dialogs with industry vendors indicating that, for various reasons, believe the sky is falling in on IT Operations. And in fact they often may be right, especially in those environments where IT Operations remains reactive, siloed, and lost in the past.

But my conversations (admittedly most often directed at technology deployments addressed in question 4) show a much more optimistic direction for IT Operations as a whole. What I feel is missing among the doomsayers is the understanding that new technologies are almost always additive, and in fact the current IT infrastructure and application landscape couldn't be more heterogeneous. What's needed most often isn't a pure, new way of working that magically replaces everything before it, but an investment in assimilation, governance and migration over time in which business objectives and IT objectives can meaningfully combine.

Read Transforming Operations, and IT as a Whole, with the Right Technology Investments

Image removed.

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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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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.

Is IT Operations Going Away or Is It Enjoying a Renaissance?

The answer depends in part on how you define “IT operations”
Dennis Drogseth

It's safe to say that the role of IT Operations is changing, but beyond that there are countless opinions about just why and how. Lately I've been hearing a growing number of doomsday prophecies about how operations professionals are going away as they shrink in importance to managing an infrastructure already being replaced by cloud.

Others see only reactive, siloed professionals desperately in need of overlay teams (without strong operations roots) emerging somewhere between myth and reality.

Others see a dwindling role for operations in the age of microservices and containers, as development magically ascends to deliver full lifecycle application support.

And finally, and perhaps the most incontrovertible, for those environments with converged or hyper-converged solutions, the operations overhead is seriously reduced.

On the other hand, I speak to about 40-50 deployments a year centered on optimizing IT for service delivery. And in these dialogs I see a strong and consistent trend that isn't a move away from operations, but rather a deliberate transformation of how IT Operations teams work. These transformations include multi-dimensional IT service management (ITSM) integrations with the rest of operations, investments in advanced analytics and automation, team-directed approaches to improved process efficiencies, better data on governance and performance, and a psychological shift toward cross-domain, service-aware thinking.

These, in other words, follow in the tradition of the now much maligned term "Business Service Management" but are central in enabling a newly popular term "digital transformation" and ultimately impact all of IT, including development and the executive suite, as well as business stakeholders.

So which vision is correct? Gloom and doom or new levels of empowerment and rebirth?

As always, the answer is: it depends.

So let me examine this in a series of questions:

Question 1: What is IT Operations?

As I see it most often, IT Operations includes management for change, performance and service delivery across the full IT infrastructure and includes all domains except security, while sharing application performance issues with application owners and development. It also includes ITSM teams that typically report to the VP of Operations. Security interdependencies are on the rise, and EMA is planning a unique Q1 investigation of SecOps trends as my data and our security analyst indicate that operations and security teams are finally beginning to bridge the divide.

One of the "official" missions of IT Operations has always been to "run itself as a business." In parallel, EMA's research on digital transformation indicated that after the IT executive suite, "IT Operations as a whole" was most likely to oversee IT and digital transformation initiatives.

Question 2: What is the impact of cloud on IT Operations?

Generally, cloud, in all its various forms, has forced IT Operations teams to accelerate their directions toward more cross-domain awareness, superior investments in automation and analytics, and actually promoted more dialog with business stakeholders. (Of course cloud can have an opposite effect for operations teams unable or unwilling to recognize that they live in a new world order.)

Question 3: What about the growing role of overlay teams — are they reducing the role of IT Operations or enhancing it?

There should be little debate about the fact that "overlay" teams are on the rise, albeit once again they are defined in various ways by various constituencies. The mission of these overlay teams varies, of course, which is part of the challenge. It can range from "unified digital experience management across the full application lifecycle," to "cross-domain IT OpEx and CapEx asset optimization" or simply "optimizing the move to cloud" just to name three of the more prevalent. (By the way, EMA is about to get a lot of hard data on "unified digital experience management.") Moreover, these overlay teams typically are driven from the IT executive suite and include business stakeholders ranging from digital services managers and marketing, to LOB service consumers, to enterprise procurement, just to name a few examples.

In my conversations, these teams are critical in enhancing the role of IT Operations and helping it evolve into our "new age." However, this isn't to say these new directions are painless, smooth rides on chariots in the clouds. I routinely hear of staff being let go when they are unwilling to change how they think and work to support a full range of challenges from cloud, to mobile, to agile, to digital transformation. So I guess the answer here is a little bit of both, with the weight, as I see it, still solidly on "enhancement."

Question 4: What technologies most apply in supporting these "operational transformations?"

This of course could be a blog, or rather a book, in itself. But a very short answer would be to highlight advanced IT analytics, more effective levels of automation, multi-dimensional integrations between ITSM and operations, and advanced levels of user, customer and digital experience to inform on business outcomes and optimize IT operational performance.

I would also add that I see a strong tie between service modeling (in various forms) and analytics as a key growth area. At this point I'd like to mention a webinar I'll be doing on December 6: A Realistic Approach to Transforming IT Operations: Analytics + Automation + Common Sense. Please listen in if you can.

Question 5: Why did I write this blog?

While the webinar might seem to be the obvious answer, the original spark came from a whole host of dialogs with industry vendors indicating that, for various reasons, believe the sky is falling in on IT Operations. And in fact they often may be right, especially in those environments where IT Operations remains reactive, siloed, and lost in the past.

But my conversations (admittedly most often directed at technology deployments addressed in question 4) show a much more optimistic direction for IT Operations as a whole. What I feel is missing among the doomsayers is the understanding that new technologies are almost always additive, and in fact the current IT infrastructure and application landscape couldn't be more heterogeneous. What's needed most often isn't a pure, new way of working that magically replaces everything before it, but an investment in assimilation, governance and migration over time in which business objectives and IT objectives can meaningfully combine.

Read Transforming Operations, and IT as a Whole, with the Right Technology Investments

Image removed.

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.