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Hybrid Cloud Is Here to Stay – and IT Leaders Are (Mostly) Missing the Tools They Need to Succeed

James Field
LogicMonitor

It won't come as a surprise to IT managers, but an alarming number of them describe their company's monitoring approach as "chaotic." According to a recent survey of over 500 global IT leaders, the challenges plaguing IT teams are significant, as they navigate everything from economic constraints, demands AI puts on their tech stack, and competing job priorities from senior leadership.

What Is the Problem?

The overwhelming majority of IT leaders (80%) say budget cuts are negatively impacting their company's cloud migration. At the same time, nearly the same amount (71%) say they expect to be working with a mix of both cloud and on-prem infrastructure — and all of them (100%) think it's best for business. It's clear that hybrid isn't going anywhere.

So what's the problem?

Almost half of IT leaders have only negative things to say about their company's current hybrid monitoring approach — contributing to that "chaotic" environment. And maybe most alarmingly, the majority (74%) of IT managers spend more than a full day each week responding to incidents. Giving IT teams that time back not only makes employees happier, but helps a businesses' bottom line. More on that later.

Where AI Fits In

We know artificial intelligence is absolutely everywhere these days — including on IT leaders' minds. Surprisingly, only 50% think that their organization's infrastructure is prepared to handle additional use of AI. Even worse: only 17% say their company's IT infrastructure completely supports business goals. This should be a wakeup call for the C-suite to listen to the concerns of their IT teams so they aren't hamstrung by tech capabilities when it comes time to implement AI tools.

They do have a wishlist, though. IT leaders mostly want AI to provide recommendations for actions they can take to solve incidents (taking a chunk out of that one day per week that they already spend responding), and ideally, recognize and resolve issues on its own. AIOps is heating up as an industry, so luckily for IT teams, this reality isn't far away.

The Big Picture: Helping IT Leaders Make an Impact

The IT teams I've worked with throughout my career have always been extremely impressive. They're committed to their work, steeped in the details, and they keep an eye on the bottom line and care deeply about how their work supports it. I was not surprised to see this is true of most IT leaders, too – 74% have ideas about how to solve business problems using their data, but no time to develop them.

These findings should alert company leadership that more needs to be done (cough cough, better tools!) to give IT leaders more job satisfaction, as 65% of them say they're happiest at work when they have interesting, innovative work to do. Freeing up their time is also imperative for the business: 40% have put off projects that increase user and customer satisfaction to focus on responding to incidents, and 35% say they put off increasing revenue. Talk about a missed opportunity.

All of this to say: heed the concerns of your IT people, and results — everything from job satisfaction to company performance — will follow.

James Field is Sr. Director of Product Strategy and Operations at LogicMonitor

Hot Topics

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 ...

Hybrid Cloud Is Here to Stay – and IT Leaders Are (Mostly) Missing the Tools They Need to Succeed

James Field
LogicMonitor

It won't come as a surprise to IT managers, but an alarming number of them describe their company's monitoring approach as "chaotic." According to a recent survey of over 500 global IT leaders, the challenges plaguing IT teams are significant, as they navigate everything from economic constraints, demands AI puts on their tech stack, and competing job priorities from senior leadership.

What Is the Problem?

The overwhelming majority of IT leaders (80%) say budget cuts are negatively impacting their company's cloud migration. At the same time, nearly the same amount (71%) say they expect to be working with a mix of both cloud and on-prem infrastructure — and all of them (100%) think it's best for business. It's clear that hybrid isn't going anywhere.

So what's the problem?

Almost half of IT leaders have only negative things to say about their company's current hybrid monitoring approach — contributing to that "chaotic" environment. And maybe most alarmingly, the majority (74%) of IT managers spend more than a full day each week responding to incidents. Giving IT teams that time back not only makes employees happier, but helps a businesses' bottom line. More on that later.

Where AI Fits In

We know artificial intelligence is absolutely everywhere these days — including on IT leaders' minds. Surprisingly, only 50% think that their organization's infrastructure is prepared to handle additional use of AI. Even worse: only 17% say their company's IT infrastructure completely supports business goals. This should be a wakeup call for the C-suite to listen to the concerns of their IT teams so they aren't hamstrung by tech capabilities when it comes time to implement AI tools.

They do have a wishlist, though. IT leaders mostly want AI to provide recommendations for actions they can take to solve incidents (taking a chunk out of that one day per week that they already spend responding), and ideally, recognize and resolve issues on its own. AIOps is heating up as an industry, so luckily for IT teams, this reality isn't far away.

The Big Picture: Helping IT Leaders Make an Impact

The IT teams I've worked with throughout my career have always been extremely impressive. They're committed to their work, steeped in the details, and they keep an eye on the bottom line and care deeply about how their work supports it. I was not surprised to see this is true of most IT leaders, too – 74% have ideas about how to solve business problems using their data, but no time to develop them.

These findings should alert company leadership that more needs to be done (cough cough, better tools!) to give IT leaders more job satisfaction, as 65% of them say they're happiest at work when they have interesting, innovative work to do. Freeing up their time is also imperative for the business: 40% have put off projects that increase user and customer satisfaction to focus on responding to incidents, and 35% say they put off increasing revenue. Talk about a missed opportunity.

All of this to say: heed the concerns of your IT people, and results — everything from job satisfaction to company performance — will follow.

James Field is Sr. Director of Product Strategy and Operations at LogicMonitor

Hot Topics

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 ...