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Rising IT Complexity Threatens Modernization - Survey Shows SysAdmins Under Pressure

Martin Hirschvogel
Checkmk

Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk.

Complexity Undermines Control and Cybersecurity

As cloud adoption, containerization, and serverless computing scale up, IT teams are struggling to maintain control, manage workloads, and mitigate risks. Without a coordinated response, the very goals of digital transformation could be at stake.

The survey highlights a dramatic rise in operational strain. Four out of five IT professionals say their tasks are becoming more complex, while 83% feel intense pressure to keep up with the rapid pace of innovation. This complexity isn't just technical — it's operational. Fragmented toolchains, distributed systems, and increased interdependencies are making environments more difficult to manage and leaving them more vulnerable to cyber threats.

Many teams find themselves forced into short-term solutions. In fact, 59% of respondents admit that quick fixes — often implemented under pressure — end up causing new problems. The lack of coherence in IT tool strategies further escalates costs and maintenance overhead.

Staff Shortages and Skills Gaps Add Fuel to the Fire

The strain on human resources is just as critical. Half of those surveyed report heavier workloads due to staffing shortages. At the same time, 49% now identify the IT skills gap as the greatest barrier to modernization — a 10 percentage point increase in just two years.

Upskilling is non-negotiable: A striking 94% of IT professionals say they'll need to learn new technologies in the next 12 months to stay effective. Skill areas in high demand include automation, configuration management, and IT monitoring — competencies that are increasingly tied to system resilience and performance. DevOps and programming expertise are also gaining traction as deployment cycles accelerate.

AI Expectations Remain Modest

Despite the buzz around artificial intelligence, the survey reveals skepticism around its real-world value. Only 40% of survey respondents expect AI to significantly reduce their daily workload. AI-driven monitoring ranks among the lowest-priority tools today, with most teams focusing instead on foundational capabilities that offer direct, tangible insights.

Monitoring: A Critical Line of Defense

Monitoring is widely regarded as essential for keeping operations on track. An overwhelming 94% of IT professionals consider IT infrastructure monitoring crucial for reducing Mean Time to Resolution (MTTR) and maintaining service level objectives (SLOs). Log management (72%), application performance management (64%), and full-stack observability (60%) are also seen as key areas, as IT teams increasingly rely on tools and methods that provide deeper insights into system components and dependencies, aiming for end-to-end visibility.

However, even effective monitoring is being challenged. A lack of knowledge is the second biggest barrier to improving MTTR — right behind infrastructure complexity itself. Without adequate support and training, even the best platforms can fall short of delivering value.

Lowering the Barrier to Innovation

The  report paints a clear picture of an industry under pressure: complexity is rising, skills are in short supply, and workloads are becoming unsustainable. To help, technology providers must lower adoption barriers and lighten the load on IT teams — with simple setup, intuitive workflows, strong automation, and flexible SaaS models. These platforms must be built not just for modern systems, but for the real-world challenges sysadmins face every day.

As IT demands grow, one thing is clear: innovation won't scale unless those managing it can keep up. Investing in better tools, training, and support for sysadmins isn't optional — it's essential to digital transformation.

Methodology: In fall 2024, Checkmk surveyed 192 IT professionals in 27 countries, primarily in IT operations, management, and consulting. Most respondents were based in Europe and North America.

Martin Hirschvogel is Chief Product Officer at Checkmk

The Latest

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

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Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

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Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...

Rising IT Complexity Threatens Modernization - Survey Shows SysAdmins Under Pressure

Martin Hirschvogel
Checkmk

Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk.

Complexity Undermines Control and Cybersecurity

As cloud adoption, containerization, and serverless computing scale up, IT teams are struggling to maintain control, manage workloads, and mitigate risks. Without a coordinated response, the very goals of digital transformation could be at stake.

The survey highlights a dramatic rise in operational strain. Four out of five IT professionals say their tasks are becoming more complex, while 83% feel intense pressure to keep up with the rapid pace of innovation. This complexity isn't just technical — it's operational. Fragmented toolchains, distributed systems, and increased interdependencies are making environments more difficult to manage and leaving them more vulnerable to cyber threats.

Many teams find themselves forced into short-term solutions. In fact, 59% of respondents admit that quick fixes — often implemented under pressure — end up causing new problems. The lack of coherence in IT tool strategies further escalates costs and maintenance overhead.

Staff Shortages and Skills Gaps Add Fuel to the Fire

The strain on human resources is just as critical. Half of those surveyed report heavier workloads due to staffing shortages. At the same time, 49% now identify the IT skills gap as the greatest barrier to modernization — a 10 percentage point increase in just two years.

Upskilling is non-negotiable: A striking 94% of IT professionals say they'll need to learn new technologies in the next 12 months to stay effective. Skill areas in high demand include automation, configuration management, and IT monitoring — competencies that are increasingly tied to system resilience and performance. DevOps and programming expertise are also gaining traction as deployment cycles accelerate.

AI Expectations Remain Modest

Despite the buzz around artificial intelligence, the survey reveals skepticism around its real-world value. Only 40% of survey respondents expect AI to significantly reduce their daily workload. AI-driven monitoring ranks among the lowest-priority tools today, with most teams focusing instead on foundational capabilities that offer direct, tangible insights.

Monitoring: A Critical Line of Defense

Monitoring is widely regarded as essential for keeping operations on track. An overwhelming 94% of IT professionals consider IT infrastructure monitoring crucial for reducing Mean Time to Resolution (MTTR) and maintaining service level objectives (SLOs). Log management (72%), application performance management (64%), and full-stack observability (60%) are also seen as key areas, as IT teams increasingly rely on tools and methods that provide deeper insights into system components and dependencies, aiming for end-to-end visibility.

However, even effective monitoring is being challenged. A lack of knowledge is the second biggest barrier to improving MTTR — right behind infrastructure complexity itself. Without adequate support and training, even the best platforms can fall short of delivering value.

Lowering the Barrier to Innovation

The  report paints a clear picture of an industry under pressure: complexity is rising, skills are in short supply, and workloads are becoming unsustainable. To help, technology providers must lower adoption barriers and lighten the load on IT teams — with simple setup, intuitive workflows, strong automation, and flexible SaaS models. These platforms must be built not just for modern systems, but for the real-world challenges sysadmins face every day.

As IT demands grow, one thing is clear: innovation won't scale unless those managing it can keep up. Investing in better tools, training, and support for sysadmins isn't optional — it's essential to digital transformation.

Methodology: In fall 2024, Checkmk surveyed 192 IT professionals in 27 countries, primarily in IT operations, management, and consulting. Most respondents were based in Europe and North America.

Martin Hirschvogel is Chief Product Officer at Checkmk

The Latest

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...