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Lack of Infrastructure Visibility Puts Businesses at Risk

Len Rosenthal

Most enterprises lack the complete visibility required to avoid business-impacting application outages and slowdowns – resulting in nearly 90 percent of enterprises being unable to consistently meet service level agreements (SLAs) for their business-critical applications, according to a recent survey conducted by Dimensional Research and Virtual Instruments. This research indicates a serious gap in IT operations teams' ability to monitor their enterprises' highly virtualized, multi-vendor hybrid data center environments, and the results show that this lack of visibility is significantly impacting business.

Blind Spots, Slowdowns and Outages Abound

59 percent of application outages and performance problems are related to infrastructure

The reality is that large enterprises endure a substantial number of application outages and performance issues every year, and an overwhelming number of those surveyed indicated that a slowdown impacts businesses just as much as a full outage.

86 percent of users experience two or more significant outages a year, with 61 percent suffering from four or more in the same period.

59 percent of application outages and performance problems are related to infrastructure, which begs the question: why can't IT teams see these problems coming, and what's getting in the way of timely resolution?

Too Many Cooks in the Kitchen

There are many dozens of infrastructure and application monitoring tools available to enterprises, so why does this visibility gap still exist?

This research showed that it's not necessarily a lack of tools that may be causing the problem, but rather the combination of too many silo-specific tools. In fact, more than 70 percent of respondents use more than five IT infrastructure monitoring tools, and 15 percent use more than 20!

But despite this plethora of tools, 54 percent of companies lack full visibility into their infrastructure and application workload behavior, and 42 percent of companies operate primarily in "reactive mode" when managing their infrastructure.

Teamwork Makes the Dream Work

When it comes to the modern enterprise, there's no single internal team that can accurately manage and assess application performance requirements. However, less than half of enterprises take a collaborative approach to establishing performance requirements for new data center infrastructure. With no collective understanding of how applications relate to the underlying infrastructure, the resulting blind spots cause chain reactions that leave enterprises highly exposed.

79 percent of application outages and other issues directly impact customers

Nearly 40 percent of enterprises say that performance issues related to infrastructure are the most challenging to resolve, and when you consider that 79 percent of application outages and other issues directly impact customers, there just isn't room for guessing.

Deeper Insights Are the Key

The lack of visibility and proactive infrastructure and application management contributes to a lack of confidence from IT teams and their executives. In fact, 62 percent doubt that their current infrastructure would be able to meet their projected performance needs in the next two years, and two-thirds of respondents feel that they're often held personally responsible for application outages and slowdowns.

In addition, with an increasing number of applications being deployed in public clouds, nearly 65 percent are concerned about the perceived value of the internal IT infrastructure team to the business.

As discouraging as these findings may seem, the numbers indicate a strong opportunity for engineering, operations and application teams to come together and gain a deeper understanding of the impact of their applications on the underlying infrastructure, and visa versa. Since applications and infrastructure are intertwined to the point where they can no longer be viewed as distinct entities, an infrastructure monitoring approach that understands application workload behavior is essential to performance assurance.

The bottom line is that in today's highly competitive business environment, enterprises cannot afford to test their customers' limited patience by having an unacceptable number of application outages or slowdowns.

The Latest

For fifteen years, observability lived downstream of everything else. Code shipped, something broke, an engineer went to the dashboards. The job was forensic. The pillars we built, such as logs, metrics, and traces, were designed for that role: tell a human what just happened, fast enough that they can make it stop. That role has quietly ended ...

Hybrid IT has become the standard operating model for enterprises — but that companies are still looking for the right hybrid IT mix, according to the 2026 State of the Data Center Report from CoreSite. After years of cloud migration and hybrid adoption, organizations are shifting their focus from deciding whether to use cloud, colocation or on-premises infrastructure to determining which workloads belong in each environment ...

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

Lack of Infrastructure Visibility Puts Businesses at Risk

Len Rosenthal

Most enterprises lack the complete visibility required to avoid business-impacting application outages and slowdowns – resulting in nearly 90 percent of enterprises being unable to consistently meet service level agreements (SLAs) for their business-critical applications, according to a recent survey conducted by Dimensional Research and Virtual Instruments. This research indicates a serious gap in IT operations teams' ability to monitor their enterprises' highly virtualized, multi-vendor hybrid data center environments, and the results show that this lack of visibility is significantly impacting business.

Blind Spots, Slowdowns and Outages Abound

59 percent of application outages and performance problems are related to infrastructure

The reality is that large enterprises endure a substantial number of application outages and performance issues every year, and an overwhelming number of those surveyed indicated that a slowdown impacts businesses just as much as a full outage.

86 percent of users experience two or more significant outages a year, with 61 percent suffering from four or more in the same period.

59 percent of application outages and performance problems are related to infrastructure, which begs the question: why can't IT teams see these problems coming, and what's getting in the way of timely resolution?

Too Many Cooks in the Kitchen

There are many dozens of infrastructure and application monitoring tools available to enterprises, so why does this visibility gap still exist?

This research showed that it's not necessarily a lack of tools that may be causing the problem, but rather the combination of too many silo-specific tools. In fact, more than 70 percent of respondents use more than five IT infrastructure monitoring tools, and 15 percent use more than 20!

But despite this plethora of tools, 54 percent of companies lack full visibility into their infrastructure and application workload behavior, and 42 percent of companies operate primarily in "reactive mode" when managing their infrastructure.

Teamwork Makes the Dream Work

When it comes to the modern enterprise, there's no single internal team that can accurately manage and assess application performance requirements. However, less than half of enterprises take a collaborative approach to establishing performance requirements for new data center infrastructure. With no collective understanding of how applications relate to the underlying infrastructure, the resulting blind spots cause chain reactions that leave enterprises highly exposed.

79 percent of application outages and other issues directly impact customers

Nearly 40 percent of enterprises say that performance issues related to infrastructure are the most challenging to resolve, and when you consider that 79 percent of application outages and other issues directly impact customers, there just isn't room for guessing.

Deeper Insights Are the Key

The lack of visibility and proactive infrastructure and application management contributes to a lack of confidence from IT teams and their executives. In fact, 62 percent doubt that their current infrastructure would be able to meet their projected performance needs in the next two years, and two-thirds of respondents feel that they're often held personally responsible for application outages and slowdowns.

In addition, with an increasing number of applications being deployed in public clouds, nearly 65 percent are concerned about the perceived value of the internal IT infrastructure team to the business.

As discouraging as these findings may seem, the numbers indicate a strong opportunity for engineering, operations and application teams to come together and gain a deeper understanding of the impact of their applications on the underlying infrastructure, and visa versa. Since applications and infrastructure are intertwined to the point where they can no longer be viewed as distinct entities, an infrastructure monitoring approach that understands application workload behavior is essential to performance assurance.

The bottom line is that in today's highly competitive business environment, enterprises cannot afford to test their customers' limited patience by having an unacceptable number of application outages or slowdowns.

The Latest

For fifteen years, observability lived downstream of everything else. Code shipped, something broke, an engineer went to the dashboards. The job was forensic. The pillars we built, such as logs, metrics, and traces, were designed for that role: tell a human what just happened, fast enough that they can make it stop. That role has quietly ended ...

Hybrid IT has become the standard operating model for enterprises — but that companies are still looking for the right hybrid IT mix, according to the 2026 State of the Data Center Report from CoreSite. After years of cloud migration and hybrid adoption, organizations are shifting their focus from deciding whether to use cloud, colocation or on-premises infrastructure to determining which workloads belong in each environment ...

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...