Skip to main content

5 IT Operations Challenges – and 1 Main Cause

A recent survey of IT Operations executives found the following to be the most impactful challenges facing their teams:

1. Too much time spent resolving business-impacting application outages or slowdowns

IT Operations teams spend too many work hours resolving application performance problems. The biggest single opportunity to reduce this resource drain is to streamline the process of localizing the problem – in short, find the actual problem faster.

The Mean Time to Resolve issues (MTTR) is the primary measure that Operations teams use to determine their effectiveness in dealing with problems. Whenever Operations teams speak about management projects, the ultimate goal is to reduce MTTR.

Forrester Research’s Evelyn Oehrlich breaks down MTTR as the sum of four sub-components:

- The time it takes to detect a problem (measured by the MTTI or “Mean Time to Identify”)

- The time it takes to isolate the problem (measured by the MTTK or “Mean Time to Know”)

- The time it takes to implement the fix (measured by MTTF or “Mean Time to Fix”)

- The time it takes to verify that the fix is working (measured by MTTV or “Mean Time to Verify”)


Image removed.

As shown in the above graphic, the best opportunity to reduce the overall time to resolve issues is to cut the time spent isolating the root cause of the problem. Understanding that quickly finding where a problem occurred has the most potential for improvement, the focus should be on tools that isolate issues across the infrastructure, as opposed to solving more issues on specific platforms.

2. Too many Experts are required to help with application incidents

Having too many people spending time on bridge calls is a well-documented complaint. But really it is a symptom of a process problem. Bridge calls are attended by specialists – experts from the web tier, the database, the application server, etc. They are all on the same call to facilitate a broken process – that of using people to isolate the source of an application problem.

Management tools that provide a holistic view of application performance can eliminate the need to assemble the large team, and instead allow a single individual to isolate the problem component. With the source of the problem isolated, that individual can then engage only with the appropriate expert.

3. Problems are only discovered when users complain about them

As an Operations executive, I have a rule for my team that I never be surprised. I’m also realistic enough to know that sometimes things will go wrong. In an IT environment, outages will happen. The key is to not be surprised by the outages. This means proactive monitoring of applications – not just at the individual component level, but across the entire application infrastructure.

In today’s complex environments, relying on resource monitoring of individual servers is a sure-fire path to unpleasant surprises.

4. Management Tools can’t support the Mix of Technologies that Make up Apps

Management tools are built to address specific problems. Many of the APM tools in the field today were built to handle Java and .Net application code manipulation. These capabilities are important, but they don’t address problems that originate outside the application code. Enterprise applications of today are complicated animals – often consisting of several different discrete component types. IT Operations teams need to ensure that their management tools can identify and address the most common sources of application failures.

5. Implementation of mass virtualization, Private, and Hybrid Cloud

Virtualization and Private Cloud have become mainstream components of today’s application environments, and Hybrid Cloud is expected to be very big in 2013. Disconnecting the applications from the infrastructure specification creates a management visibility gap as to how systems are working together to deliver the business services. IT Operations teams need tools that can provide a complete application view across all these environments to be able to avoid the management blind spots.

One Major Cause: Application Complexity

The key difference in today’s applications from those running even 3 years ago is growing complexity. New technologies allow for more sophisticated enterprise applications - the days of applications being made up of a web server and a database are gone. Today’s applications feature a broad mixture of technologies and platforms, all with specialized functions and specialized management tools.

It’s this massive complexity that creates the other challenges:

- Today’s applications employ infrastructure components that alter the transaction paths and topology layout of applications on the fly, making it difficult or impossible to understand how transactions, applications and infrastructure work together.

- The resulting visibility gaps require experts for each platform to be available, just to TRY to understand (as a team) where applications and transactions go.

- Rapid change means that management tools struggle to keep up with the pace of change in technologies. In some cases, the platforms are so new that traditional management tools have no effective way of seeing even basic information.

- Finally, it is this dynamic complexity that makes it difficult for either IT Operations team members or full SWAT teams to solve problems when they occur. There are simply too many moving parts, too many new technologies, all put together in an unknown way (to the Operations Team) to deliver the desired business service.

The best way to deal with these challenges is to take a service-oriented approach to application service delivery. IT Operations teams that focus on how infrastructure performance impacts end-user service levels and use tools that manage transactions, applications, and infrastructure together will be able to overcome the 5 major challenges – cutting through those management gaps to provide true service management.

ABOUT Vic Nyman

Vic Nyman is the co-founder and COO of BlueStripe Software. Nyman has over 20 years of experience in systems management and APM and has held leadership positions at Wily Technology, IBM Tivoli, and Relicore/Symantec.

Hot Topics

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 ...

5 IT Operations Challenges – and 1 Main Cause

A recent survey of IT Operations executives found the following to be the most impactful challenges facing their teams:

1. Too much time spent resolving business-impacting application outages or slowdowns

IT Operations teams spend too many work hours resolving application performance problems. The biggest single opportunity to reduce this resource drain is to streamline the process of localizing the problem – in short, find the actual problem faster.

The Mean Time to Resolve issues (MTTR) is the primary measure that Operations teams use to determine their effectiveness in dealing with problems. Whenever Operations teams speak about management projects, the ultimate goal is to reduce MTTR.

Forrester Research’s Evelyn Oehrlich breaks down MTTR as the sum of four sub-components:

- The time it takes to detect a problem (measured by the MTTI or “Mean Time to Identify”)

- The time it takes to isolate the problem (measured by the MTTK or “Mean Time to Know”)

- The time it takes to implement the fix (measured by MTTF or “Mean Time to Fix”)

- The time it takes to verify that the fix is working (measured by MTTV or “Mean Time to Verify”)


Image removed.

As shown in the above graphic, the best opportunity to reduce the overall time to resolve issues is to cut the time spent isolating the root cause of the problem. Understanding that quickly finding where a problem occurred has the most potential for improvement, the focus should be on tools that isolate issues across the infrastructure, as opposed to solving more issues on specific platforms.

2. Too many Experts are required to help with application incidents

Having too many people spending time on bridge calls is a well-documented complaint. But really it is a symptom of a process problem. Bridge calls are attended by specialists – experts from the web tier, the database, the application server, etc. They are all on the same call to facilitate a broken process – that of using people to isolate the source of an application problem.

Management tools that provide a holistic view of application performance can eliminate the need to assemble the large team, and instead allow a single individual to isolate the problem component. With the source of the problem isolated, that individual can then engage only with the appropriate expert.

3. Problems are only discovered when users complain about them

As an Operations executive, I have a rule for my team that I never be surprised. I’m also realistic enough to know that sometimes things will go wrong. In an IT environment, outages will happen. The key is to not be surprised by the outages. This means proactive monitoring of applications – not just at the individual component level, but across the entire application infrastructure.

In today’s complex environments, relying on resource monitoring of individual servers is a sure-fire path to unpleasant surprises.

4. Management Tools can’t support the Mix of Technologies that Make up Apps

Management tools are built to address specific problems. Many of the APM tools in the field today were built to handle Java and .Net application code manipulation. These capabilities are important, but they don’t address problems that originate outside the application code. Enterprise applications of today are complicated animals – often consisting of several different discrete component types. IT Operations teams need to ensure that their management tools can identify and address the most common sources of application failures.

5. Implementation of mass virtualization, Private, and Hybrid Cloud

Virtualization and Private Cloud have become mainstream components of today’s application environments, and Hybrid Cloud is expected to be very big in 2013. Disconnecting the applications from the infrastructure specification creates a management visibility gap as to how systems are working together to deliver the business services. IT Operations teams need tools that can provide a complete application view across all these environments to be able to avoid the management blind spots.

One Major Cause: Application Complexity

The key difference in today’s applications from those running even 3 years ago is growing complexity. New technologies allow for more sophisticated enterprise applications - the days of applications being made up of a web server and a database are gone. Today’s applications feature a broad mixture of technologies and platforms, all with specialized functions and specialized management tools.

It’s this massive complexity that creates the other challenges:

- Today’s applications employ infrastructure components that alter the transaction paths and topology layout of applications on the fly, making it difficult or impossible to understand how transactions, applications and infrastructure work together.

- The resulting visibility gaps require experts for each platform to be available, just to TRY to understand (as a team) where applications and transactions go.

- Rapid change means that management tools struggle to keep up with the pace of change in technologies. In some cases, the platforms are so new that traditional management tools have no effective way of seeing even basic information.

- Finally, it is this dynamic complexity that makes it difficult for either IT Operations team members or full SWAT teams to solve problems when they occur. There are simply too many moving parts, too many new technologies, all put together in an unknown way (to the Operations Team) to deliver the desired business service.

The best way to deal with these challenges is to take a service-oriented approach to application service delivery. IT Operations teams that focus on how infrastructure performance impacts end-user service levels and use tools that manage transactions, applications, and infrastructure together will be able to overcome the 5 major challenges – cutting through those management gaps to provide true service management.

ABOUT Vic Nyman

Vic Nyman is the co-founder and COO of BlueStripe Software. Nyman has over 20 years of experience in systems management and APM and has held leadership positions at Wily Technology, IBM Tivoli, and Relicore/Symantec.

Hot Topics

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 ...