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Q&A Part Two: TRAC Research Talks About the APM Spectrum

Pete Goldin
APMdigest

In Part Two of APMdigest's exclusive interview, Bojan Simic, President and Principal Analyst at TRAC Research, talks about the firm's new APM Spectrum report, APM analytics, virtualization, and different types of APM for different job roles.

Start with Q&A Part One: TRAC Research Talks About the APM Spectrum

APM: Your report deals a lot with job roles. Did you see differences in expectations for APM solutions between IT operations and developers?

TRAC: We saw a major difference between IT operations versus developers, in terms of what they are looking to purchase. You can talk to developers and IT operations about the same exact tool and developers might say it is very effective, while IT operations will say it is too difficult for them to deploy in the workflow, and just not designed for what they are trying to do.

We asked developers and IT operations about their levels of satisfaction with the solutions that are currently being deployed. The data shows that developers are more likely to say that usability of data is pretty good. 59% of developers said they are satisfied, versus 40% of IT operations.

We also asked a question about the quality of user experience, and the numbers flip-flopped. 56% of IT operations said they were satisfied compared to only 39% of developers. Part of the reason is that some of the solutions being purchased by developers work really well in pre-production, but they are not as effective in production.

APM: So what is the solution? Do developers and IT operations always require separate tools?

TRAC: In some cases they could benefit from using two separate solutions. It really depends on the use case. A lot of it has to do with how they want to use the data they are collecting, whether it is one tool or multiple tools, and how the tool actually maps to what they're trying to do in production versus pre-production.

It goes back to what I mentioned before, it is not about selecting one solution that is going to take care of all your needs, user experience monitoring, transaction monitoring, infrastructure view — in many cases you need multiple products. What is important to know is: can these products work together?

One point that is important to mention, we asked the question in the survey about tools being used in pre-production only, production only, or both pre-production and production. 52% said APM tools are being used in production only. 10% are being used in pre-production only. 38% are being used in both. So on the developer side, you need to make sure the tool can also be effective in production. That is one of the recommendations that we have for developers in the study.

APM: Developer vs. IT ops is a fairly high profile example. Can you give some other examples of APM for specific job roles?

TRAC: We have seen quite a few people who purchase APM solutions, but they come from the business side, which IT is not even aware of. We are seeing almost a new class of APM deployments where IT is not even involved in the buying cycle. They might not even be aware it exists because the business side is buying APM for their purposes. Business users are becoming almost a separate submarket.

We are seeing more marketing folks being able to benefit from APM data if it is presented in the right way. They don't necessarily care about all the nuts and bolts of the technology, looking at packets and code, but they do care about the user experience. They care about how performance impacts application usage and business metrics.

We talked to people in charge of application training, and they want to use APM tools to understand why a number of licenses are unused. Is it because the application is slow, or because people are not trained properly, or because the workflow is difficult to use?

In our survey, CIOs identified that their number one goal was to be able to invest more resources in innovation. Where APM fits into the CIO's agenda is to reduce the time and resources spent on maintaining IT services. Once you do that, you can allocate more resources in developing innovative services and create a competitive advantage.

APM: Do these multiple roles with different needs cause a challenge when purchasing an APM solution?

TRAC: Very often multiple job roles will be involved in the buying cycle. Capacity planning managers, developers, application support — and the companies are trying to get an APM solution that can support all of them, providing a value proposition across all the different job roles. But very often, what they end up buying is a solution that addresses only limited use cases.

APM: How do you view the increased importance of APM analytics?

TRAC: This is one of the key stories in the report. Analytics comes across most, if not all, sections of the report — anywhere from the APM overview to key challenges to best practices to recommendations.

One point is that 81% of organizations in the survey reported that the amount of APM data they collect increased over the last 12 months. That, by itself, shows that there is more data to be processed, the complexity is growing, and if you try to make sense out of the data manually you are setting yourself up for a task that is not humanly possible.

The survey also shows that only 16% of these organizations are able to proactively prevent issues in 80% of incidents or more. Many of them are using a number of different solutions that were never designed to work together, while trying to bring them all together and make sense out of this information. They need some technology in place to be able to analyze the data and bring it back to a single view.

In terms of usability, two key challenges were shown. One is the challenge of correlating and normalizing data collected from different sources. Second, is the amount of information that is not relevant to the problem you're trying to solve. I think the bottom line is that there is no correlation between the amount of information people have in the end, and their effectiveness in addressing key challenges. The fact that you can collect more information does not mean a whole lot unless you can process it, and present it back to people who are making decisions to prevent and resolve these issues.

APM: Your report says that virtualization is becoming another management silo. Why is that happening?

TRAC: Traditionally, we have two different types of solutions that are dealing with virtualization. You have virtualization management solutions that do a really good job talking about CPU utilization, availability and capacity. Most of these tools do not have any visibility into how actions on the virtualization management side impact the quality of the user experience for applications that are being virtualized.

Then you have user experience monitoring solutions that can do a good job telling you when you have a problem, but they don't have a lot of visibility into the actual infrastructure.

In the virtualization section of the study, we asked: what are the key challenges for managing application performance in virtualized environments? Number one was the inability to find the optimal balance between utilization and performance. If you are looking to manage a virtualization project with one goal in mind, to improve utilization, you need to know how it impacts the user experience. That is why virtualization is becoming a silo, because a lot of people don't have visibility into how their actions are impacting the end-user.

The number two challenge of virtualization management was lack of visibility into transaction flow, anywhere from the point where end-users interact with the application into the virtualized server. Having that kind of end-to-end visibility is critical, and not a lot of people have that.

Read Q&A Part Three: TRAC Research Talks About the APM Spectrum

Related Links:

Read Q&A Part One: TRAC Research Talks About the APM Spectrum

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For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

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Q&A Part Two: TRAC Research Talks About the APM Spectrum

Pete Goldin
APMdigest

In Part Two of APMdigest's exclusive interview, Bojan Simic, President and Principal Analyst at TRAC Research, talks about the firm's new APM Spectrum report, APM analytics, virtualization, and different types of APM for different job roles.

Start with Q&A Part One: TRAC Research Talks About the APM Spectrum

APM: Your report deals a lot with job roles. Did you see differences in expectations for APM solutions between IT operations and developers?

TRAC: We saw a major difference between IT operations versus developers, in terms of what they are looking to purchase. You can talk to developers and IT operations about the same exact tool and developers might say it is very effective, while IT operations will say it is too difficult for them to deploy in the workflow, and just not designed for what they are trying to do.

We asked developers and IT operations about their levels of satisfaction with the solutions that are currently being deployed. The data shows that developers are more likely to say that usability of data is pretty good. 59% of developers said they are satisfied, versus 40% of IT operations.

We also asked a question about the quality of user experience, and the numbers flip-flopped. 56% of IT operations said they were satisfied compared to only 39% of developers. Part of the reason is that some of the solutions being purchased by developers work really well in pre-production, but they are not as effective in production.

APM: So what is the solution? Do developers and IT operations always require separate tools?

TRAC: In some cases they could benefit from using two separate solutions. It really depends on the use case. A lot of it has to do with how they want to use the data they are collecting, whether it is one tool or multiple tools, and how the tool actually maps to what they're trying to do in production versus pre-production.

It goes back to what I mentioned before, it is not about selecting one solution that is going to take care of all your needs, user experience monitoring, transaction monitoring, infrastructure view — in many cases you need multiple products. What is important to know is: can these products work together?

One point that is important to mention, we asked the question in the survey about tools being used in pre-production only, production only, or both pre-production and production. 52% said APM tools are being used in production only. 10% are being used in pre-production only. 38% are being used in both. So on the developer side, you need to make sure the tool can also be effective in production. That is one of the recommendations that we have for developers in the study.

APM: Developer vs. IT ops is a fairly high profile example. Can you give some other examples of APM for specific job roles?

TRAC: We have seen quite a few people who purchase APM solutions, but they come from the business side, which IT is not even aware of. We are seeing almost a new class of APM deployments where IT is not even involved in the buying cycle. They might not even be aware it exists because the business side is buying APM for their purposes. Business users are becoming almost a separate submarket.

We are seeing more marketing folks being able to benefit from APM data if it is presented in the right way. They don't necessarily care about all the nuts and bolts of the technology, looking at packets and code, but they do care about the user experience. They care about how performance impacts application usage and business metrics.

We talked to people in charge of application training, and they want to use APM tools to understand why a number of licenses are unused. Is it because the application is slow, or because people are not trained properly, or because the workflow is difficult to use?

In our survey, CIOs identified that their number one goal was to be able to invest more resources in innovation. Where APM fits into the CIO's agenda is to reduce the time and resources spent on maintaining IT services. Once you do that, you can allocate more resources in developing innovative services and create a competitive advantage.

APM: Do these multiple roles with different needs cause a challenge when purchasing an APM solution?

TRAC: Very often multiple job roles will be involved in the buying cycle. Capacity planning managers, developers, application support — and the companies are trying to get an APM solution that can support all of them, providing a value proposition across all the different job roles. But very often, what they end up buying is a solution that addresses only limited use cases.

APM: How do you view the increased importance of APM analytics?

TRAC: This is one of the key stories in the report. Analytics comes across most, if not all, sections of the report — anywhere from the APM overview to key challenges to best practices to recommendations.

One point is that 81% of organizations in the survey reported that the amount of APM data they collect increased over the last 12 months. That, by itself, shows that there is more data to be processed, the complexity is growing, and if you try to make sense out of the data manually you are setting yourself up for a task that is not humanly possible.

The survey also shows that only 16% of these organizations are able to proactively prevent issues in 80% of incidents or more. Many of them are using a number of different solutions that were never designed to work together, while trying to bring them all together and make sense out of this information. They need some technology in place to be able to analyze the data and bring it back to a single view.

In terms of usability, two key challenges were shown. One is the challenge of correlating and normalizing data collected from different sources. Second, is the amount of information that is not relevant to the problem you're trying to solve. I think the bottom line is that there is no correlation between the amount of information people have in the end, and their effectiveness in addressing key challenges. The fact that you can collect more information does not mean a whole lot unless you can process it, and present it back to people who are making decisions to prevent and resolve these issues.

APM: Your report says that virtualization is becoming another management silo. Why is that happening?

TRAC: Traditionally, we have two different types of solutions that are dealing with virtualization. You have virtualization management solutions that do a really good job talking about CPU utilization, availability and capacity. Most of these tools do not have any visibility into how actions on the virtualization management side impact the quality of the user experience for applications that are being virtualized.

Then you have user experience monitoring solutions that can do a good job telling you when you have a problem, but they don't have a lot of visibility into the actual infrastructure.

In the virtualization section of the study, we asked: what are the key challenges for managing application performance in virtualized environments? Number one was the inability to find the optimal balance between utilization and performance. If you are looking to manage a virtualization project with one goal in mind, to improve utilization, you need to know how it impacts the user experience. That is why virtualization is becoming a silo, because a lot of people don't have visibility into how their actions are impacting the end-user.

The number two challenge of virtualization management was lack of visibility into transaction flow, anywhere from the point where end-users interact with the application into the virtualized server. Having that kind of end-to-end visibility is critical, and not a lot of people have that.

Read Q&A Part Three: TRAC Research Talks About the APM Spectrum

Related Links:

Read Q&A Part One: TRAC Research Talks About the APM Spectrum

Hot Topic
The Latest
The Latest 10

The Latest

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...