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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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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

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...