Skip to main content

Gartner Q&A: Jonah Kowall Talks About APM - Part 1

Pete Goldin
APMdigest

In Part 1 of APMdigest's exclusive interview, Jonah Kowall, Research Vice President, IT Operations Management at Gartner, discusses Gartner's 2013 Magic Quadrant for Application Performance Monitoring (APM), and APM hot topics including SaaS and Mobile.

APM: What do you see as the most significant changes in the market between the release of Gartner's 2012 and 2013 Magic Quadrants for APM?

JK: We have seen increased acceleration and investment by some of the smaller players in the space. In addition, the use of analytics technology has further differentiated offerings in the Application Performance Monitoring (APM) market.

And, of course, we have seen a greater importance on Software-as-a-Service (SaaS) delivery. We definitely see more end-user organizations implementing SaaS. I think that trend will continue, hence the relative weighting of SaaS and analytics will be increasing year over year for the APM Magic Quadrant.

APM: Is the growth of SaaS APM living up to the expectations many of us set for it a year or two ago?

JK: SaaS is not for everyone. It is definitely a subset of the market today. Solutions which offer differentiation because of the delivery model, or solutions which give you a choice of the same product in both delivery models, appeal more to buyers.

Additionally, SaaS helps shorten the buying cycle, meaning POCs can be executed much more efficiently, and customers can see value quickly, even if they decide longer-term that they may want to move on-premise.

APM: The requirements for Gartner's Magic Quadrant for APM continue to say "some features of the APM offering must be available via a SaaS delivery model" rather than requiring full feature SaaS. At some point, do you foresee the APM Magic Quadrant requiring every vendor to offer the full product as a service?

JK: We require that vendors have a least some functionality in SaaS. In 2012, we allowed a third party to provide the SaaS, and in 2013 we required that the vendors themselves provide SaaS.

Looking forward, we definitely do see most of the players in the APM Magic Quadrant offering more of their full solution as a service, so I wouldn't be surprised to see that requirement continue to expand.

APM: Do you have any stats on how much productivity can be increased by using APM SaaS?

JK: There have not been any studies conducted and I think that it would be hard to determine what that number is. It also depends on the complexity of the product.

Some solutions are very straightforward to implement, in terms of infrastructure requirements, meaning the server that collects the data from the agents. Other solutions can be more complex and require many components, especially at scale. It really varies on the vendor solution in terms of the complexity of the infrastructure requirements.

APM: But you do see an advantage to APM as a service?

Yes. There is no question upgrades may be painful. One area of complication is when customizations or integrations have been made with other products. By offering APM as a service, the customer is automatically upgraded without having to deal with the upgrade process. The agents are normally backwards compatible, but at least the user interface and functionality will remain current without putting in the extra work.

The other piece is that SaaS products integrate with well-formed APIs because they have been designed that way, since they are remotely delivered. When you have on-premise software, customization and integration often takes the form of either custom code or integrations that are not as well formed in terms of the APIs that are available.

SaaS providers have to keep some level of API compatibility in order for integration. That is definitely not the case with on-premise, and we have seen that be an issue with keeping customers on current revisions of software. If the software is not kept up to date, the customer eventually gets disgruntled with the fact that it doesn't support the new technologies or there are bugs that do not get fixed. It ultimately ends up reflecting poorly on the vendor, even if the solution, in its current version, fixes a lot of the issues that the users dislike. SaaS solves these issues.

APM: It seems like a lot of these productivity issues are maintenance oriented?

JK: Yes, it is the work that the ops guys need to do to keep current on the versions of the software. Enterprises often skip a major version of software and go to the next one. That is something we see a lot. For example, with Windows, many enterprises deployed Windows XP and then Windows 7, and skipped Windows Vista. We are seeing a lot of the same type of approach to APM. But the vendors don't expect enterprises to skip major versions. If you try to upgrade from version 5 to version 7, for example, it can cause problems because there is a pretty significant gap between those major versions.

APM: Your 2013 APM Magic Quadrant says "Mobile APM is the next wave of innovation" but it seems to be taking longer than we all expected.

JK: In 2013, we didn't really see mobile APM products that were actually giving “true APM”. We have had synthetic testing products that do mobile for quite a while, but that is a completely different value proposition from APM, which lives inside the application. So when I say "mobile APM", I am really talking about the same type of APM that looks inside applications, not the type of synthetic end user experience that just tries to emulate a user.

So even a year ago from today we just started to see early versions of true APM products for mobile coming out. This market has not been around very long. Solution providers typically have a revenue goal in mind when they release these products, and most of the mobile APM solutions out there exceeded any of the goals that were set.

APM: When do you feel Mobile APM will become truly mainstream, to the point where it drives the APM market?

JK: The demand is there because of the growth and diversity of mobile applications themselves. There are a lot of mobile apps out there, so it is going to take a while to actually proliferate through enough of the development organizations to be what I would call "mainstream". I would say that true Mobile APM is probably a couple of years off from being mainstream by any stretch of the imagination, but it is definitely growing in adoption and we are seeing new and interesting solutions coming to market.

Gartner Q&A: Jonah Kowall Talks About APM - Part 2

In Part 2, Jonah Kowall discusses Gartner's 2013 Magic Quadrant for Application Performance Monitoring (APM), complexity in today's product offerings, and the market's move to simplify APM.

Hot Topic
The Latest
The Latest 10

The Latest

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 ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

Gartner Q&A: Jonah Kowall Talks About APM - Part 1

Pete Goldin
APMdigest

In Part 1 of APMdigest's exclusive interview, Jonah Kowall, Research Vice President, IT Operations Management at Gartner, discusses Gartner's 2013 Magic Quadrant for Application Performance Monitoring (APM), and APM hot topics including SaaS and Mobile.

APM: What do you see as the most significant changes in the market between the release of Gartner's 2012 and 2013 Magic Quadrants for APM?

JK: We have seen increased acceleration and investment by some of the smaller players in the space. In addition, the use of analytics technology has further differentiated offerings in the Application Performance Monitoring (APM) market.

And, of course, we have seen a greater importance on Software-as-a-Service (SaaS) delivery. We definitely see more end-user organizations implementing SaaS. I think that trend will continue, hence the relative weighting of SaaS and analytics will be increasing year over year for the APM Magic Quadrant.

APM: Is the growth of SaaS APM living up to the expectations many of us set for it a year or two ago?

JK: SaaS is not for everyone. It is definitely a subset of the market today. Solutions which offer differentiation because of the delivery model, or solutions which give you a choice of the same product in both delivery models, appeal more to buyers.

Additionally, SaaS helps shorten the buying cycle, meaning POCs can be executed much more efficiently, and customers can see value quickly, even if they decide longer-term that they may want to move on-premise.

APM: The requirements for Gartner's Magic Quadrant for APM continue to say "some features of the APM offering must be available via a SaaS delivery model" rather than requiring full feature SaaS. At some point, do you foresee the APM Magic Quadrant requiring every vendor to offer the full product as a service?

JK: We require that vendors have a least some functionality in SaaS. In 2012, we allowed a third party to provide the SaaS, and in 2013 we required that the vendors themselves provide SaaS.

Looking forward, we definitely do see most of the players in the APM Magic Quadrant offering more of their full solution as a service, so I wouldn't be surprised to see that requirement continue to expand.

APM: Do you have any stats on how much productivity can be increased by using APM SaaS?

JK: There have not been any studies conducted and I think that it would be hard to determine what that number is. It also depends on the complexity of the product.

Some solutions are very straightforward to implement, in terms of infrastructure requirements, meaning the server that collects the data from the agents. Other solutions can be more complex and require many components, especially at scale. It really varies on the vendor solution in terms of the complexity of the infrastructure requirements.

APM: But you do see an advantage to APM as a service?

Yes. There is no question upgrades may be painful. One area of complication is when customizations or integrations have been made with other products. By offering APM as a service, the customer is automatically upgraded without having to deal with the upgrade process. The agents are normally backwards compatible, but at least the user interface and functionality will remain current without putting in the extra work.

The other piece is that SaaS products integrate with well-formed APIs because they have been designed that way, since they are remotely delivered. When you have on-premise software, customization and integration often takes the form of either custom code or integrations that are not as well formed in terms of the APIs that are available.

SaaS providers have to keep some level of API compatibility in order for integration. That is definitely not the case with on-premise, and we have seen that be an issue with keeping customers on current revisions of software. If the software is not kept up to date, the customer eventually gets disgruntled with the fact that it doesn't support the new technologies or there are bugs that do not get fixed. It ultimately ends up reflecting poorly on the vendor, even if the solution, in its current version, fixes a lot of the issues that the users dislike. SaaS solves these issues.

APM: It seems like a lot of these productivity issues are maintenance oriented?

JK: Yes, it is the work that the ops guys need to do to keep current on the versions of the software. Enterprises often skip a major version of software and go to the next one. That is something we see a lot. For example, with Windows, many enterprises deployed Windows XP and then Windows 7, and skipped Windows Vista. We are seeing a lot of the same type of approach to APM. But the vendors don't expect enterprises to skip major versions. If you try to upgrade from version 5 to version 7, for example, it can cause problems because there is a pretty significant gap between those major versions.

APM: Your 2013 APM Magic Quadrant says "Mobile APM is the next wave of innovation" but it seems to be taking longer than we all expected.

JK: In 2013, we didn't really see mobile APM products that were actually giving “true APM”. We have had synthetic testing products that do mobile for quite a while, but that is a completely different value proposition from APM, which lives inside the application. So when I say "mobile APM", I am really talking about the same type of APM that looks inside applications, not the type of synthetic end user experience that just tries to emulate a user.

So even a year ago from today we just started to see early versions of true APM products for mobile coming out. This market has not been around very long. Solution providers typically have a revenue goal in mind when they release these products, and most of the mobile APM solutions out there exceeded any of the goals that were set.

APM: When do you feel Mobile APM will become truly mainstream, to the point where it drives the APM market?

JK: The demand is there because of the growth and diversity of mobile applications themselves. There are a lot of mobile apps out there, so it is going to take a while to actually proliferate through enough of the development organizations to be what I would call "mainstream". I would say that true Mobile APM is probably a couple of years off from being mainstream by any stretch of the imagination, but it is definitely growing in adoption and we are seeing new and interesting solutions coming to market.

Gartner Q&A: Jonah Kowall Talks About APM - Part 2

In Part 2, Jonah Kowall discusses Gartner's 2013 Magic Quadrant for Application Performance Monitoring (APM), complexity in today's product offerings, and the market's move to simplify APM.

Hot Topic
The Latest
The Latest 10

The Latest

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 ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...