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Q&A Part One: EMA Talks About Advanced Performance Analytics

Pete Goldin
APMdigest

In APMdigest's exclusive interview, Dennis Drogseth, VP of Research at Enterprise Management Associates (EMA), talks about the APA market, and the recently released EMA Radar for Advanced Performance Analytics (APA) Use Cases: Q4 2012.

APM: Let's start be defining APA.

APA is about Big Data. Huge volumes of data coming out of what I would call the service performance management space – tools that have evolved to manage the performance of applications and other services. APA assimilates that Big Data in near real-time, and uses a lot of advanced heuristics to do predictive or least innovative ways of looking at problems.

APM: Are the capabilities to analyze Big Data, in real-time, and produce predictive results the 3 main defining characteristics that differentiate APA from traditional analytics?

DD: That's true, although I would add other potential attributes such as “self-learning” and “discovering the unobvious.”

But I can hear BI analysts saying that BI tools are evolving to deliver in real-time. All the 22 vendors in the APA Radar Report came out of performance management, they did not come out of the data warehousing. So the DNA is different. It is really a heritage statement, in part that requires Big Data, heuristics and some real-time, either predictive or strong analytic value add.

And APA is not limited to real-time either. Some of these solutions have very strong historical analytics. One even has its own internal OLAP cube. This is why a lot of analysts so far haven’t looked at APA. It is more of a biological thing – sort of how species evolve – than it is a lovely little mathematical definition.

APM: Do you consider APA as a subset of Application Performance Management (APM), or a totally separate market

DD: I would consider it separate but not totally separate. In APA, “A” stands for “advanced” not “application.” I am not saying there isn’t a strong overlap, but the two are not the same. You could make a case that APA is more accurately a subset of “service” performance.

The way I would define APM is certainly smaller than the span of APA. APA is more sprawling and more unruly than APM, in some respects. But there are a lot of APM capabilities that are not APA, such as basic monitoring. Maybe the best way to summarize is that I see APA as a child of APM and service management that will grow up to be bigger than they are in the future.

APM: It seems to me that you would almost have to have APA for APM, to make APM work today, to deal with Big Data and the other issues.

DD: To be competitive, yes. Not all of the 22 vendors in the Radar Report would claim to be APM, but for the ones who would, one of the factors that makes them more competitive is some APA capabilities. Yes, I would say it is a competitive differentiator for APM. But it is not limited to APM.

APM: Do users always buy APA separately or does it come with an APM solution?

DD: The goal of the radar is to show that APA can come in many different forms. In some cases, like Netuitive, it is primarily an overlay, and that general approach — to leverage APA by assimilating many different pre-existing data sources — is growing more and more. But in most cases, APA is part of a suite of solutions, many or most of which do some of their own monitoring, or can at least collect data directly.

APA: In your recent blog on APMdigest, you said “By Q4 of last year I realized that the industry was at an APA turning point.” What was the turning point?

DD: The turning point for me was when both IBM and HP introduced Netuitive-like functionality in Q4 of 2011. They introduced analytic overlays that would feed off third-party sources as well as their own solutions. And of course you could argue the same was true when ProactiveNet was acquired by BMC.

To tell you the truth, I have been watching Netuitive, along with other APA innovators, for years, and I have been waiting for the industry to move more in that direction. And in Q4 last year I saw the ship is beginning to sail – or at least it is leaving the dock.

APM: What has caused this new drive toward APA?

DD: That's a good question. What are the drivers? The need for more cross domain capabilities, for one. If you think about how performance management has evolved, it began with a lot of point solution tools. Niche tools. But unfortunately they were targeted at very narrow spans, and sometimes device specific. You can no longer run an IT organization based on a lot of siloed tools that only look at one domain in isolation.

The other driver is the increasing pressure for IT to become more efficient and deliver value as well as cost efficiencies to the business, which includes a much more enlightened summary of what is going on than was available in the past.

One of the factors that has sort of doomed the BSM acronym was its association with long, protracted, costly deployments that would take years to evolve. That is not how IT organizations can function anymore. So another driver is to have a much more dynamic, self-aware, self-learning capabilities.

Yet another driver for APA has been the need to manage more eclectic environments – thanks to Cloud computing. Cloud is often a mosaic of service provider infrastructures and internal IT infrastructures – Cloud and non-Cloud. How do you bring that all together and understand that from an effective, service-centric point of view?

Q&A Part Two: EMA Talks About Advanced Performance Analytics

Related Links:

EMA Releases New Radar Report on Advanced Performance Analytics

APMdigest Sponsors Featured in New EMA Radar Report on Advanced Performance Analytics

EMA's Dennis Drogseth Publishes New Novel

Click here to download the EMA Radar Report on Advanced Performance Analytics

View the EMA On-demand webinar- Advanced Performance Analytics (APA) Radar Report: Big Data with a New, Real-time Context

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Q&A Part One: EMA Talks About Advanced Performance Analytics

Pete Goldin
APMdigest

In APMdigest's exclusive interview, Dennis Drogseth, VP of Research at Enterprise Management Associates (EMA), talks about the APA market, and the recently released EMA Radar for Advanced Performance Analytics (APA) Use Cases: Q4 2012.

APM: Let's start be defining APA.

APA is about Big Data. Huge volumes of data coming out of what I would call the service performance management space – tools that have evolved to manage the performance of applications and other services. APA assimilates that Big Data in near real-time, and uses a lot of advanced heuristics to do predictive or least innovative ways of looking at problems.

APM: Are the capabilities to analyze Big Data, in real-time, and produce predictive results the 3 main defining characteristics that differentiate APA from traditional analytics?

DD: That's true, although I would add other potential attributes such as “self-learning” and “discovering the unobvious.”

But I can hear BI analysts saying that BI tools are evolving to deliver in real-time. All the 22 vendors in the APA Radar Report came out of performance management, they did not come out of the data warehousing. So the DNA is different. It is really a heritage statement, in part that requires Big Data, heuristics and some real-time, either predictive or strong analytic value add.

And APA is not limited to real-time either. Some of these solutions have very strong historical analytics. One even has its own internal OLAP cube. This is why a lot of analysts so far haven’t looked at APA. It is more of a biological thing – sort of how species evolve – than it is a lovely little mathematical definition.

APM: Do you consider APA as a subset of Application Performance Management (APM), or a totally separate market

DD: I would consider it separate but not totally separate. In APA, “A” stands for “advanced” not “application.” I am not saying there isn’t a strong overlap, but the two are not the same. You could make a case that APA is more accurately a subset of “service” performance.

The way I would define APM is certainly smaller than the span of APA. APA is more sprawling and more unruly than APM, in some respects. But there are a lot of APM capabilities that are not APA, such as basic monitoring. Maybe the best way to summarize is that I see APA as a child of APM and service management that will grow up to be bigger than they are in the future.

APM: It seems to me that you would almost have to have APA for APM, to make APM work today, to deal with Big Data and the other issues.

DD: To be competitive, yes. Not all of the 22 vendors in the Radar Report would claim to be APM, but for the ones who would, one of the factors that makes them more competitive is some APA capabilities. Yes, I would say it is a competitive differentiator for APM. But it is not limited to APM.

APM: Do users always buy APA separately or does it come with an APM solution?

DD: The goal of the radar is to show that APA can come in many different forms. In some cases, like Netuitive, it is primarily an overlay, and that general approach — to leverage APA by assimilating many different pre-existing data sources — is growing more and more. But in most cases, APA is part of a suite of solutions, many or most of which do some of their own monitoring, or can at least collect data directly.

APA: In your recent blog on APMdigest, you said “By Q4 of last year I realized that the industry was at an APA turning point.” What was the turning point?

DD: The turning point for me was when both IBM and HP introduced Netuitive-like functionality in Q4 of 2011. They introduced analytic overlays that would feed off third-party sources as well as their own solutions. And of course you could argue the same was true when ProactiveNet was acquired by BMC.

To tell you the truth, I have been watching Netuitive, along with other APA innovators, for years, and I have been waiting for the industry to move more in that direction. And in Q4 last year I saw the ship is beginning to sail – or at least it is leaving the dock.

APM: What has caused this new drive toward APA?

DD: That's a good question. What are the drivers? The need for more cross domain capabilities, for one. If you think about how performance management has evolved, it began with a lot of point solution tools. Niche tools. But unfortunately they were targeted at very narrow spans, and sometimes device specific. You can no longer run an IT organization based on a lot of siloed tools that only look at one domain in isolation.

The other driver is the increasing pressure for IT to become more efficient and deliver value as well as cost efficiencies to the business, which includes a much more enlightened summary of what is going on than was available in the past.

One of the factors that has sort of doomed the BSM acronym was its association with long, protracted, costly deployments that would take years to evolve. That is not how IT organizations can function anymore. So another driver is to have a much more dynamic, self-aware, self-learning capabilities.

Yet another driver for APA has been the need to manage more eclectic environments – thanks to Cloud computing. Cloud is often a mosaic of service provider infrastructures and internal IT infrastructures – Cloud and non-Cloud. How do you bring that all together and understand that from an effective, service-centric point of view?

Q&A Part Two: EMA Talks About Advanced Performance Analytics

Related Links:

EMA Releases New Radar Report on Advanced Performance Analytics

APMdigest Sponsors Featured in New EMA Radar Report on Advanced Performance Analytics

EMA's Dennis Drogseth Publishes New Novel

Click here to download the EMA Radar Report on Advanced Performance Analytics

View the EMA On-demand webinar- Advanced Performance Analytics (APA) Radar Report: Big Data with a New, Real-time Context

Hot Topic
The Latest
The Latest 10

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...