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Compuware's Top 5 APM Predictions for 2013

Steve Tack

2013 will be another year of accelerated change in the Application Performance Management (APM) market, driven by two main forces.

First is the growing realization among C-level executives that highly performing applications have a direct impact on sales, productivity and customer satisfaction.

Second is the availability of a new generation of APM solutions which address the needs of modern-day application delivery processes and environments.

With this macro-context in mind, here are five key predictions for APM in 2013:

1. Increased Visibility Required Across the Application Delivery Chain

Today’s applications involve an increasingly complex set of services, delivered from within as well as beyond the four walls of your data center. These services include multi-tier application architectures, virtualized systems and an expanding mix of cloud and third-party services. The modern day data center is, essentially, without boundaries.

This means that optimizing the user experience, which is the only perspective that really counts for business-critical applications, will require broad and deep visibility across the delivery chain. Next year, the accelerating complexity at the edge of the internet, in the cloud and in the data center, will make managing your applications from the true end-user perspective all the more critical.

2. APM for Mobile Applications Will Industrialize

After years of hearing of the arrival of mobile commerce, the promise has been fulfilled this year, driven by tablet adoption. For both Thanksgiving Day and Black Friday, Compuware measured more than a 250 percent increase in the number of iPad page views when compared to 2011. Businesses realize that the revenue-generating potential of their customer-facing applications hinges on the ability to ensure strong performance across a widening range of mobile browsers and devices.

In addition, the Bring-Your-Own-Device (BYOD) movement places a premium on exceptional performance across diverse devices for internal productivity-enhancing applications.

In 2013, APM for mobile applications, both native and web, will mature from special project status to a core pillar of an APM practice.

3. Focus Shifts from Data Collection to Actionable, Automated Analytics

As monitoring becomes more pervasive and the amount of data increases, additional emphasis is being put on analysis. Businesses are seeing that it’s not enough to just collect more and more data regarding the performance of individual silos, and that an APM strategy needs to include performance analytics from the start. This includes the ability to automatically establish smart baselines, incorporate real-time and self-learning statistical analytics, and identify performance and availability anomalies without human intervention.

All stakeholders, including business owners, development, test and production teams, need rapid access to actionable information in order to find, fix and optimize performance to ensure applications meet business goals. As such, the demand for automated analytics, or “answer-focused APM,” will be on the rise in 2013.

4. DevOps and Agile Mandate a Lifecycle Approach to APM

Poorly performing applications in production can spell disaster for revenues and customer satisfaction. Buying a better “mouse trap” to capture problems once they reach production isn’t the way to go.

In 2013, we expect to see growing demand for a strong performance discipline that applies to the entire application lifecycle – from development, to testing, to production. We expect that the “DevOps” movement – which entails bringing together developers and operations teams early on, to prevent problems from reaching production in the first place – will continue to gain traction. The end-result will be improved time-to-market for production applications without sacrificing confidence in performance.

5. Big Data Initiatives Employ APM to Realize ROI

Big data has big potential, providing executives with a means to not just make better strategic decisions, but to also improve the critical, day-to-day decisions made at the front lines of business. Big data leverages a wealth of information in traditional databases as well as from the fast-growing new sources of digital data, including the web, biological and industrial sensors, video, e-mail and social network communications.

But extracting timely business insights depends in large part on the availability and speed of the big data environment. The reality is that Big Data applications and environments suffer from many of the performance challenges that plague current distributed applications, while adding new bottlenecks related to highly distributed processing of vast volumes of data, putting ROI from big data projects at risk. Poorly performing big data applications and environments can impact the business and revenues when customers complain or business analytics are delayed or unavailable. Increasingly, we believe APM will be used to help ensure the performance and availability of big data applications to meet business demands and satisfy users.

Conclusion

In summary, we believe in 2013, a new generation of APM will continue to gain traction. This approach will address the challenges of increased complexity along the complete application delivery path – from the data center, through the cloud, to end-user devices. It will provide the key insights needed to fix performance problems expeditiously, while helping businesses speed time-to-market for high-performing, production-ready applications. And, this new generation of APM will increasingly serve as a cornerstone for major IT initiatives like Big Data.

All in all, APM will continue its transformation from an IT toolkit to a C-suite imperative, underscoring customer satisfaction, employee productivity, revenues and profits.

Steve Tack is VP of Product Management, Compuware APM.

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Compuware's Top 5 APM Predictions for 2013

Steve Tack

2013 will be another year of accelerated change in the Application Performance Management (APM) market, driven by two main forces.

First is the growing realization among C-level executives that highly performing applications have a direct impact on sales, productivity and customer satisfaction.

Second is the availability of a new generation of APM solutions which address the needs of modern-day application delivery processes and environments.

With this macro-context in mind, here are five key predictions for APM in 2013:

1. Increased Visibility Required Across the Application Delivery Chain

Today’s applications involve an increasingly complex set of services, delivered from within as well as beyond the four walls of your data center. These services include multi-tier application architectures, virtualized systems and an expanding mix of cloud and third-party services. The modern day data center is, essentially, without boundaries.

This means that optimizing the user experience, which is the only perspective that really counts for business-critical applications, will require broad and deep visibility across the delivery chain. Next year, the accelerating complexity at the edge of the internet, in the cloud and in the data center, will make managing your applications from the true end-user perspective all the more critical.

2. APM for Mobile Applications Will Industrialize

After years of hearing of the arrival of mobile commerce, the promise has been fulfilled this year, driven by tablet adoption. For both Thanksgiving Day and Black Friday, Compuware measured more than a 250 percent increase in the number of iPad page views when compared to 2011. Businesses realize that the revenue-generating potential of their customer-facing applications hinges on the ability to ensure strong performance across a widening range of mobile browsers and devices.

In addition, the Bring-Your-Own-Device (BYOD) movement places a premium on exceptional performance across diverse devices for internal productivity-enhancing applications.

In 2013, APM for mobile applications, both native and web, will mature from special project status to a core pillar of an APM practice.

3. Focus Shifts from Data Collection to Actionable, Automated Analytics

As monitoring becomes more pervasive and the amount of data increases, additional emphasis is being put on analysis. Businesses are seeing that it’s not enough to just collect more and more data regarding the performance of individual silos, and that an APM strategy needs to include performance analytics from the start. This includes the ability to automatically establish smart baselines, incorporate real-time and self-learning statistical analytics, and identify performance and availability anomalies without human intervention.

All stakeholders, including business owners, development, test and production teams, need rapid access to actionable information in order to find, fix and optimize performance to ensure applications meet business goals. As such, the demand for automated analytics, or “answer-focused APM,” will be on the rise in 2013.

4. DevOps and Agile Mandate a Lifecycle Approach to APM

Poorly performing applications in production can spell disaster for revenues and customer satisfaction. Buying a better “mouse trap” to capture problems once they reach production isn’t the way to go.

In 2013, we expect to see growing demand for a strong performance discipline that applies to the entire application lifecycle – from development, to testing, to production. We expect that the “DevOps” movement – which entails bringing together developers and operations teams early on, to prevent problems from reaching production in the first place – will continue to gain traction. The end-result will be improved time-to-market for production applications without sacrificing confidence in performance.

5. Big Data Initiatives Employ APM to Realize ROI

Big data has big potential, providing executives with a means to not just make better strategic decisions, but to also improve the critical, day-to-day decisions made at the front lines of business. Big data leverages a wealth of information in traditional databases as well as from the fast-growing new sources of digital data, including the web, biological and industrial sensors, video, e-mail and social network communications.

But extracting timely business insights depends in large part on the availability and speed of the big data environment. The reality is that Big Data applications and environments suffer from many of the performance challenges that plague current distributed applications, while adding new bottlenecks related to highly distributed processing of vast volumes of data, putting ROI from big data projects at risk. Poorly performing big data applications and environments can impact the business and revenues when customers complain or business analytics are delayed or unavailable. Increasingly, we believe APM will be used to help ensure the performance and availability of big data applications to meet business demands and satisfy users.

Conclusion

In summary, we believe in 2013, a new generation of APM will continue to gain traction. This approach will address the challenges of increased complexity along the complete application delivery path – from the data center, through the cloud, to end-user devices. It will provide the key insights needed to fix performance problems expeditiously, while helping businesses speed time-to-market for high-performing, production-ready applications. And, this new generation of APM will increasingly serve as a cornerstone for major IT initiatives like Big Data.

All in all, APM will continue its transformation from an IT toolkit to a C-suite imperative, underscoring customer satisfaction, employee productivity, revenues and profits.

Steve Tack is VP of Product Management, Compuware APM.

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...