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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

FinOps champions crucial cross-departmental collaboration, uniting business, finance, technology and engineering leaders to demystify cloud expenses. Yet, too often, critical cost issues are softened into mere "recommendations" or "insights" — easy to ignore. But what if we adopted security's battle-tested strategy and reframed these as the urgent risks they truly are, demanding immediate action? ...

Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...

While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...

A perfect storm is brewing in cybersecurity — certificate lifespans shrinking to just 47 days while quantum computing threatens today's encryption. Organizations must embrace ephemeral trust and crypto-agility to survive this dual challenge ...

In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...