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Finding Your Organization’s Blind Spots

Steve Tack

How a Lifecycle Approach to APM Improves User Experience, Business Transaction Performance and Ultimately Revenues

Imagine it's Black Friday, when all of the sudden … boom! Your most critical Web application goes awry, bringing your e-commerce operation to a screeching halt on the very day flawless performance is needed most.

According to industry research cited in a Quocirca report titled “2012: The Year of Application Performance Management (APM)” a two second slowdown in response time is estimated to equal about four percent of revenue loss per visitor to an e-commerce site. So your organization probably doesn't have a lot of time to scramble to find out what is going wrong. You need to find answers – actionable information – and you need it fast.

The challenge to expeditious resolution is cutting through the vast amount of complexity that organizations are faced with today. First, there's the complexity involved in modern application delivery which is growing immensely. With applications increasingly pulling content from third-party services, and the advent of external infrastructures like the cloud, there are so many blind spots in the application delivery chain. Pinpointing the precise cause of application performance degradations can be tremendously difficult.

Second, there's the complexity that exists within organizations themselves, with so many stakeholders in application performance including developers, testers (QA), operations and line of business executives. Often, these groups are all speaking different business “languages” and concerned with different business goals.

For instance, developers speak in terms of debugging application code and don't want anything to impede their progress as they swiftly push out new products and enhancements. Operations, who wants to keep things as reliable and stable as possible, is quick to say “I told you so” whenever a problem arises. For their part, line of business speaks in numbers and they just want to know how conversions and revenues are being impacted – and when the bloodletting will stop!

This is a big mess which often results in a lot of wasted time, lack of meaningful communication and finger-pointing. One thing's for sure, “speed matters” – both in terms of actual application speed, as well as the speed at which performance problems are found, prioritized, addressed and fixed. Organizations desperately need a way to simplify all this complexity.

By now, you've more than likely heard the term DevOps, which entails bringing together developers and operations – both the pre-production and the production sides of the house. The goal is to aid in the release process, satisfying developers' requirements for speed while addressing operations' needs for stability. A key cornerstone of the DevOps movement is to commit to ongoing performance management and testing at all stages of an application lifecycle, from the earliest stages of development, to prevent problems from reaching production.

We at Compuware like to call this a lifecycle approach to performance management, since this term extends to include line of business executives. In order to successfully achieve a lifecycle approach, the proper type of APM system must be in place. First and foremost, this system must understand, from the user perspective, how applications and websites are performing. Achieving this level of insight requires monitoring of applications to go beyond the data center and start with the user perspective.

In addition, the proper type of APM system must:

- Deliver an integrated environment across stakeholders, to eliminate time spent correlating between different tools and to enable a common language of understanding. What applications are performing poorly? Why and whose problem is it? What's the impact on conversions?

- Provide automated, continuous visibility into what's going on – user behaviors, business transactions, conversion rates, etc.

- Offer actionable information for various stakeholders.

- Be application-centric as opposed to component-centric, which doesn't offer an overall view into how vital applications are performing. Additionally, be business aware, connecting IT to line of business by showing, for example, how IT is impacting the end- user experience and revenue.

In summary, it's important to remember that even the supposedly best application is never complete. Gartner estimates that only eight percent of an application's total cost of ownership (TCO) can be attributed to building, while the other 92 percent goes to ongoing enhancements, fixes and optimizationsi. A lifecycle approach to performance management, based on the right kind of APM solution, can help organizations navigate the vast complexity, ensure the strongest performing applications and make the best decisions that drive the user experience and revenues.

Steve Tack is VP of Product Management, Compuware APM.

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Finding Your Organization’s Blind Spots

Steve Tack

How a Lifecycle Approach to APM Improves User Experience, Business Transaction Performance and Ultimately Revenues

Imagine it's Black Friday, when all of the sudden … boom! Your most critical Web application goes awry, bringing your e-commerce operation to a screeching halt on the very day flawless performance is needed most.

According to industry research cited in a Quocirca report titled “2012: The Year of Application Performance Management (APM)” a two second slowdown in response time is estimated to equal about four percent of revenue loss per visitor to an e-commerce site. So your organization probably doesn't have a lot of time to scramble to find out what is going wrong. You need to find answers – actionable information – and you need it fast.

The challenge to expeditious resolution is cutting through the vast amount of complexity that organizations are faced with today. First, there's the complexity involved in modern application delivery which is growing immensely. With applications increasingly pulling content from third-party services, and the advent of external infrastructures like the cloud, there are so many blind spots in the application delivery chain. Pinpointing the precise cause of application performance degradations can be tremendously difficult.

Second, there's the complexity that exists within organizations themselves, with so many stakeholders in application performance including developers, testers (QA), operations and line of business executives. Often, these groups are all speaking different business “languages” and concerned with different business goals.

For instance, developers speak in terms of debugging application code and don't want anything to impede their progress as they swiftly push out new products and enhancements. Operations, who wants to keep things as reliable and stable as possible, is quick to say “I told you so” whenever a problem arises. For their part, line of business speaks in numbers and they just want to know how conversions and revenues are being impacted – and when the bloodletting will stop!

This is a big mess which often results in a lot of wasted time, lack of meaningful communication and finger-pointing. One thing's for sure, “speed matters” – both in terms of actual application speed, as well as the speed at which performance problems are found, prioritized, addressed and fixed. Organizations desperately need a way to simplify all this complexity.

By now, you've more than likely heard the term DevOps, which entails bringing together developers and operations – both the pre-production and the production sides of the house. The goal is to aid in the release process, satisfying developers' requirements for speed while addressing operations' needs for stability. A key cornerstone of the DevOps movement is to commit to ongoing performance management and testing at all stages of an application lifecycle, from the earliest stages of development, to prevent problems from reaching production.

We at Compuware like to call this a lifecycle approach to performance management, since this term extends to include line of business executives. In order to successfully achieve a lifecycle approach, the proper type of APM system must be in place. First and foremost, this system must understand, from the user perspective, how applications and websites are performing. Achieving this level of insight requires monitoring of applications to go beyond the data center and start with the user perspective.

In addition, the proper type of APM system must:

- Deliver an integrated environment across stakeholders, to eliminate time spent correlating between different tools and to enable a common language of understanding. What applications are performing poorly? Why and whose problem is it? What's the impact on conversions?

- Provide automated, continuous visibility into what's going on – user behaviors, business transactions, conversion rates, etc.

- Offer actionable information for various stakeholders.

- Be application-centric as opposed to component-centric, which doesn't offer an overall view into how vital applications are performing. Additionally, be business aware, connecting IT to line of business by showing, for example, how IT is impacting the end- user experience and revenue.

In summary, it's important to remember that even the supposedly best application is never complete. Gartner estimates that only eight percent of an application's total cost of ownership (TCO) can be attributed to building, while the other 92 percent goes to ongoing enhancements, fixes and optimizationsi. A lifecycle approach to performance management, based on the right kind of APM solution, can help organizations navigate the vast complexity, ensure the strongest performing applications and make the best decisions that drive the user experience and revenues.

Steve Tack is VP of Product Management, Compuware APM.

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Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

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Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

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