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Application Performance: A Hidden Cost of Cloud Computing

In December 2012, Research in Action (on behalf of Compuware) conducted a survey of 468 CIOs and other senior IT professionals from around the world. The survey determined cloud computing to be the top IT investment priority for 2013. No surprises there, as clearly these professionals are being driven by the promised benefits of greater agility, flexibility and time-to-value.

What is surprising is the fact that 79 percent of these professionals expressed concern over the hidden costs of cloud computing, with poor end-user experience resonating as the biggest management worry.

According to the survey, here are the four leading concerns with cloud migration:

- Performance Bottlenecks: (64%) Respondents believe that cloud resources and e-commerce will experience poor performance due to cloud application bottleneck usage.

- Poor End-User Experience: (64%) End users may end up dissatisfied with the cloud performance due to heavy traffic from application usage.

- Reduced Brand Perception: (51%) Customer loyalty may be greatly reduced due to poor experience and poor cloud performance.

- Loss of Revenue: (44%) Companies may lose revenues as a result of poor performance, reduced availability or slow technical troubleshooting services.

Ironically, these responses come at a time when the cloud is increasingly being used to support mission-critical applications like e-commerce. More than 80 percent of the professionals surveyed are either already using cloud-based e-commerce platforms or are planning to do so within the next 12 months.

It used to be that issues like security and cost dominated the list of cloud concerns. But application performance is increasingly making headway as end users grow more demanding. For the average end user, 0.1 seconds is an instantaneous, acceptable response, similar to what they experience with a Google search. As response times increase, interactions begin to slow and dissatisfaction rises.

The impact of a slowdown can be devastating: Amazon has calculated that a page load slowdown of just one second could cost it $1.6 billion in sales each year. In addition, Google itself found that slowing search response times by just four-tenths of a second would reduce the number of searches by eight million per day – a sizeable amount.

Inherent cloud attributes like on-demand resource provisioning and scalability are designed to increase confidence in the usability of applications and data hosted in the cloud. But the most common mistake that people often make is interpreting availability guarantees as performance guarantees in a cloud computing environment.

Availability shows that a cloud service provider’s servers are up and running – but that’s about it. Service-level agreements (SLAs) based on availability say nothing about the end-user experience, which can be significantly impacted by the cloud – such as, when an organization’s “neighbor” in the cloud experiences an unexpected spike in traffic.

Yet, despite the business critical nature of many cloud applications, our survey found that 73 percent of companies are still using outdated methods like availability measurements to track and manage application performance.

The fact is that most traditional monitoring tools simply don’t work in the cloud. Effectively monitoring and managing modern cloud-based applications and services requires a new approach based on more granular end-user metrics such as response time and page rendering time. This approach must be based in an understanding of the true end-user interaction “on the other side” of the cloud. It must enable cloud customers to directly measure the performance of their cloud service providers and validate SLAs. With this type of approach, cloud customers can be better assured that application performance issues will not undo the benefits of moving to the cloud.

ABOUT Michael Kopp

Michael Kopp is Technology Strategist, Compuware APM Center of Excellence. He has more than 10 years of experience as an architect and developer. Additionally, Kopp specializes in architecture and performance of Big Data and Cloud environments.

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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 ...

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Application Performance: A Hidden Cost of Cloud Computing

In December 2012, Research in Action (on behalf of Compuware) conducted a survey of 468 CIOs and other senior IT professionals from around the world. The survey determined cloud computing to be the top IT investment priority for 2013. No surprises there, as clearly these professionals are being driven by the promised benefits of greater agility, flexibility and time-to-value.

What is surprising is the fact that 79 percent of these professionals expressed concern over the hidden costs of cloud computing, with poor end-user experience resonating as the biggest management worry.

According to the survey, here are the four leading concerns with cloud migration:

- Performance Bottlenecks: (64%) Respondents believe that cloud resources and e-commerce will experience poor performance due to cloud application bottleneck usage.

- Poor End-User Experience: (64%) End users may end up dissatisfied with the cloud performance due to heavy traffic from application usage.

- Reduced Brand Perception: (51%) Customer loyalty may be greatly reduced due to poor experience and poor cloud performance.

- Loss of Revenue: (44%) Companies may lose revenues as a result of poor performance, reduced availability or slow technical troubleshooting services.

Ironically, these responses come at a time when the cloud is increasingly being used to support mission-critical applications like e-commerce. More than 80 percent of the professionals surveyed are either already using cloud-based e-commerce platforms or are planning to do so within the next 12 months.

It used to be that issues like security and cost dominated the list of cloud concerns. But application performance is increasingly making headway as end users grow more demanding. For the average end user, 0.1 seconds is an instantaneous, acceptable response, similar to what they experience with a Google search. As response times increase, interactions begin to slow and dissatisfaction rises.

The impact of a slowdown can be devastating: Amazon has calculated that a page load slowdown of just one second could cost it $1.6 billion in sales each year. In addition, Google itself found that slowing search response times by just four-tenths of a second would reduce the number of searches by eight million per day – a sizeable amount.

Inherent cloud attributes like on-demand resource provisioning and scalability are designed to increase confidence in the usability of applications and data hosted in the cloud. But the most common mistake that people often make is interpreting availability guarantees as performance guarantees in a cloud computing environment.

Availability shows that a cloud service provider’s servers are up and running – but that’s about it. Service-level agreements (SLAs) based on availability say nothing about the end-user experience, which can be significantly impacted by the cloud – such as, when an organization’s “neighbor” in the cloud experiences an unexpected spike in traffic.

Yet, despite the business critical nature of many cloud applications, our survey found that 73 percent of companies are still using outdated methods like availability measurements to track and manage application performance.

The fact is that most traditional monitoring tools simply don’t work in the cloud. Effectively monitoring and managing modern cloud-based applications and services requires a new approach based on more granular end-user metrics such as response time and page rendering time. This approach must be based in an understanding of the true end-user interaction “on the other side” of the cloud. It must enable cloud customers to directly measure the performance of their cloud service providers and validate SLAs. With this type of approach, cloud customers can be better assured that application performance issues will not undo the benefits of moving to the cloud.

ABOUT Michael Kopp

Michael Kopp is Technology Strategist, Compuware APM Center of Excellence. He has more than 10 years of experience as an architect and developer. Additionally, Kopp specializes in architecture and performance of Big Data and Cloud environments.

Hot Topics

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.