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Forrester Study Highlights Application Performance Challenges

Today's enterprises are powered by their applications, so ensuring those applications are available and performing well has become a key business initiative around the globe. However, this is easier said than done in the face of rapid IT change and innovation. Mobile users and devices, cloud-based infrastructures and applications, big data challenges, and the never-ending march of virtualization are all speed bumps along the road to successful and efficient IT and application delivery.  

In fact, it is so difficult to effectively manage application performance that a commissioned study conducted by Forrester Consulting on behalf of Riverbed found of 159 IT professionals with direct responsibility for business-critical applications, 54 percent of those surveyed are unable to resolve more than 25 percent of their problems in less than 24 hours. And 31 percent have experienced issues that persist for a month or more.

Not unsurprisingly, Forrester found that slow application performance has a strong impact on enterprise efficiency. Business user productivity takes the biggest hit, but IT productivity loss is not far behind. Almost two-thirds (65 percent) of IT operations groups surveyed regularly spend between 10 to 30 percent of their IT operational resources on unplanned or unscheduled tasks due to infrastructure and application issues.

The good news is that IT operation groups are turning to performance management solutions to help them address these issues. An overwhelming 80 percent believe that performance management tools are important or very important in managing application performance.

Unfortunately,it is not that simple. While many organizations have performance management solutions in place, these solutions are often not meeting their complete needs. Companies frequently have too many tools that report on different consoles with no data normalization or time alignment between them, making it impossible to gain a holistic view of the problem, or they lack complete coverage/visibility in their environment.

Image removed.

Forrester noted that organizations are looking for a number of improvements from their performance management solutions, including:

- Enabling better cooperation and collaboration between IT teams

- Providing a single console for data presentation and analysis

- Earlier, more proactive alerting

- Analytics and correlation for advanced root cause determination

- Real-time mapping of application dependencies on infrastructure

To the survey respondents, transaction mapping, the ability to describe all the components used in delivering a specific transaction, is the cornerstone of an integrated application monitoring strategy, but it needs to be complemented with data collected across all components of the application environment.

Image removed.

This is because application problems can happen anywhere — out at the end user device, on the network, inside the infrastructure or in the application code. IT operations and dev teams need a performance management solution that provides visibility across the entire application delivery environment. They need intelligence into the end-user experience, application transactions and code, and network performance to quickly diagnose root cause before the business is impacted.

Merging application performance management and application-aware network performance management capabilities in the same dashboard, and applying a common language of application-related intelligence like transaction analysis, can streamline the interaction between IT operations and development. This type of cooperation and collaboration leads to significantly reduced troubleshooting time, and connects dev teams with their production environments to assist in healthy and efficient application lifecycle management. 

ABOUT Heidi Gabrielson

Heidi Gabrielson is a Senior Product Marketing Manager for the Riverbed Performance Management business unit.

Related Links:

www.riverbed.com

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Forrester Study Highlights Application Performance Challenges

Today's enterprises are powered by their applications, so ensuring those applications are available and performing well has become a key business initiative around the globe. However, this is easier said than done in the face of rapid IT change and innovation. Mobile users and devices, cloud-based infrastructures and applications, big data challenges, and the never-ending march of virtualization are all speed bumps along the road to successful and efficient IT and application delivery.  

In fact, it is so difficult to effectively manage application performance that a commissioned study conducted by Forrester Consulting on behalf of Riverbed found of 159 IT professionals with direct responsibility for business-critical applications, 54 percent of those surveyed are unable to resolve more than 25 percent of their problems in less than 24 hours. And 31 percent have experienced issues that persist for a month or more.

Not unsurprisingly, Forrester found that slow application performance has a strong impact on enterprise efficiency. Business user productivity takes the biggest hit, but IT productivity loss is not far behind. Almost two-thirds (65 percent) of IT operations groups surveyed regularly spend between 10 to 30 percent of their IT operational resources on unplanned or unscheduled tasks due to infrastructure and application issues.

The good news is that IT operation groups are turning to performance management solutions to help them address these issues. An overwhelming 80 percent believe that performance management tools are important or very important in managing application performance.

Unfortunately,it is not that simple. While many organizations have performance management solutions in place, these solutions are often not meeting their complete needs. Companies frequently have too many tools that report on different consoles with no data normalization or time alignment between them, making it impossible to gain a holistic view of the problem, or they lack complete coverage/visibility in their environment.

Image removed.

Forrester noted that organizations are looking for a number of improvements from their performance management solutions, including:

- Enabling better cooperation and collaboration between IT teams

- Providing a single console for data presentation and analysis

- Earlier, more proactive alerting

- Analytics and correlation for advanced root cause determination

- Real-time mapping of application dependencies on infrastructure

To the survey respondents, transaction mapping, the ability to describe all the components used in delivering a specific transaction, is the cornerstone of an integrated application monitoring strategy, but it needs to be complemented with data collected across all components of the application environment.

Image removed.

This is because application problems can happen anywhere — out at the end user device, on the network, inside the infrastructure or in the application code. IT operations and dev teams need a performance management solution that provides visibility across the entire application delivery environment. They need intelligence into the end-user experience, application transactions and code, and network performance to quickly diagnose root cause before the business is impacted.

Merging application performance management and application-aware network performance management capabilities in the same dashboard, and applying a common language of application-related intelligence like transaction analysis, can streamline the interaction between IT operations and development. This type of cooperation and collaboration leads to significantly reduced troubleshooting time, and connects dev teams with their production environments to assist in healthy and efficient application lifecycle management. 

ABOUT Heidi Gabrielson

Heidi Gabrielson is a Senior Product Marketing Manager for the Riverbed Performance Management business unit.

Related Links:

www.riverbed.com

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.