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Application Performance Equals Business Performance

Steve Riley

At the Interop conference in April 2014, Riverbed conducted a short survey to determine whether and how application performance problems might affect an organization’s business. 210 respondents answered questions about the performance of business-critical applications, non-critical applications, and productivity applications.

We asked participants to consider their experiences at main offices, branch offices, and remote situations and evaluate how each of the following contributed to performance problems:

■ branch office infrastructure issues

■ insufficient bandwidth

■ poor application coding techniques

■ slow servers

■ too much latency in the network

We asked participants to indicate how far along they might be on projects to mitigate performance problems and to rate the effectiveness of several techniques including:

■ add more bandwidth

■ build a branch-converged infrastructure

■ distribute workloads geographically

■ deploy faster endpoints

■ deploy faster servers

■ implement application delivery controllers

■ implement performance monitoring

■ implement WAN optimization

■ rewrite applications


The Results

80% of respondents indicated that slow business-critical applications negatively affect business performance. 71% indicated that slow access to productivity applications negatively affect business performance. The top three causes of performance problems were insufficient bandwidth, too much latency, and slow servers. From this, we can observe that modern business has come to rely on highly available, high quality connectivity, and the sense that applications and data behave as if they’re local. Individuals can no longer work in isolation, disconnected from their peers. Nor can they waste time waiting for the computer to “catch up.”

Turning to mitigation techniques, we can see a curious gap emerge. The three top-rated techniques were adding bandwidth at 70%, implementing WAN optimization at 67%, and distributing workloads geographically at 52%. In all cases, however, fewer respondents indicated that they were engaged in related projects. Only 50% have added bandwidth, only 42% have implemented WAN optimization, and only 28% have distributed workloads geographically.

It isn’t all that unusual, really, for action to lag awareness. It is interesting to consider the reasons why, though. Discovering the root causes of performance problems can be challenging at times. Users often blame only one aspect: “Hey, what’s wrong with the network? Why is it always soooo sloooow?” This is a common reaction even if all except one or two applications are performing acceptably. In reality, performance problems could exist anywhere in the technology stack — the network, the application, the database, or the “glue” layers holding everything together.

Recommendations

We recommend four simple yet critical steps to help avoid unnecessary slowness, to help keep applications performing at their peak, and to help maintain a consistent end-user experience.

1. Analyze, diagnose, and resolve performance problems first

Monitoring tools can identify chatty applications, slow servers, congested networks, and other kinds of resource exhaustion. An end-to-end view provides the most visibility. Monitoring entire transactions, rather than just particular points, can reveal true causes of performance problems.

2. Remember that electrons and photons have a speed limit

And that limit is 186,282 miles per second (only under perfect conditions, naturally). Increasing the distance between users and data can negatively affect performance. It takes time for data to scoot across a continent or even a city.

3. Distribute workloads geographically when it makes good business sense

A “follow the sun” model can be a useful guide. Deploy application delivery controllers to increase availability and connect users to the data that’s closest. Take advantage of global load balancing capabilities to route requests as locally as possible, while also providing planet-wide resiliency against failures.

4. Address latency, the primary cause of poor WAN performance

Deploy WAN optimizers to reduce the amount of data traversing the WAN and to reduce the number of connections between clients and servers. These techniques minimize the effects of latency, and — almost — make it seem as if data moves faster than light.

Steve Riley is Deputy CTO for Riverbed Technology.

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Application Performance Equals Business Performance

Steve Riley

At the Interop conference in April 2014, Riverbed conducted a short survey to determine whether and how application performance problems might affect an organization’s business. 210 respondents answered questions about the performance of business-critical applications, non-critical applications, and productivity applications.

We asked participants to consider their experiences at main offices, branch offices, and remote situations and evaluate how each of the following contributed to performance problems:

■ branch office infrastructure issues

■ insufficient bandwidth

■ poor application coding techniques

■ slow servers

■ too much latency in the network

We asked participants to indicate how far along they might be on projects to mitigate performance problems and to rate the effectiveness of several techniques including:

■ add more bandwidth

■ build a branch-converged infrastructure

■ distribute workloads geographically

■ deploy faster endpoints

■ deploy faster servers

■ implement application delivery controllers

■ implement performance monitoring

■ implement WAN optimization

■ rewrite applications


The Results

80% of respondents indicated that slow business-critical applications negatively affect business performance. 71% indicated that slow access to productivity applications negatively affect business performance. The top three causes of performance problems were insufficient bandwidth, too much latency, and slow servers. From this, we can observe that modern business has come to rely on highly available, high quality connectivity, and the sense that applications and data behave as if they’re local. Individuals can no longer work in isolation, disconnected from their peers. Nor can they waste time waiting for the computer to “catch up.”

Turning to mitigation techniques, we can see a curious gap emerge. The three top-rated techniques were adding bandwidth at 70%, implementing WAN optimization at 67%, and distributing workloads geographically at 52%. In all cases, however, fewer respondents indicated that they were engaged in related projects. Only 50% have added bandwidth, only 42% have implemented WAN optimization, and only 28% have distributed workloads geographically.

It isn’t all that unusual, really, for action to lag awareness. It is interesting to consider the reasons why, though. Discovering the root causes of performance problems can be challenging at times. Users often blame only one aspect: “Hey, what’s wrong with the network? Why is it always soooo sloooow?” This is a common reaction even if all except one or two applications are performing acceptably. In reality, performance problems could exist anywhere in the technology stack — the network, the application, the database, or the “glue” layers holding everything together.

Recommendations

We recommend four simple yet critical steps to help avoid unnecessary slowness, to help keep applications performing at their peak, and to help maintain a consistent end-user experience.

1. Analyze, diagnose, and resolve performance problems first

Monitoring tools can identify chatty applications, slow servers, congested networks, and other kinds of resource exhaustion. An end-to-end view provides the most visibility. Monitoring entire transactions, rather than just particular points, can reveal true causes of performance problems.

2. Remember that electrons and photons have a speed limit

And that limit is 186,282 miles per second (only under perfect conditions, naturally). Increasing the distance between users and data can negatively affect performance. It takes time for data to scoot across a continent or even a city.

3. Distribute workloads geographically when it makes good business sense

A “follow the sun” model can be a useful guide. Deploy application delivery controllers to increase availability and connect users to the data that’s closest. Take advantage of global load balancing capabilities to route requests as locally as possible, while also providing planet-wide resiliency against failures.

4. Address latency, the primary cause of poor WAN performance

Deploy WAN optimizers to reduce the amount of data traversing the WAN and to reduce the number of connections between clients and servers. These techniques minimize the effects of latency, and — almost — make it seem as if data moves faster than light.

Steve Riley is Deputy CTO for Riverbed Technology.

Hot Topics

The Latest

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 ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...