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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

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

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The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ...