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Waste Not, Want Not - Raising VDI Performance at the Endpoint

Jeff Kalberg

A recent story in APMdigest revealed the amount of operational waste enterprises are experiencing as IT devotes significantly more time to performance issues related to digital transformation initiatives. The research study detailed in the story finds that IT professionals are losing over 2 hours every business day, or 522 hours per year. Study respondents noted a more complex technology environment was a leading culprit in these performance issues.

Complex technology isn't going away. In fact, more than likely, digital transformation will continue to add technical complexity. One area that enables enterprises to reduce complexity and streamline operations is their virtual desktop infrastructure (VDI). Virtualization is a linchpin of digital transformation and effectively optimizing an enterprise's VDI is essential to moving forward with digital technologies.

Delivering the best possible VDI performance means taking a fresh look at what "desktop" means today. The endpoint, or desktop, now can be a physical thin client, a software-defined thin client, a traditional laptop, a phone or tablet.

To reduce operational waste and achieve better performance across the desktop environment, consider these five actions:

1. Accommodating Self-Serve Access

Employees should be able to access certain applications without having to contact an IT help desk. Enabling "self-serve" application access, as appropriate, allows employees to access their personal desktop workspaces, and needed applications, without using valuable IT time.

However, there is a flip side to this: IT needs to control how far employees can take self-service. If employees are spending too much time onboarding more advanced applications, and less time being work-productive, then those applications may need to be controlled by IT.

2. Paying Attention to the Edge

Using centralized management software, IT can control and manage edge devices' use of applications residing in the data center.

For example, software managing thin clients can retrieve a user profile and populate the endpoint with applications that a user needs to be productive. This centralized approach can result in the economies of a single IT person managing as many as 30,000 endpoints – a great reduction in IT time and resources.

3. Thinking Software, not Hardware

Enterprises are moving away from endpoint hardware investments to software that supports the pace of digital transformation. Improving endpoint performance means being able to quickly onboard new employees, deliver custom configurations to a remote workforce using a variety of devices, and to quickly populate new applications for ready use. Endpoint software such as thin client firmware is a means of delivering profiles and applications via a single pane of glass, regardless of device.

4. Understanding User Expectations

Your average worker today wants to use many devices, with the expectation the device will deliver what they need to do their job. The "desktop" of today can range from software-driven thin clients to USB devices. Endpoint management must be able to manage all these devices, control application access and mitigate security risk. It is challenging since, for example, there are many versions of Android and iOS in use, with the threat that users are loading up applications that can pose risk to the network.

USB devices pose one solution, freeing the user from physical boundaries, yet delivering the desired level of endpoint security. A new employee, for example, can plug the device into their personal laptop, and securely receive the configuration and applications they need, without IT ever having to touch the device.

Enterprises are searching for these types of solutions that deliver an optimal user experience without adding to operational complexity.

5. Looking at the Bigger Picture

Getting ahead of digital transformation technology needs, and advancements, is critical to winning the digital game. The alternative is never really catching up with technology and being overwhelmed by the complex IT environments that are becoming standard today.

In the study of operational waste, IT professionals said, if they could reclaim those two hours a day, they would spend more time researching and deploying new systems/technologies.

Staying up to speed on virtualization technology is essential to digital transformation succeeding. Companiesmare innovating technology that plays right into the enablement of high VDI performance. Remote display technology that accommodates workers using graphics intensive applications is an example of delivering innovation that users expect. Freeing up IT time to continue to integrate these enhancements in the user experience has to be part of a thorough digital transformation.

Conclusion: Move Digital Transformation Forward with Optimized VDI

Enterprises are grappling with the challenges of digital transformation, from figuring out cloud deployment, data storage, and BYOD security threats to how to deliver an endpoint experience that optimizes performance.

These five actions will help IT deliver VDI performance that supports digital transformation initiatives. Improvements such as enabling workers to be more self-sufficient, and streamlining endpoint management will reduce operational waste, reduce both operational and capital expenditures, and maps to the market trend toward centralized endpoint management software that can accommodate a variety of devices.

Freeing up IT time will allow IT to better plan for more integration of digital technologies which in turn, increases the enterprise's competitive strength. After all, this is the purpose of digital transformation!

The Latest

Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

 

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...

If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

Waste Not, Want Not - Raising VDI Performance at the Endpoint

Jeff Kalberg

A recent story in APMdigest revealed the amount of operational waste enterprises are experiencing as IT devotes significantly more time to performance issues related to digital transformation initiatives. The research study detailed in the story finds that IT professionals are losing over 2 hours every business day, or 522 hours per year. Study respondents noted a more complex technology environment was a leading culprit in these performance issues.

Complex technology isn't going away. In fact, more than likely, digital transformation will continue to add technical complexity. One area that enables enterprises to reduce complexity and streamline operations is their virtual desktop infrastructure (VDI). Virtualization is a linchpin of digital transformation and effectively optimizing an enterprise's VDI is essential to moving forward with digital technologies.

Delivering the best possible VDI performance means taking a fresh look at what "desktop" means today. The endpoint, or desktop, now can be a physical thin client, a software-defined thin client, a traditional laptop, a phone or tablet.

To reduce operational waste and achieve better performance across the desktop environment, consider these five actions:

1. Accommodating Self-Serve Access

Employees should be able to access certain applications without having to contact an IT help desk. Enabling "self-serve" application access, as appropriate, allows employees to access their personal desktop workspaces, and needed applications, without using valuable IT time.

However, there is a flip side to this: IT needs to control how far employees can take self-service. If employees are spending too much time onboarding more advanced applications, and less time being work-productive, then those applications may need to be controlled by IT.

2. Paying Attention to the Edge

Using centralized management software, IT can control and manage edge devices' use of applications residing in the data center.

For example, software managing thin clients can retrieve a user profile and populate the endpoint with applications that a user needs to be productive. This centralized approach can result in the economies of a single IT person managing as many as 30,000 endpoints – a great reduction in IT time and resources.

3. Thinking Software, not Hardware

Enterprises are moving away from endpoint hardware investments to software that supports the pace of digital transformation. Improving endpoint performance means being able to quickly onboard new employees, deliver custom configurations to a remote workforce using a variety of devices, and to quickly populate new applications for ready use. Endpoint software such as thin client firmware is a means of delivering profiles and applications via a single pane of glass, regardless of device.

4. Understanding User Expectations

Your average worker today wants to use many devices, with the expectation the device will deliver what they need to do their job. The "desktop" of today can range from software-driven thin clients to USB devices. Endpoint management must be able to manage all these devices, control application access and mitigate security risk. It is challenging since, for example, there are many versions of Android and iOS in use, with the threat that users are loading up applications that can pose risk to the network.

USB devices pose one solution, freeing the user from physical boundaries, yet delivering the desired level of endpoint security. A new employee, for example, can plug the device into their personal laptop, and securely receive the configuration and applications they need, without IT ever having to touch the device.

Enterprises are searching for these types of solutions that deliver an optimal user experience without adding to operational complexity.

5. Looking at the Bigger Picture

Getting ahead of digital transformation technology needs, and advancements, is critical to winning the digital game. The alternative is never really catching up with technology and being overwhelmed by the complex IT environments that are becoming standard today.

In the study of operational waste, IT professionals said, if they could reclaim those two hours a day, they would spend more time researching and deploying new systems/technologies.

Staying up to speed on virtualization technology is essential to digital transformation succeeding. Companiesmare innovating technology that plays right into the enablement of high VDI performance. Remote display technology that accommodates workers using graphics intensive applications is an example of delivering innovation that users expect. Freeing up IT time to continue to integrate these enhancements in the user experience has to be part of a thorough digital transformation.

Conclusion: Move Digital Transformation Forward with Optimized VDI

Enterprises are grappling with the challenges of digital transformation, from figuring out cloud deployment, data storage, and BYOD security threats to how to deliver an endpoint experience that optimizes performance.

These five actions will help IT deliver VDI performance that supports digital transformation initiatives. Improvements such as enabling workers to be more self-sufficient, and streamlining endpoint management will reduce operational waste, reduce both operational and capital expenditures, and maps to the market trend toward centralized endpoint management software that can accommodate a variety of devices.

Freeing up IT time will allow IT to better plan for more integration of digital technologies which in turn, increases the enterprise's competitive strength. After all, this is the purpose of digital transformation!

The Latest

Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

 

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...

If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ...