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3 Ways to Improve Azure Virtual Desktop Performance

Amol Dalvi
Nerdio

As remote work becomes a standard business practice, virtual desktops continue to gain popularity as a primary means of delivering data and applications to end users. Azure Virtual Desktop (AVD), for example, is seeing strong adoption due to its ease of deployment and its portal which enables desktop and application management from one interface. Enterprises can also control costs since they pay for virtual servers only when desktops are running, and can scale in or out depending on desktop needs. A recent survey indicated over half of the respondents (58%) expected to have AVD technology in production within two years.

Like many emerging platforms, AVD is still in its early days and IT pros are evolving, as well, in their approach to deploying and managing the service. The platform is seeing strong traction among SMB market enterprises of less than 1,000 users who like the scalability and related cost control features.

While AVD is gaining traction, IT teams are looking for ways to better deliver application performance and satisfy the end user's expectations of seamless productivity. The survey found the two biggest complaints from IT pros are slow application performance (47%) and slow logons (40%). Supporting video calls, more efficient monitoring of all AVD elements and solving latency problems are among other key issues.

Stepping Up Virtual Machine Performance

End users are on the front lines of experiencing sluggish virtual desktop performance. If it takes what feels like forever to do a simple task like opening up Word or Excel, IT will get unwanted help desk calls. For example, if your end users in a specific department are running intensive workloads, such as graphic design, confirm they are getting the right number of resources in terms of virtual machine (VM) compute power by having the optimum number of users in any one AVD host pool.

Microsoft has a guide for sizing session host VMs that makes a good point that IT needs to continually monitor VM usage, sizing up and down accordingly. If there are no graphics processing units (GPU) or graphics-intensive workloads, it is also recommended to stay with smaller VMs since they can be more easily updated — another performance related practice. With fewer users on one VM, it is more likely IT will find no one signed on and can shut it down to make updates as necessary if they are manually managing the environment.

Accommodating Multi-Media Environments

Zoom, Teams, intensive graphics use, and eventually more metaverse style collaboration, are all driving more performance concerns about latency, cloud costs, and the ability to provide an end user experience expected by Gen Z and Gen Y workers.

Stop-and-start video screens, too long video downloads; these are some examples in which latency detracts from performance. Since so many meetings are now video conferencing it's a good practice to run load and stress scenarios to ensure the remote desktop session will have adequate bandwidth to provide a satisfying experience.

Latency and quality of multimedia transmission is also affected by the connection round trip time (RTT) from the current location, through the AVD service to the Azure region in which IT can deploy VMs. Check AVD's estimator to determine the lowest RTT relevant to your users' location and make session host adjustments as needed.

Lastly, consider GPUs for better performance in video, 3D design and other graphics applications. AVD GPU virtual machines will enable graphics accelerated rendering and help AVD end users be more efficient and productive.

Monitoring all Performance Aspects

Improving AVD performance, or for that matter, any critical platform, depends on diligent monitoring. AVD offers native tools for monitoring and there are also third-party options to enhance monitoring and management. According to the survey, almost half of the IT pros say they need end-to-end monitoring that includes session hosts, control plane and Azure AD.

Further efficiency can be gained by using tools with a central dashboard that can record and analyze data in usage, active users, session host, CPUs, and other metrics to view performance and potentially identify cost savings. IT can have a per-user view to identify latency, use patterns and pinpoint application delays hampering performance.

To better load balance, IT can also view VM performance to ensure the number of users per host session is at an optimum level. Applications themselves can be analyzed to better understand user behavior and resource allocation.

Focusing on Performance

While AVD is still somewhat in the early adoption phase, performance themes are beginning to emerge. Fine tuning the allocation of users per host session and supplying employees with supportive technology like GPUs will help to diminish latency issues. Constantly monitoring and testing for performance issues and syncing with user behavior will, in the long term, create a solid foundation for using virtual desktops — the emerging go-to solution for a remote workforce.

Amol Dalvi is VP, Product, at Nerdio

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3 Ways to Improve Azure Virtual Desktop Performance

Amol Dalvi
Nerdio

As remote work becomes a standard business practice, virtual desktops continue to gain popularity as a primary means of delivering data and applications to end users. Azure Virtual Desktop (AVD), for example, is seeing strong adoption due to its ease of deployment and its portal which enables desktop and application management from one interface. Enterprises can also control costs since they pay for virtual servers only when desktops are running, and can scale in or out depending on desktop needs. A recent survey indicated over half of the respondents (58%) expected to have AVD technology in production within two years.

Like many emerging platforms, AVD is still in its early days and IT pros are evolving, as well, in their approach to deploying and managing the service. The platform is seeing strong traction among SMB market enterprises of less than 1,000 users who like the scalability and related cost control features.

While AVD is gaining traction, IT teams are looking for ways to better deliver application performance and satisfy the end user's expectations of seamless productivity. The survey found the two biggest complaints from IT pros are slow application performance (47%) and slow logons (40%). Supporting video calls, more efficient monitoring of all AVD elements and solving latency problems are among other key issues.

Stepping Up Virtual Machine Performance

End users are on the front lines of experiencing sluggish virtual desktop performance. If it takes what feels like forever to do a simple task like opening up Word or Excel, IT will get unwanted help desk calls. For example, if your end users in a specific department are running intensive workloads, such as graphic design, confirm they are getting the right number of resources in terms of virtual machine (VM) compute power by having the optimum number of users in any one AVD host pool.

Microsoft has a guide for sizing session host VMs that makes a good point that IT needs to continually monitor VM usage, sizing up and down accordingly. If there are no graphics processing units (GPU) or graphics-intensive workloads, it is also recommended to stay with smaller VMs since they can be more easily updated — another performance related practice. With fewer users on one VM, it is more likely IT will find no one signed on and can shut it down to make updates as necessary if they are manually managing the environment.

Accommodating Multi-Media Environments

Zoom, Teams, intensive graphics use, and eventually more metaverse style collaboration, are all driving more performance concerns about latency, cloud costs, and the ability to provide an end user experience expected by Gen Z and Gen Y workers.

Stop-and-start video screens, too long video downloads; these are some examples in which latency detracts from performance. Since so many meetings are now video conferencing it's a good practice to run load and stress scenarios to ensure the remote desktop session will have adequate bandwidth to provide a satisfying experience.

Latency and quality of multimedia transmission is also affected by the connection round trip time (RTT) from the current location, through the AVD service to the Azure region in which IT can deploy VMs. Check AVD's estimator to determine the lowest RTT relevant to your users' location and make session host adjustments as needed.

Lastly, consider GPUs for better performance in video, 3D design and other graphics applications. AVD GPU virtual machines will enable graphics accelerated rendering and help AVD end users be more efficient and productive.

Monitoring all Performance Aspects

Improving AVD performance, or for that matter, any critical platform, depends on diligent monitoring. AVD offers native tools for monitoring and there are also third-party options to enhance monitoring and management. According to the survey, almost half of the IT pros say they need end-to-end monitoring that includes session hosts, control plane and Azure AD.

Further efficiency can be gained by using tools with a central dashboard that can record and analyze data in usage, active users, session host, CPUs, and other metrics to view performance and potentially identify cost savings. IT can have a per-user view to identify latency, use patterns and pinpoint application delays hampering performance.

To better load balance, IT can also view VM performance to ensure the number of users per host session is at an optimum level. Applications themselves can be analyzed to better understand user behavior and resource allocation.

Focusing on Performance

While AVD is still somewhat in the early adoption phase, performance themes are beginning to emerge. Fine tuning the allocation of users per host session and supplying employees with supportive technology like GPUs will help to diminish latency issues. Constantly monitoring and testing for performance issues and syncing with user behavior will, in the long term, create a solid foundation for using virtual desktops — the emerging go-to solution for a remote workforce.

Amol Dalvi is VP, Product, at Nerdio

Hot Topics

The Latest

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

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