Why VDI Performance Software Should Track

and Analyze Functional Interactions

Xangati Blog

Atchison Frazer Vice President, Marketing

March 17, 2015

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Effective performance management in a virtualized world requires knowledge and understanding

about how the actions of one object impact another. If there is a problem with one object, you need

to be able to see which other objects interact with it and could be causing a degrading problem.

Accomplishing such a high level of comparative data requires analytics that can detect and show, for

example, that a CPU spike relates to a certain interaction between two VMs or which specific VM is

causing a data store contention storm, while also impacting which individual users. This unique

ability to parse interactions allows you to point directly to root cause and analyze real-time

remediation.

Unlike conventional average-trending solutions, Xangati delivers accelerated troubleshooting

capability through tracking and analyzing interactions for all the consumptive metrics it gathers. The

virtualization environment fluctuates constantly, and the interdependencies of objects at a given

moment vary widely from pre-configured, static relationships. Sensing the impacts of these short-

term interactions is fundamental to problem identification in a world of non-persistent desktops

where a user logs into a different desktop from a different location with each access, which is

particularly prevalent in healthcare IT environments, for example.

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Without the benefit of a cross- and inter-silo interactional analysis engine – hundreds of thousands

of interactional data crunched in real time – you might not be able to catch important contention

issues, for example:

• Tracking functions in isolation may cause you to miss the performance impact of a function on a

different part of the VI/VDI environment

• To troubleshoot a performance problem with one object, you need to be able to track

interactions with other objects that could be causing a conflict

• By correlating dynamic physical and virtual interactions, you’re able to continuously search and

predict patterns for transient fluctuations that indicate performance storms

System-learned profiles are also a key element to tracking the health of your VDI environment. Used

in conjunction with industry recognized best practices and heuristic algorithms, system-learned

profiles help Xangati fully understand the operational challenges of your virtual environment,

especially when visibility is sometimes constrained by infrastructure complexity.

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Xangati develops performance profiles across dozens of functional metrics for every object it tracks

including VMs, end users, VDI protocols, data stores, and hypervisor or cloud hosts. Xangati profiles

continuously react to the environment; evolving as VDI environment conditions evolve, which is

especially useful in tracking parameters that vary depending on the changing roles of VDI end-

users.

Finally, as a service assurance outcome, Xangati allows you to manage virtual infrastructure

capacity more strategically. The Xangati VDI dashboard provides insights into how short-term

fluctuations affect long-term system capacity and summarizes that in a capacity health score.

Xangati processes trend analysis of CPU, memory, disk and network capacity over time, identifying

what period of time additional capacity needs to be added. Additionally, the Xangati StormTracker

function correlates performance storms to capacity saturation, so that if there is a high correlation

between performance issues and capacity saturation, Xangati provides you with the compelling

business case to add incremental hardware capacity to the environment or vice versa to take

elements out of the equation.

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Xangati affords VI administrators the luxury of instantly identifying contention storms and prevent

them before they have an adverse impact on your VDI end-user community. With live, continuous

tracking of performance health across the VI/VDI environment, Xangati provides organizations an

immediate ROI by enriching existing service management processes. The incident management

process is significantly improved by capabilities such as Visual Trouble Ticket (VTT) recordings and

how they integrate with service desk management. The problem avoidance process is similarly

bolstered by the system’s ability to proactively track storms and provide instant notification as

opposed to providing retrospective data.

So when evaluating management solutions for VDI performance, always consider the following:

Virtual Desktop Key Metrics and Interactions for Quality of Experience (QoE) From Compute,

Network and Storage – Live and Historical: Can you see key metrics of a user desktop including

bandwidth, performance and storage characteristics as well as its interactions with the client and the

specific services and data stores used?

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Specific Information From Desktops’ Remoting Protocol: In addition to virtual desktop

networking, compute and storage metrics and interactions, are ancillary metrics also available from

the PCoIP or HDX remoting services on each desktop? These protocols include information such as

end-to-end latency to the client, and PCoIP/HDX compositional bitrate and frame rates, all of which

can contribute to assuring end-user QoE.

Are historical reports readily available for any desktop or any client across multiple trends

and dependencies? Does the performance analytics engine show logon duration and top users by

logon duration for a VDI desktop pool for the last 24 hours? If so, then it should be able to encode

the live calculation of MOS scores (e.g., quality measures of voice-over-IP) so that these scores and

performance metrics are readily available as part of a managed VDI services workflow.

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