Why VDI Performance Software Should Track and Analyze Functional Interactions Xangati Blog Atchison Frazer Vice President, Marketing
March 17, 2015
Xangati Blog 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 shortterm 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.
Xangati Blog 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.
Xangati Blog 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 endusers. 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.
Xangati Blog 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?
Xangati Blog 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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