Figure 1: Desktop computer components |
Figure 2: Virtualized desktop |
Consolidating desktop computational and storage resources in the data center improves efficiency and reduces administrative costs. In addition, desktop virtualization makes desktop environments accessible from a variety of devices, including home PCs, thin clients, smart phones and tablets.
Looking at Figure 2, it is clear that the desktop virtualization service is critically dependent on the network (represented by the cloud). Poor network performance can result in slow screen updates and delayed responses to keyboard presses and mouse clicks. Network congestion can affect access to storage, increasing the time taken to start desktop sessions and launch applications. Virtual machines hosting desktop sessions share computational resources on the server and disks in the storage arrays, resources need to be carefully managed in order to prevent performance problems from propagating.
End-to-end visibility into the resources needed to deliver desktop virtualization is essential to ensure that services are adequately provisioned. Desktop virtualization protocols (e.g. Microsoft RDP, Citrix ICA/HDX, Redhat SPICE and Teradici PCoIP) already measure quality of service in order to adapt sessions to different network conditions and clients. However, these measurements are not easily accessible to management tools.
The sFlow standard provides an integrated framework for monitoring the performance of network, server, storage and applications resources. Extending sFlow to report on desktop virtualization sessions provides end to end visibility into quality of service. As a proof of concept, the Host sFlow agent has been extended to report PCoIP metrics. The sFlow agent was installed on all the virtual machines in a VMware View 5 (VMware VDI) cluster. Exporting the metrics using sFlow is extremely efficient, allowing tens of thousands of desktop virtualization sessions to be monitored in real-time.
Figure 3: Receiving sFlow from network, servers and applications |
Figure 4: VDI performance dashboard |
All three layers are linked, for example a decrease in video frame rate may be due to slow disk I/O which in turn might be caused by packet discards on the network. While the dashboard simplifies management by showing aggregate cluster performance, sFlow's centralized architecture provides the data needed to identify busy servers, map application dependencies, monitor networked storage and quickly identify sources of network congestion.
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