Cloud and VDI Performance Metrics: What to Keep an Eye On

CPU: Remember, your VDI and cloud ecosystem will be a combination of virtual and physical resources. Administrators must look at specific machines (virtual and physical) and see how users are accessing the CPU resources. With numerous users launching desktops or applications from the cloud, special considerations must be made as to how many dedicated cores this server requires.

GPU: Always ensure that you include graphics resource planning as a key design consideration around successful VDI deployments and end user acceptance. The key here is to assess the types of applications that utilize rich graphics and allocate those required resources to them based on user graphics requirements. For example, high-end designers and engineers will need to be allocated high-end vGPUs to ensure that they have a consistently positive user experience. 

RAM: There will be instances where VDI workloads can be very RAM intensive. By monitoring a workload on a specific server, administrators are able to gauge how much RAM needs to be allocated. The key here is to plan for fluctuation without over-allocating resources. This is where workload monitoring becomes very important. By looking at RAM utilization over a period of time, administrators will be able to tell when spikes occur and at which level RAM should be set.

Storage: Sizing considerations are always important when working with a cloud and VDI workload. User settings and workload location will all require space. However, I/O is another consideration that must be looked at. For example, a boot storm or massive spike in usage can cripple a SAN not prepared for such an event. Monitoring I/O and controller metrics, administrators are able to make decisions that will determine performance specifics for their storage system. Often times, SSDs or onboard flash cache may need to be used to help prevent spikes in I/O.

Network: As mentioned earlier, there are numerous components that comprise a good VDI and cloud ecosystem. With that in mind, it’s critical to understand that networking and its corresponding architecture play a very important piece in a cloud-facing workload. Monitoring network throughput internally in the datacenter as well as in the cloud will help determine specific speed requirements. Uplinks from the servers into the SAN through a fabric switch providing 10GB connectivity can help reduce bottlenecks and help VDI, as well as cloud workloads perform better.