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Using IT Analytics to analyze Hyper-V Performance

By Ryan Stolte at 6/4/2011 11:10 AM
Filed Under: Hyper-V, IT Analytics, OpsMgr, Private Cloud

This post is the next in my series on using IT Analytics to analyze the performance of our Private Cloud at Bay Dynamics. In previous posts I've focused on analysis of my VMware infrastructure, but now I'll turn my attention to investigating the performance of our Hyper-V hosts.

We start with opening our SCOM Performance Cube and refine the metrics to data coming from System Center Virtual Machine Manager by choosing the MP named "System Center Virtualization Reports 2008". Adding the Entity Count and Sample Count to the pivot table gives me a high level picture of how much data I'm collecting from different objects within that MP. We have lots to choose from, including information on virtualization candidate servers, Hyper-V hosts, VM guests, and VMware ESX servers. See below:



In this case, I only want to look at my Hyper-V hosts, so I'll multi-select those five objects, right click, and filter my results to that selection.



Next I add the actual host name to the mix, and I can see the six Hyper-V hosts I'm collecting performance metrics for with this MP.



Now that I have a good set of metrics and hosts, I want to change my measures to show the actual minimum, average, and maximum values of each.



Now I've got some real numbers to chew on. To make the analysis easier, I'd like to see this as a chart. Choosing the Chart option at the top and adjusting the options to split that into three charts by Counter, I now have a much more visually informative perspective.

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I see that one of the hosts, svsfhypv002, has the most available memory as well as good free space, but also has the highest variance in CPU % total run time. I'd like to drill into that further and see that data over time to help me determine if this host is a good candidate for a new set of VMs I need to provision.

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Hmm, looks like things were stable in April with high available space and low CPU utilization, but there was a big change in May. My next thought is to see that % free space broken down by specific day to see the recent trend. Dragging in the date, I see:

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Clearly there was additional load added to this server in early May. Fortunately I still have over 75% of the disk free and this is still a good candidate to host new Hyper-V VMs.

Once again, by leveraging my IT Analytics SCOM Performance cube, I was able to analyze trends in a fluid way, asking and answering my own questions on the fly in a matter of minutes. No guessing and no waiting, I have the information I need to make good decisions about loading and capacity of my virtual infrastructure!