I was chatting with my friend Mr. Anson today and he asked about a use-case a number of his end users were asking about. They were asking Mr. Anson when CPU spikes were occurring on their server. Unfortunately, the end users did not know when these spikes were occurring, just that some users were mentioning that their experience was being effected through the day.
In this blog post, we will show you how to locate CPU spikes and patterns by investigating SCOM data with IT Analytics.
Finding the Spikes
We first start with the SCOM Performance Daily cube and filter on the Windows 2008 Server Management Pack and the % Processor Time counter. This is across all 2008 servers and across all dates and times.
We then add the server name (Host Entity – Display Name) and sort descending. What is listed are servers that have spiked at 100% across all time. There are others (75% or less) that have not.
The next result set is to only look at the machines that have spiked 90% or greater. There are a number of servers that have not spiked significantly (75% or greater).
Next, we only look at data from 2012:
There is an even smaller set of computers that have spiked over 90% in 2012. We'll filter on those next.
These are the servers we will now be concentrating on. Next add month to see the trend for all servers.
We will filter on VMDCFTP001 to look at the daily trend.
Since the highest spike is at the first of the year, we re-create this chart in the SCOM Performance Hourly cube to see the hourly trend.
We then filter on dates 01/04/2012 – 01/21/2012 and add the Hour dimension to see what hour the CPU spikes are occurring.
Now that we know when these spikes are occurring, we can investigate other data by changing (or adding) the Management Pack and associated counters to see what other information is being gathered on that server and correlate that data to investigate the root cause of the discovered CPU spikes.
||Rob has over 11 years of experience in software implementation and sales. Since joining Bay Dynamics in 2003, Rob has held a number of technical, sales, and sales engineering positions that have made him a valuable asset to the organization. He continues to assist clients in effectively optimizing both their physical and virtual infrastructure through the use of IT Analytics.