Of showers and sysstat
Posted: February 20, 2013 Filed under: NetApp, Storage | Tags: flash cache, netapp cpu %, netapp cpu utilization, netapp performance, performance, performance analysis, sysstat Leave a commentI was asked by a client yesterday in passing how to check CPU utilization on one of their NetApp filers. I didn’t immediately know where to go and we quickly moved on to something else. So as I was showering this morning, as I do many mornings, I remembered that, of course, you can use sysstat to view performance data. Anyways, this is a real nice way to view instantaneous general performance data. Options for this command are shown below.
deathstar> sysstat ?
usage: sysstat [-c count] [-s] [-u | -x | -m | -f | -i | -b] [interval]
-c count – the number of iterations to execute
-s – print out summary statistics when done
-u – print out utilization format instead
-x – print out all fields (overrides -u)
-m – print out multiprocessor statistics
-f – print out FCP target statistics
-i – print out iSCSI target statistics
-b – print out SAN statistics
interval – the interval between iterations in seconds, default is 15 seconds
Performance Analysis for a SQL Cluster
Posted: July 23, 2012 Filed under: SQL Server, Windows | Tags: analysis, cluster metrics, cluster performance, metrics, performance, performance analysis, sql, sql cluster, sql cluster metrics, sql cluster performance, sql metrics, sql performance 5 CommentsI was recently asked to pull the performance metrics for a new SQL cluster at work. In an effort to finally get back to blogging, I thought I’d share my results and how someone else may be able to look at their clusters for ways to improve. I should start by saying that although this analysis was performed on a two-node Windows Server Failover Cluster using Windows Server 2008 R2 x64 (WSFC, formerly MSCS) and SQL Server 2008, SQL-specific metrics are not pulled. Rather, I looked at the Big Four: CPU, Memory, Disk, and Network. The second node in the cluster, Node B, was analyzed because the application using the first node was not in production yet, so we knew that node would barely be utilized.
Using Microsoft System Center Operations Manager (a behemoth in its own right!), I was able to pull the previous six days’ worth of performance data. What I included in my analysis were graphs of performance for seven days, an explanation of what the data was measuring, and somewhat of an average baseline against which to measure.
The original work was presented in PowerPoint. I’ve taken screenshots of the presentation and included them here.