Performance Monitoring: Averages and Peaks

Now that we are into the topic of performance (of capacity) monitoring and planning, let us continue with something that has kept me busy the last couple of days: averages of performance data (and other statistical information) versus peaks.

This goes back to a classic textbook example in statistics, where the mean value of a series of data points is completely irrelevant as a representation of the data points itself. Let us consider the following example. Given a series of data like in the table below:

X Y
A 1
B 2
C 4
D 7
E 100
F 4
G 9
H 7
I 3
J 5

These may, for instance, represent scores (0-100) given to students (by a very strange teacher). In a graph, this is presented below:



The red line represents the average value. It is clear that everyone (except the teacher's little friend with 100 points) is below the average. As a consequence, the average is not a good representation of the data as a whole. Some say it is too much influenced by the extreme values. In fact, this average (sum of the data values divided by the total amount of data points) is called the arithmetic mean. There is another notion of 'an average' which is called 'geometric mean'. In the example above, the value of it would be 5.4 which is much more relevant. The median would even better define the data set, but that would lead us too far.

Basically, the fact that the arithmetic mean does not give a good indication of the data set is caused by the large spread of the data. In statistics, there is another indicator for this: the variance, or standard deviation. It is a measure for how close or far apart the values are. In the example above, the standard deviation. In our example above, it would read 30.2. Suppose the value of E would be 10 instead of 100, the standard deviation becomes 3. In others words, the lower is the standard deviation, the more the data is 'close'.

The above brings me back to performance monitoring. Somehow, I want to summarize the performance data of a server by a small set of indicators (averages of time etc.) that give a reasonable picture of the actual performance or in other words: that are representable for the system's actual performance. Typically, when looking at the percentage a CPU is used over time, we see fluctuations that are similar to the figure above (don't believe me, below is an actual example of a system with some high peaks and further sitting idle for most of the time - this server has 4 cores by the way). We conclude that, therefore, it does not make much sense to look at simple averages of the performance counters in order to get an idea of the behavior of the system..



Coming back to VMware Capacity Planner: the tool keeps track of the average value (yes, the simple average that does not say much) but also internally uses the geometric mean but not the variance (as far as I can tell). From this perspective, the whole performance gathering using this tool would be worthless. Luckily, it also keeps track of peak values (and calculates averages over these peaks but that is another story). Comparing the peak values with the average tells us a lot about the spread of the data points. The system behind the graph above, has an average CPU value of less than 20% while the peak CPU utilization is higher than 90%! This tells us that the variance/spreading in data points is large.

In a virtualization/consolidation assessment, these cases have to be taken into account, as we do not want our systems to become unresponsive because they have their peaks at the same time. More about this and other topics later...

Capacity Planning: What to monitor and how to interpret

Capacity planning starts with capacity (of performance) monitoring.

Everybody who is involved in the monitoring of systems will acknowledge that the most difficult aspects in monitoring a server (or set of servers) are:

1. Finding the proper indicators for the performance of the system (CPU usage, CPU cycles, memory usage, paging, etc.)


2. Making sure they are queried regularly, but not too much in order to avoid impacting the performance of the system by monitoring it.


3. Storing the resulting data


4. Summarize, create views, average, etc. (this also depends on what you want to know about the system)


5. Analyze, interpret, etc.

Did I say the most difficult aspects? Are there any other aspects? Well, not really... capacity monitoring (and planning as a further step) is not an easy task:

• Are you aware of the utilization of your systems? Even of your workstations?


• Would you have any idea how many of your servers could be placed on a virtualization platform with a specific set of hardware characteristics?


• Would you know when your mail server had the hardest time managing mail boxes the last couple of weeks?

Probably the answer is 'no'. Maybe the answer is 'I don't care'?

Most companies do care, because of several reasons: cost, manageability, flexibility, scalability, environment, space, etc.

There are already some players on the market: VMware Capacity Planner (see earlier posts), PlateSpin PowerRecon, Veeam Monitor, etc. I'm mostly used to VMware Capacity Planner (VMCP) but recently, I have also evaluated both PowerRecon and Veeam Monitor. More about this later.

VMware Capacity Planner: taking the data offline (Part 3: Getting CSV data)

This is part 3 of a series concerning VMware Capacity Planner.

First a general remark about the update to version 2.6 of the tool: it was not always pleasant to use the web interface the last week because of downtime (scheduled maintenance), errors in the interface, latency, etc. It all feels normal again, and some of the new features where definitely worth it.

Back to business: What interests me most when it comes to downloading data from the website is the pure performance data. VMware averages this information over a week, so data can be downloaded on a weekly basis.

I'm not going into the full details of everything that can be tweaked, configured or queried but most of it will be clear when looking at the actual command-line to get a CSV file. Most important is understanding that some of the choices you make are based on the session that is open on te server, and are not selected using POST or GET. Some of these options can be configured on the html view, but not the export view (although the syntax is available) so we have to apply a trick: first get the html view for the type of data we want and then export the data.

Below, you find a typical command-line to download the core VMware statistics for week 45 of a company with ID 1234:

wget --keep-session-cookies --load-cookies cookies.txt
--save-cookies cookies.txt https://optimize.vmware.com/inv_report.cfm?page=ViewStatsMain2.cfm&action=export§ion=View&sort=ObjectName&sortDir=ASC&YearWeek=200745&Mon=2&ISO=2&opt=P&PerfGroupID=1&grpt=S&HostType=0&menutab=Performance --post-data CID=1234&YearWeek=200745 --no-check-certificate -O Stats.csv

Note that quite some things have to be specified: week, company, type of average, type of metrics, system group, etc.

Drop me a line or leave a comment in case you want to know more about the precise parameters that are important or in case you're interested in my little script that does the magic for me.

This concludes the practical part of this series. I plan to write more about capacity planning and capacity monitoring in general later...

Word vs. Excel

I stumbled upon the iWork suite (aka Office for Mac) already some time ago, but today thought back of it as I was thinking about Excel and Word...

The main problem I have with Excel and Word is that there is nothing in-between. Let me explain what I mean by means of some examples:

Text-based tables: Excel (as most spreadsheets) is a numerical calculation sheet application. Although it has some functions to work with strings, it is not the primary goal of the application. This is fine, but in practice, we see that a lot of people (and even big companies) use it to store text-based data (e.g.: IP ranges, Application overview, user accounts, passwords, etc.)

Side-by-side comparison: this is in fact an example of the previous point: how many times do we not want to compare pros and cons of something? Excel is not really optimized for this, but a table in Word is even worse.

Documents with a lot of tables: This really is on the boundary of both products. In order to keep the exact formatting as set in Excel, I usually copy/past the table into Word as a picture. This is not very efficient in terms of having to change some numbers in the tables. Using the OLE features with a conventional copy/paste is usually not an option as the table in Word does not look half as nice as it should.

Reports: This is again a special case of the previous point: sometimes the data in the tables is expected to change because it contains for instance KPI information, or extracts from a database. Using Excel to nicely print a paper/PDF report is hard, copying all the tables and graphs to a Word document every day or week is even harder. In practice, I solve this by using a macro that automatically creates a Word document and pastes the tables and graphs (as pictures) where they belong. This approach has been the most successful for me up till now.

It seems iNumber makes a step in the right direction. Take a look at some of the demos on the page and see for yourself: graphics, text and tables are mixed easily.

Is this another 'sign' I have to switch to the Mac?

VMware Capacity Planner: taking the data offline (Part 2: Cygwin & wget)

I started thinking about avoiding the manual exports from the VMCP website and remembered I used WGET in the past for this kind of stuff. The difference with before was that this time, I needed to login to the website before being able to get data from it.

Login in to the VMCP website is done using a POST method and luckily wget supports that. The next thing is to understand what the post data needs to be. This can be fetched from the source of the logon page:


The relevant POST data is derived to be

fuseaction=Security
Page=users_login.cfm
username=???
password=???


Since I run Windows XP on my laptop, I use Cygwin to run wget. Cookies are used to store a session ID for you logon session, so wget has to be told to store those cookies in a file. This is the resulting command line:


wget --keep-session-cookies --save-cookies cookies.txt 'https://optimize.vmware.com/index.cfm' --post-data 'fuseaction=Security&Page=users_login.cfm&username=???&password=???' --no-check-certificate -O output.html


Parsing the output.html file, you should be able to see whether logon was succesful. The success depends on many factors (local proxy, network settings, username/password, etc.). You can get more info by adding suitable options to wget.

This concludes part 2 of this series of articles. In this part, we used wget to logon to the VMware capacity planner website.