There are multiple levels of looking at performance. Tool I wrote analyzes server side performance since that was the main goal of project however you could adapt it to analyze any other type of response times ie. there is a parser that takes URLs and how long it took the web server to serve that request. User perceived performance is much harder to gauge since it depends on a number of factors not under your control such as CPU speed, rendering engine, spyware etc. slowing things down etc. You should obviously get as many metrics and evaluate how you can speed things up but server side performance ie. time it takes to generate the HTML is one you have most control over.

As far as client perceived response time there is also Boomerang

https://github.com/yahoo/boomerang

Vladimir

On Sat, 12 Mar 2011, Archana N wrote:

Thank you so much. This looks really interesting. I am working on a project to 
monitor the performance of lighttpd servers in a
cloud environment(for resource provisioning purposes) . Also, in the blog, I was not 
clear by the term "response time". Is it the
response time as perceived by the client or is it the request processing time 
of the server. I had seen many tools such as Piwik
which would measure the client percieved response time of the web pages, but 
they have the disadvantage of having java-script to
be enabled at the client's for this purpose. Is the tool you had developed 
similar to Piwik or is it measuring the server side
processing time.

-Archana

On Sat, Mar 12, 2011 at 9:46 PM, Vladimir Vuksan <vli...@veus.hr> wrote:
      You could use Ganglia but depending on number of unique URLs this may not 
be such a great idea. I did something
      similar at a previous job to evaluate page response times (aggregated on 
hourly basis). You can find it here

      https://github.com/vvuksan/pagetime-analyzer

      I blogged about it here

      http://vuksan.com/blog/2010/07/15/analyzing-your-web-page-response-times

      Vladimir


On Sat, 12 Mar 2011, Archana N wrote:

      Hi,
      I was also thinking of having metrics for counting the number of access 
of a particular string, but the problem
      is I am working
      with an application which has many directories (similar to wordpress) and 
there are a lot of directories which
      get different
      amount of hits by the users and I would like to track which ones are 
mostly hit. I will also try to think about
      it. I was not
      sure if Ganglia provided the aggregation, but now I got the answer to 
that :) .Do let me know if you also come
      up with ideas.

      On Fri, Mar 11, 2011 at 6:34 PM, Rick Cobb <rick_c...@ieee.org> wrote:
           Ganglia doesn't have a model for aggregating string-valued metrics.

           On the other hand, you can get a long way by having your
           metrics-gathering modules post a count *per string* (e.g.,
           "www.yahoo.com:hits", 15); you'll have a ton, though, so you may want
           to use some sort of naming prefix to help organize them.

           If you have ideas about how you'd like to see them aggregated, I for
           one would love to hear them; it's a fun problem to try to solve.

           -- ReC

      On Fri, Mar 11, 2011 at 9:13 AM, Archana N <dreamgirl...@gmail.com> wrote:
      > Hi,
      > I am using Ganglia for monitoring lighttpd server statistics in a cloud
      > environment. In my case I would have string metrics such as the pages 
which
      > are frequently accessed etc. I understand that if there are many 
clusters,
      > then Ganglia aggregates the information at the grid level. This is 
possible
      > for the numerical metrics. However, I would like to know how this would 
work
      > for the string metrics.
      > -Archana
      >
      > 
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