New question #166527 on Graphite:
https://answers.launchpad.net/graphite/+question/166527

This is probably more of a Python question than a Graphite question but I 
thought I'd ask for other users experiences and advice. My Python skills are 
not far past the "Hello world" stage (although I'm getting better!)

When I first started playing with Graphite I installed it on a VMWare VM 
(Ubuntu 10.10). Unsurprisingly, once I started putting lots of data in to it 
the rendering slowed down. What I found though was that even by adding memcache 
and giving the VM more processors there was not much of an improvement to the 
rendering. 

Now that my company has decided we're going to adopt Graphite I've been doing a 
few experiments with the hardware I have available. I've taken 3 large datasets 
I created (a little script that just creates a text file of steve.metric.1 
<random number> <timestamp every 5 secs>) and uploaded it to a fresh Graphite 
install on either Ubuntu 10.10 or RHEL 6 on four bits of hardware: a Intel Core 
2 Duo desktop, an AMD Opteron server, an Intel Qaud core server and what we 
call "Dodecs" - 3 quad core AMD processor machines.

Although you can see a difference in the processor usage - as in the dodecs 
clearly aren't working as hard as the Core 2 -  the end result - the time it 
takes to render various graphs - doesn't seem to change much. 

My assumption is that something somewhere isn't using the available processing 
power - for example, Apache is but Python isn't - which is why we observe less 
processing power for the same end result? But this is an assumption based on 
very solid facts, the main one being that I don't know the inner workings of 
Python.

In summary, do I need to do something to take advantage of the extra processing 
power or should I not bother putting Graphite on high powered boxes?

Thanks in advance!

Steve

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