Re: [Ganglia-general] Ganglia gmond memory leak?

2012-02-23 Thread svd.ganglia
i observed this in the past as well.  running valgrind for days did not 
yeild any clue.  i had a hunch that remote spoofed metrics were involved, 
as the leak seemed to get better when i had coincidentally disabled the 
sending of some of those spoof metrics.  but, we never found anything 
conclusive.  there was also some odd race such that sometimes after 
restart the leak was much faster, but after restarting a few times the 
leak slowed (but was always still fast enough to be a burden).

-scott

 From: Aidan Wong aidanw...@attinteractive.com
 To: Ave-Lallemant, Nathan P nathan.p.ave-lallem...@efleets.com; 
 ganglia-general ganglia-general@lists.sourceforge.net
 Sent: Thursday, February 23, 2012 8:34 AM
 Subject: Re: [Ganglia-general] Ganglia gmond memory leak?


 I've restarted the gmond process and memory usage drops until gmond hogs 
 memory over time. ?Any Ganglia contributors who may want to chime in on this 
 memory leak issue? ?I'm on Ganglia 3.2.0. ?Are there any improvements on 
 version 3.3.1 addressing this issue?


 Thanks

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Re: [Ganglia-general] Ganglia gmond memory leak?

2012-02-23 Thread svd.ganglia
makes sense, but i know in my case the number of metrics was constant 
after the server gmond had been started for about 10 minutes all gmetric 
crons had a chance to submit an initial value.


-scott

On Thu, 23 Feb 2012, Matt Massie wrote:


Each unique metric (keyed on metric name) requires memory space in gmond.  
A good test is to peek at the number of metrics in gmond over time, e.g.
$ telnet localhost 8649 | grep METRIC | wc -l

If the number of metrics over time increases, so will the memory use.

Ganglia will release the metric and memory when the age of the metric is 
greater than DMAX.  A DMAX value of zero will cause ganglia to hold the metric
indefinitely.  In order to make sure that ganglia is releasing old metrics, set 
the DMAX value to something like 5 minutes (300 secs).

For example, lets assume you are doing per process monitoring and the metric 
name looks like

cpu_user.%d % (pid,)

Over time, you'll have lots of metrics (cpu_user.343493, cpu_user.343022, 
cpu_user.232323) that start accumulating and taking up memory space.

-Matt--
Virtualization  Cloud Management Using Capacity Planning
Cloud computing makes use of virtualization - but cloud computing 
also focuses on allowing computing to be delivered as a service.
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