Thanks for reply David - I've enjoyed reading your notes/prezos on rsyslog
recently!

I feel it's somewhere downstream as well.  I've made these changes to try
and improve throughput.

I added haproxy between rsyslog and a logstash farm. I have two logstash
instances accepting connections from the haproxy frontend.  I'm still
trying to figure out how to get balanced traffic across each, but I see
traffic hitting both at some point.

A spike came in again this AM and there were a few thousand DA files
created so I'm not sure what else to try here. Is there a way to increase
the rsyslog output processing? Can multiple tcp output connections be
established to the haproxy input to increase output? Can the processing of
DA files be increased/accelerated somehow?

Thanks for any pointers!

Doug


On Fri, Jun 27, 2014 at 3:07 PM, David Lang <[email protected]> wrote:

> On Fri, 27 Jun 2014, Doug McClure wrote:
>
>  I'm in the tuning & optimization phase for a large rsyslog - logstash
>> deployment and working through very close monitoring of system
>> performance,
>> logging load and imstats.
>>
>> This morning, a very large incoming log spike occurred on the rsyslog
>> imptcp input and was processed. That spike was routed to my omfwd action
>> to
>> be shipped to a logstash tcp input.
>>
>> What it appears is happening is that very large input spike went to disk
>> assisted queues and has created over 37K files on disk.  They are being
>> processed and shipped and I have a steady 60Kb/s output headed towards
>> logstash tcp input.
>>
>> My question - where should I begin to look to optimize the processing of
>> that output action queue or changing configuration to avoid queuing up so
>> much in the first place?  How would I determine if this is due to rsyslog
>> setup or on the logstash input side?
>>
>
> This is probably logstash not being able to keep up with the flood of
> traffic from rsyslog. Then once rsyslog spills to disk, it gets
> significantly slower (one of the things that can use a revision/upgrade is
> the disk queue code)
>
> you can specify a larger queue to hold more im memory (also, FixedArray
> seems to be a little more efficient thatn LinkedList, but that's not your
> problem now)
>
> If logstash can handle more inputs effectively, you can try adding more
> workers, but that can acutally slow things down (the locking between
> threads can sometimes slow things down more than the added cores working
> speed it up)
>
> But start by looking on the logstash side.
>
> David Lang
>
>  Looking at imstats in the analyzer for logstash output (omfwd) I see
>> significant processed/failed numbers and then in the logstash ouput -DA-
>> it
>> looks like things are as described above - large queues, with no failures
>> being processed gradually.
>>
>>
>> rsyslog 7.4.4 output action:
>>
>> action(type="omfwd"
>>       Target="10.x.x.x"
>>       Port="10515"
>>       Protocol="tcp"
>>       Template="LogFormatDSV"
>>       queue.filename="logstashqueue"     # set file name, also enables
>> disk mode
>>       queue.size="1000000"
>>       queue.type="LinkedList"            # use asynchronous processing
>>       queue.workerthreads="5"
>>       name="logstashforwarder"
>>       )
>>
>>
>> Thanks for any pointers!
>>
>> Doug
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