scaling unicorn

snacktime snacktime at
Tue Jun 22 14:03:20 EDT 2010

>> Somewhat related -- I've been meaning to discuss the finer points of
>> backlog tuning.
>> I've been experimenting with the multi-server socket+TCP megaunicorn
>> configuration from your CDT:

So I'm in the position of launching a web app in a couple of weeks
that is pretty much guaranteed to get huge traffic.  I'm working with
ops people who are very good but this is not how they would normally
setup load balancing and scale out.  I'm having a meeting with our
network ops lead tomorrow to talk about this.  I like the idea of this
approach, it seems like it gives you more fine grained control over
how much load you put on individual servers as well as how individual
requests are handled.  But I'm not too keen on using something like
this at scale when we simply don't have the chance to test it out at a
smaller scale.  I have yet to see anyone with this setup running at
scale.  That of course doesn't mean it's not a great idea, only that I
doubt our ops guys are going to want to be the first.  They are
already overworked as it is:)

So assuming we will scale out the 'normal' way by not having a short
backlog, any info on how to manage that?   Should we control the
backlog queue in nginx (not sure exactly how I would do that) or via
the listen backlog?  I was looking around last night and couldn't find
a way to actually poll the listen backlog queue size.

Also, any ideas on how you would practically manage this type of load
balancing setup?  Seems like you would have some type of 'reserve'
cluster for requests that hit the listen backlog, and when you start
seeing too much traffic going to the reserve, you add more servers to
your main pool.  How else would you manage the configuration for
something like this when you are working with 100 - 200 servers?  You
can't be changing the nginx configs every time you add servers, that's
just not practical.


More information about the mongrel-unicorn mailing list