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From "Cody A. Ray" <cody.a....@gmail.com>
Subject Re: Machine specs
Date Thu, 01 May 2014 03:48:01 GMT
We use m1.larges in EC2 <http://aws.amazon.com/ec2/instance-types/> for
both nimbus and supervisor machines (though the m1 family have been
deprecated in favor of m3). Our use case is to do some pre-aggregation
before persisting the data in a store. (The main bottleneck in this setup
is the downstream datastore, but memory is the primary constraint on the
worker machines due to the in-memory cache which wraps the trident state.)

For what its worth, Infochimps
suggests<https://github.com/infochimps-labs/big_data_for_chimps/blob/master/25-storm%2Btrident-tuning.asciidoc>c1.xlarge
or m3.xlarge machines.

Using the Amazon cloud machines as a reference, we like to use either the
c1.xlarge machines (7GB ram, 8 cores, $424/month, giving the highest
CPU-performance-per-dollar) or the m3.xlargemachines (15 GB ram, 4 cores,
$365/month, the best balance of CPU-per-dollar and RAM-per-dollar). You
shouldn’t use fewer than four worker machines in production, so if your
needs are modest feel free to downsize the hardware accordingly.

Not sure what others would recommend.

-Cody


On Wed, Apr 30, 2014 at 5:57 PM, Software Dev <static.void.dev@gmail.com>wrote:

> What kind of specs are we looking at for
>
> 1) Nimbus
> 2) Workers
>
> Any recommendations?
>



-- 
Cody A. Ray, LEED AP
cody.a.ray@gmail.com
215.501.7891

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