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Re: Apache Kafka in AWS
Awesome right up Jason!  Very helpful as we are also looking to build a
Kafka environment in AWS.  I am curious, are you using Kafka 0.7.2 or 0.8
in your tests?  Did you have just one EBS volume per broker instance or
RAID 10 across EBS volumes per broker?

Thanks again for the great info!

-Jonathan
On Wed, May 22, 2013 at 4:35 PM, Jason Weiss <[EMAIL PROTECTED]> wrote:

> Ken,
>
> Great question! I should have indicated I was using EBS, 500GB with 2000
> provisioned IOPs.
>
> Jason
>
> ________________________________________
> From: Ken Krugler [[EMAIL PROTECTED]]
> Sent: Wednesday, May 22, 2013 17:23
> To: [EMAIL PROTECTED]
> Subject: Re: Apache Kafka in AWS
>
> Hi Jason,
>
> Thanks for the notes.
>
> I'm curious whether you went with using local drives (ephemeral storage)
> or EBS, and if with EBS then what IOPS.
>
> Thanks,
>
> -- Ken
>
> On May 22, 2013, at 1:42pm, Jason Weiss wrote:
>
> > All,
> >
> > I asked a number of questions of the group over the last week, and I'm
> happy to report that I've had great success getting Kafka up and running in
> AWS. I am using 3 EC2 instances, each of which is a M2 High-Memory
> Quadruple Extra Large with 8 cores and 58.4 GiB of memory according to the
> AWS specs. I have co-located Zookeeper instances next to Zafka on each
> machine.
> >
> > I am able to publish in a repeatable fashion 273,000 events per second,
> with each event payload consisting of a fixed size of 2048 bytes! This
> represents the maximum throughput possible on this configuration, as the
> servers became CPU constrained, averaging 97% utilization in a relatively
> flat line. This isn't a "burst" speed – it represents a sustained
> throughput from 20 M1 Large EC2 Kafka multi-threaded producers. Putting
> this into perspective, if my log retention period was a month, I'd be
> aggregating 1.3 petabytes of data on my disk drives. Suffice to say, I
> don't see us retaining data for more than a few hours!
> >
> > Here were the keys to tuning for future folks to consider:
> >
> > First and foremost, be sure to configure your Java heap size accordingly
> when you launch Kafka. The default is like 512MB, which in my case left
> virtually all of my RAM inaccessible to Kafka.
> > Second, stay away from OpenJDK. No, seriously – this was a huge thorn in
> my side, and I almost gave up on Kafka because of the problems I
> encountered. The OpenJDK NIO functions repeatedly resulted in Kafka
> crashing and burning in dramatic fashion. The moment I switched over to
> Oracle's JDK for linux, Kafka didn't puke once- I mean, like not even a
> hiccup.
> > Third know your message size. In my opinion, the more you understand
> about your event payload characteristics, the better you can tune the
> system. The two knobs to really turn are the log.flush.interval and
> log.default.flush.interval.ms. The values here are intrinsically
> connected to the types of payloads you are putting through the system.
> > Fourth and finally, to maximize throughput you have to code against the
> async paradigm, and be prepared to tweak the batch size, queue properties,
> and compression codec (wait for it…) in a way that matches the message
> payload you are putting through the system and the capabilities of the
> producer system itself.
> >
> >
> > Jason
> >
> >
> >
> >
> >
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> --------------------------
> Ken Krugler
> +1 530-210-6378
> http://www.scaleunlimited.com
> custom big data solutions & training
> Hadoop, Cascading, Cassandra & Solr
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