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Relationship between Zookeeper and Kafka
I'm trying to maximize my throughput and seem to have hit a ceiling. Everything described below is running in AWS.

I have configured a Kafka cluster with 5 machines, M1.Large, with 600 provisioned IOPS storage for each EC2 instance. I have a Zookeeper server (we aren't in production yet, so I didn't take the time to setup a ZK cluster). Publishing to a single topic from 7 different clients, I seem to max out at around 20,000 eps with a fixed 2K message size. Each broker defines 10 file segments, with a 25000 message / 5 second flush configuration in server.properties. I have stuck with 8 threads. My producers (Java) are configured with batch.num.messages at 50, and queue.buffering.max.messages at 100.

When I went from 4 servers in the cluster to 5 servers, I only saw an increase of about 500 events per second in throughput. In sharp contrast, when I run a complete environment on my MacBook Pro, tuned as described above but with a single ZK and a single Kafka broker, I am seeing 61,000 events per second. I don't think I'm network constrained in the AWS environment (producer side) because when I add one more client, my MacBook Pro, I see a proportionate decrease in EC2 client throughput, and the net result is an identical 20,000 eps. Stated differently, my EC2 instance give up throughput when my local MacBook Pro joins the array of producers such that the throughput is exactly the same.

Does anyone have any additional suggestions on what else I could tune to try and hit our goal, 50,000 eps with a 5 machine cluster? Based on the whitepapers published, LinkedIn describes a peak of 170,000 events per second across their cluster. My 20,000 seems so far away from their production figures.

What is the relationship, in terms of performance, between ZK and Kafka? Do I need to have a more performant ZK cluster, the same, or does it really not matter in terms of maximizing throughput.

Thanks for any suggestions – I've been pulling knobs and turning levers on this for several days now.
Jason

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