Tips For Running Kafka Streams On AWS

Ian Duffy and Nina Hanzlikova have some advice if you’re looking to spin up some EC2 instances to run Kafka Streams:

With upgrades in the underlying Kafka Streams library, the Kafka community introduced many improvements to the underlying stream configuration defaults. Where in previous, more unstable iterations of the client library we spent a lot of time tweaking config values such as session.timeout.ms, max.poll.interval.ms, and request.timeout.ms to achieve some level of stability.

With new releases we found ourselves discarding these custom values and achieving better results. However, some timeout issues persisted on some of our services, where a service would frequently get stuck in a rebalancing state. We noticed that reducing the max.poll.records value for the stream configs would sometimes alleviate issues experienced by these services. From partition lag profiles we also saw that the consuming issue seemed to be confined to only a few partitions, while the others would continue processing normally between re-balances. Ultimately we realised that the processing time for a record in these services could be very long (up to minutes) in some edge cases. Kafka has a fairly large maximum offset commit time before a stream consumer is considered dead (5 minutes) but with larger message batches of data this timeout was still being exceeded. By the time the processing of the record was finished the stream was already marked as failed and so the offset could not be committed. On rebalance, this same record would once again be fetched from Kafka, would fail to process in a timely manner and the situation would repeat. Therefore for any of the affected applications we introduced a processing timeout, ensuring there was an upper bound on the time taken by any of our edge cases.

There are some interesting tidbits in here.

Related Posts

Building TensorFlow Neural Networks On Spark With Keras

Jules Damji has an example of using the PyCharm IDE to use Keras to build TensorFlow neural network models on the Databricks MLflow library: Our example in the video is a simple Keras network, modified from Keras Model Examples, that creates a simple multi-layer binary classification model with a couple of hidden and dropout layers and […]

Read More

Creating SQL Server Images In Azure Container Registry

Andrew Pruski shows us how to save Docker container images to the Azure Container Registry using Powershell: Awesome! Our custom image is in our ACR! But has it worked? Has it really? Oh ye of little faith… I guess the only way to find out is to run a container! So let’s run a Azure […]

Read More

Categories

October 2017
MTWTFSS
« Sep Nov »
 1
2345678
9101112131415
16171819202122
23242526272829
3031