Hardware requirement for apache kafka - apache-kafka

Question

I am building a production environment where I will be having Apache Kafka. I want to know the best hardware combination to have for better performance. I will be having 5000 transactions/second.

Answer 1

You would need to provide some more details regarding your use-case like average size of messages etc. but here's my 2 cents anyway:
Confluent's documentation might shed some light:
CPUs Most Kafka deployments tend to be rather light on CPU
requirements. As such, the exact processor setup matters less than the
other resources. Note that if SSL is enabled, the CPU requirements can
be significantly higher (the exact details depend on the CPU type and
JVM implementation).
You should choose a modern processor with multiple cores. Common
clusters utilize 24 core machines.
If you need to choose between faster CPUs or more cores, choose more
cores. The extra concurrency that multiple cores offers will far
outweigh a slightly faster clock speed.
How to compute your throughput
It might also be helpful to compute the throughput. For example, if you have 800 messages per second, of 500 bytes each then your throughput is 800*500/(1024*1024) = ~0.4MB/s. Now if your topic is partitioned and you have 3 brokers up and running with 3 replicas that would lead to 0.4/3*3=0.4MB/s per broker.
More details regarding your architecture can be found in Confluent's whitepaper Apache Kafka and Confluent Reference Architecture. Here's the section for memory usage,
ZooKeeper uses the JVM heap, and 4GB RAM is typically sufficient. Too
small of a heap will result in high CPU due to constant garbage
collection while too large heap may result in long garbage collection
pauses and loss of connectivity within the ZooKeeper cluster.
Kafka brokers use both the JVM heap and the OS page cache. The JVM heap is used for replication of partitions between brokers and for log
compaction. Replication requires 1MB (default replica.max.fetch.size)
for each partition on the broker. In Apache Kafka 0.10.1 (Confluent
Platform 3.1), we added a new configuration
(replica.fetch.response.max.bytes) that limits the total RAM used for
replication to 10MB, to avoid memory and garbage collection issues
when the number of partitions on a broker is high. For log compaction,
calculating the required memory is more complicated and we recommend
referring to the Kafka documentation if you are using this feature.
For small to medium-sized deployments, 4GB heap size is usually
sufficient. In addition, it is highly recommended that consumers
always read from memory, i.e. from data that was written to Kafka and
is still stored in the OS page cache. The amount of memory this
requires depends on the rate at this data is written and how far
behind you expect consumers to get. If you write 20GB per hour per
broker and you allow brokers to fall 3 hours behind in normal
scenario, you will want to reserve 60GB to the OS page cache. In cases
where consumers are forced to read from disk, performance will drop
significantly
Kafka Connect itself does not use much memory, but some connectors buffer data internally for efficiency. If you run multiple connectors
that use buffering, you will want to increase the JVM heap size to 1GB
or higher.
Consumers use at least 2MB per consumer and up to 64MB in cases of large responses from brokers (typical for bursty traffic).
Producers will have a buffer of 64MB each. Start by allocating 1GB RAM and add 64MB for each producer and 16MB for each consumer planned.
There are many different factors that need to be taken into consideration when it comes to tune the configuration of your architecture. I would suggest to go through the aforementioned documentation, monitor your existing cluster and resources and finally tune them accordingly.