Kafka transfers data with zero-copy and sends the raw bytes it receives from the producer straight to

the consumer, leveraging the RAM available as page cache

Log compaction retains at least the last known value for each record key for a single topic partition.

All compacted log offsets remain valid, even if record at offset has been compacted away as a

consumer will get the next highest offset.

clients can interact with the schema registry using the HTTP or HTTPS interface

Producers can set acks=1 to get acknowledgement from partition leader only.

Seehttps://kafka.apache.org/20/documentation/streams/developer-guide/dsl-api.html#statefultransformations

Here, we must commit the offsets right after receiving a batch from a call to .poll()

unclean.leader.election.enable=true allows non ISR replicas to become leader, ensuring availability

but losing consistency as data loss will occur

acks=all means the leader will wait for all in-sync replicas to acknowledge the record. Also the min in-

sync replica setting specifies the minimum number of replicas that need to be in-sync for the

partition to remain available for writes.

Your Zookeeper cluster needs to have an odd number of servers, and must maintain a majority of

servers up to be able to vote. Therefore, a 2N+1 zookeeper cluster can survive to N zookeeper being

down, so here the right answer is N=2, 2*N+1=5

Each producer is allowed to produce @ 1MB/s to a broker. Max throughput 5 * 1MB, because we

have 5 brokers.