Low I/O thread activity with blocked throughput often indicates that producer callbacks are consuming too much time, causing the sender thread to block while waiting for onCompletion() to finish.
From Kafka Producer Performance Guide:
"Expensive logic in callbacks (e.g., I/O or complex computation) can block the sender thread, reducing throughput." Compression (A) may slightly impact CPU but not I/O thread usage.
Large batches (B) improve throughput if managed correctly.
A Layer 2 network issue (C) would lead to packet loss, not specifically low callback metrics.
Reference: Kafka Producer Metrics and Performance Tuning

connect-configs stores configurations, connect-status helps to elect leaders for connect, and connect-offsets store source offsets for source connectors

SHOW STREAMS and EXPLAIN <query> statements run against the KSQL server that the KSQL client is connected to. They don't communicate directly with Kafka. CREATE STREAM WITH <topic> and CREATE TABLE WITH <topic> write metadata to the KSQL command topic. Persistent queries based on CREATE STREAM AS SELECT and CREATE TABLE AS SELECT read and write to Kafka topics. Non-persistent queries based on SELECT that are stateless only read from Kafka topics, for example SELECT * FROM foo WHERE. Non-persistent queries that are stateful read and write to Kafka, for example, COUNT and JOIN. The data in Kafka is deleted automatically when you terminate the query with CTRL-C.

Increasing partitions increasesparallelism, but also means:
* Consumers in a group may have to handlemore partitions, especially if the number of consumers is lower than the number of partitions.
* This can result inincreased lag, especially under high load.
FromKafka Topic Management Docs:
"Increasing the number of partitions increases consumer work, and if consumers can't keep up, lag can accumulate."
* A is false:existing data is not redistributed.
* B is false:records with the same key always map to the same partitionbased on hash.
* D is not directly impacted by the partition count.
Reference:Kafka Topic Management > Adding Partitions