The Apache Kafka producer API is asynchronous by default, and proper error handling requires explicit mechanisms. The official documentation recommends using a callback function with producer.send() to determine whether a record was successfully acknowledged or failed due to an exception. The callback provides access to both RecordMetadata and any exception encountered during sending.
Additionally, certain errors-such as serialization errors or configuration issues-are thrown synchronously when calling producer.send(). These must be handled using a try/catch block that catches KafkaException or its subclasses.
Option A is invalid because ProducerRecord has no status() method. Option C is incorrect because producer.
send() returns a Future<RecordMetadata>, not a RecordMetadata object directly.
Thus, combining a callback for asynchronous errors and a try/catch block for synchronous errors is the correct and officially documented approach to ensure reliable producer error handling when using acks=all.

The default maximum message size that a Kafka broker accepts is1MB (1,048,576 bytes), controlled by the config propertymessage.max.bytes.
FromKafka Broker Configuration Docs:
"The default maximum message size is 1MB. To accept larger messages, configure message.max.bytes and the producer's max.request.size." Producers also have a matching limit via max.request.size, and consumers via fetch.message.max.bytes.
Reference:Kafka Broker Configuration > message.max.bytes

Using assign() gives manual control over partition assignment. In this mode:
B is true: The application chooses partitions directly without involving the group coordinator.
C is true: Since no group coordination occurs, no rebalancing happens if a consumer dies.
From Kafka Consumer API Docs:
"assign() manually assigns a list of partitions to this consumer. No coordination takes place and no rebalancing is triggered." A is false: subscribe() and assign() are mutually exclusive.
D is incorrect: Partitions don't need to be equal across topics.
Reference: Kafka Consumer Java API > assign() and subscribe()

The batch.size config sets the maximum number of bytes to batch per partition before sending. This allows Kafka producers to amortize I/O and improve throughput.
From Kafka Producer Configuration Docs:
"batch.size is the maximum amount of data per partition the producer will batch before sending." buffer.memory sets total memory for the producer, not per-batch.
send.buffer.bytes is a TCP socket buffer, not a Kafka config.
max.block.ms controls blocking time, not size.
Reference: Kafka Producer Configs > batch.size

To isolate logs for a specific connector, you can configure a separate logger and appender in the Connect worker's log4j.properties file, using the connector's name as the logging context.
From Kafka Connect Logging Docs:
"Kafka Connect loggers use hierarchical logger names. You can configure per-connector log levels and output files by extending log4j.properties." A and C change verbosity but don't separate logs.
D is false; targeted logging is possible.
Reference: Kafka Connect > Logging and Debugging