Apache Kafka Connect stores source connector offsets in a Kafka topic defined by the offset.storage.topic configuration. Since this property is explicitly set to connect-offsets, Kafka Connect will commit offsets to that topic, making Option C correct.
The offset.storage.replication.factor controls how many replicas the offsets topic will have. When this value is set to -1, Kafka Connect uses the broker's default replication factor, as documented in the Kafka Connect worker configuration reference. Therefore, Option A is also correct.
Option B is incorrect because Kafka Connect does not use Kafka's internal consumer offsets topic (__consumer_offsets). It always uses the configured offsets topic. Option D is incorrect because offset.flush.
timeout.ms defines how long Connect will wait for offset commits to complete, not how long it waits before attempting a commit. The commit interval itself is controlled by offset.flush.interval.ms (60 seconds in this case).
Thus, the correct statements that match the expected behavior are A and C.

According to the official Apache Kafka consumer semantics documentation, at-most-once delivery means that records may be lost but must never be processed more than once. To achieve this guarantee, a consumer must commit offsets before processing records. If the application crashes after committing but before processing, messages are skipped rather than reprocessed, which satisfies at-most-once semantics.
Option B correctly implements this pattern. It disables automatic offset commits (enable.auto.commit=false) and explicitly calls commitAsync() immediately after polling and before processing records. This ensures that offsets are advanced regardless of whether processing succeeds, eliminating the possibility of duplicate processing.
Option C represents at-least-once semantics, because offsets are committed after processing, which can lead to duplicates on failure. Options A and D rely on automatic commits or incorrect ordering and do not provide strict at-most-once guarantees.
The Kafka documentation explicitly states that manual offset management with commits before processing is required for at-most-once delivery.
Therefore, Option B is the best and officially documented configuration and code skeleton to avoid duplicate message processing.

This syntax is a clear match to Protocol Buffers (Protobuf). It defines a schema with fields, types, and tags, which is a format supported by Kafka when using Protobuf-based schema registry serialization.
From Confluent Schema Registry Docs:
"Kafka supports Protobuf serialization, where schemas are written in .proto files and include fields with tags." int32, double, and string are standard Protobuf types.
Avro uses JSON-style schema.
JSON Schema uses JSON object structure, not .proto.
YAML is unrelated.
Reference: Confluent Schema Registry for Protobuf

According to the official Apache Kafka client documentation, Kafka uses SLF4J (Simple Logging Facade for Java) for all client-side logging. SLF4J is only an abstraction layer and requires a concrete logging implementation to route log messages to the actual logging framework used by the application.
Since the application uses Log4j2, an SLF4J-to-Log4j2 binding must be provided. The correct and officially recommended dependency is org.apache.logging.log4j:log4j-slf4j-impl. This dependency acts as the SLF4J implementation and forwards all Kafka client log messages to Log4j2, ensuring consistent logging across the application.
Option B is incorrect because it targets the legacy Log4j 1.2 framework, which is deprecated and incompatible with Log4j2. Option C is insufficient because Log4j2 alone does not satisfy Kafka's SLF4J dependency. Option D is incorrect because Kafka intentionally does not include a logging implementation transitively, allowing applications to choose their preferred logging framework.
Therefore, including the SLF4J implementation for Log4j2 is required to properly integrate Kafka client logs.

With acks=all, the leader waits formin.insync.replicasto acknowledge the message. Since min.insync.
replicas=3, Kafka will only commit the messageonce 3 brokers (leader + 2 followers)confirm they have the message.
FromKafka Documentation > Acks and Durability:
"If acks=all is specified, the producer will wait until the full set of in-sync replicas has acknowledged the record. The minimum number of in-sync replicas is controlled by min.insync.replicas." Even though the replication factor is 4, only3 acknowledgments are needed, as defined by min.insync.
replicas.
Reference:Apache Kafka Producer Configs > acks, min.insync.replicas