In ksqlDB, INSERT VALUES is used to produce data directly into a topic that underlies a STREAM or TABLE. It is a DML command that appends new records into a Kafka topic.

From ksqlDB documentation:

“INSERT VALUES adds data into a stream or table. This data is persisted in the Kafka topic backing the stream or table.”

Option analysis:

A/B → SELECT queries retrieve data but do not write.

D → Defines a table, does not write data.

C → Correct: Actually writes (produces) data to Kafka.

Page Reference:

Kafka: The Definitive Guide, 1st Edition, Chapter 7, p. 227–229

Confluent Docs: ksqlDB INSERT INTO and INSERT VALUES Statements

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Kafka Replicator does not preserve source cluster offsets. Offsets in the destination DR cluster are generated independently, and there is no guarantee they match those from the source cluster.

From Confluent Replicator documentation:

“Replicator does not guarantee preservation of message offsets between source and destination. Offsets in the destination cluster are newly assigned.”

C → Correct: Offsets may differ even for the same data.

A → Incorrect: Lag is not the issue if offsets inherently differ.

B → Misleading: Kafka does not overwrite committed messages.

D → Invalid: Kafka messages are immutable; no "update" happens.

Page Reference:

Kafka: The Definitive Guide, 1st Edition, Chapter 10, p. 313

Confluent Replicator Documentation: “Offset Mapping and Limitations”

Kafka topics support two main cleanup policies:

delete: The default policy where Kafka deletes old log segments based on retention time or size.

compact: Enables log compaction, retaining only the latest value for each key.

From Kafka documentation:

“Valid cleanup.policy values are 'delete' and 'compact'.”

B → Invalid: 'default' is not a recognized cleanup policy.

D → Invalid: 'cleanup' is not a valid keyword in this context.

Page Reference:

Kafka: The Definitive Guide, 1st Edition, Chapter 6, p. 196–197

Apache Kafka Documentation: Topic Configs – cleanup.policy

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Kafka supports multiple SASL mechanisms for authentication, including:

SASL/PLAIN – Username/password

SASL/GSSAPI – Kerberos-based

SASL/OAUTHBEARER – OAuth 2.0 token-based

From Apache Kafka documentation:

“Kafka supports the following SASL mechanisms: GSSAPI (Kerberos), PLAIN, SCRAM, OAUTHBEARER.”

B → SAML20 is not supported.

E → OTP is not a supported SASL mechanism.

Page Reference:

Kafka: The Definitive Guide, 1st Edition, Chapter 9, p. 280–284

Apache Kafka Documentation: Kafka SASL Authentication

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The Kafka REST Proxy, provided as part of Confluent Platform, allows clients to interact with Kafka over REST APIs. When securing communication between REST Proxy and REST clients, it uses TLS (HTTPS).

As per the official Confluent documentation for REST Proxy security:

“The REST Proxy supports HTTPS to encrypt communication between REST clients and the REST Proxy.”

TLS/SSL encryption ensures that data in transit is secure and private.

Other options listed, such as MD5 (a hashing algorithm), SCRAM (an authentication mechanism), and Kerberos (an authentication protocol), do not provide direct encryption of the communication channel itself for REST Proxy. They can be part of broader security configurations (e.g., SCRAM for Kafka brokers, Kerberos for SASL authentication), butTLS (HTTPS)is the explicit mechanism for encrypting data between the REST Proxy and its clients.

Page Reference:

Confluent Kafka: The Definitive Guide, 1st Edition, Chapter 9 (“Kafka Security”), Section “REST Proxy Security” (p. 288–289).

Confluent Platform REST Proxy Documentation, “Encryption (HTTPS)”.

The linger.ms property defines how long the producer will wait to fill up a batch before sending it. Combined with batch.size, it allows the producer to accumulate more messages, thus improving throughput.

From Kafka documentation:

“If batch.size is not yet reached, linger.ms causes the producer to wait for additional messages before sending the batch.”

A → send.buffer.bytes affects TCP socket size.

B → Correct: Improves batching by adding intentional delay.

C → Reduces bandwidth but not directly batching.

D → A timeout for message delivery, not related to batching.

Page Reference:

Kafka: The Definitive Guide, 1st Edition, Chapter 5, p. 162

Apache Kafka Documentation: Producer Config – linger.ms

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Kafka's Controller is a broker that also performs controller duties. It is not a dedicated node. Therefore, it continues to host topics, partitions, and leaders just like any other broker.

From Kafka documentation:

“The controller is one of the brokers in the cluster and continues to perform all normal broker functions.”

A → Correct: The controller is also a normal broker with partitions.

B/C/D → Incorrect: Replication and consumer fetches are not tied to the controller.

Page Reference:

Kafka: The Definitive Guide, 1st Edition, Chapter 6, p. 190

Apache Kafka Documentation: Kafka Controller Behavior

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