Which of the following is a benefit of using a dedicated monitoring system for Kafka instead of relying solely on JMX?
Both A and C
Simplified access to metrics without requiring a JMX client
Reduced load on Kafka brokers
Eliminates the need for JMX configuration
Which of the following is a common format for specifying connector configurations in Kafka Connect?
JSON
Properties files
YAML
All of the above
What is the primary purpose of monitoring Kafka metrics?
To debug application code that interacts with Kafka
To identify and troubleshoot security vulnerabilities in Kafka
To understand and optimize Kafka cluster performance and health
To track the number of messages consumed by each consumer group
What is the primary purpose of ZooKeeper in a multi-node Kafka cluster?
Storing and serving message data
Compressing messages for efficient storage
Managing consumer group offsets
Maintaining cluster metadata and ensuring consistency
Which partitioning strategy in Kafka is most suitable when you need messages with the same key to be processed by the same consumer instance?
Key-based Partitioning
Round Robin Partitioning
Random Partitioning
Time-based Partitioning
What is the role of a 'state store' in Kafka Streams?
To cache data from external databases.
To store intermediate results of stateless operations.
To persist data required for stateful operations.
To buffer incoming records before processing.
Which of the following is NOT a common category of Kafka metrics?
Authentication metrics
Consumer metrics
Topic metrics
Producer metrics
What happens when the retention period set for a Kafka topic expires?
The entire topic is deleted from the Kafka cluster.
Consumers can no longer subscribe to the topic.
Only messages older than the retention period are deleted.
The topic becomes read-only, preventing new messages from being published.
What is the significance of 'Exactly Once Semantics' in Kafka Streams?
It guarantees that each record is processed at least once.
It ensures that records are processed in the exact order they were produced.
It prioritizes speed over accuracy in data processing.
It prevents duplicate processing of records even in the event of failures.
What is a key difference between Source Connectors and Sink Connectors in Kafka Connect?
Source Connectors handle real-time data, while Sink Connectors handle batch data.
Source Connectors push data, while Sink Connectors pull data.
Source Connectors are stateful, while Sink Connectors are stateless.
Source Connectors require custom coding, while Sink Connectors use pre-built configurations.