What is the primary purpose of monitoring Kafka metrics?
To track the number of messages consumed by each consumer group
To identify and troubleshoot security vulnerabilities in Kafka
To debug application code that interacts with Kafka
To understand and optimize Kafka cluster performance and health
What is a key difference between synchronous and asynchronous producers in Kafka?
Synchronous producers are only used for high-throughput scenarios, while asynchronous producers are suitable for low-throughput cases.
Synchronous producers send messages to multiple topics, while asynchronous producers send to a single topic.
Synchronous producers block until the broker acknowledges message receipt, while asynchronous producers send messages without waiting for confirmation.
Synchronous producers use a push-based model, while asynchronous producers use a pull-based model.
What is the primary advantage of using a compacted topic in Kafka?
Guaranteed delivery of messages to all consumers in a group.
Real-time data aggregation and analysis capabilities.
Improved message ordering for high-throughput data streams.
Reduced storage space by only retaining the latest value for each key.
Which mechanism is fundamental to Kafka's zero-copy technology for transferring data between the broker and the operating system?
Data encryption
Message compression
Direct memory access (DMA)
Data deduplication
Which scenario would benefit from using a synchronous Kafka producer?
Financial transaction processing where guaranteed message delivery is paramount.
Logging system where message loss is acceptable.
High-volume sensor data ingestion where throughput is a primary concern.
Real-time data streaming where latency is critical.
How can you access Kafka's JMX metrics?
By accessing the Kafka web console
By querying the Kafka command-line tools
By reading the Kafka log files located on the broker servers
By connecting to the Kafka broker's JMX port using a JMX client
In Kafka Connect, what is the role of a 'Source Connector'?
It transforms data within a Kafka topic before sending it to a sink.
It routes messages between different topics within a Kafka cluster.
It writes data from a Kafka topic to an external system.
It consumes data from an external system and publishes it to a Kafka topic.
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 recommended minimum number of brokers for a production-ready Kafka cluster to ensure high availability and fault tolerance?
3
1
2
4
What happens to a consumer's offset when it encounters an error while processing a message?
The offset is automatically reset to the beginning of the partition.
The offset is not updated until the message is successfully processed.
The message is discarded and the offset is advanced.
The consumer is removed from the consumer group.