You want to increase Producer throughput for the messages it sends to your Kafka cluster by tuning the batch size (`batch size') and the time the Producer waits before sending a batch (`linger.ms').According to best practices, what should you do?
Answer(s): D
Increasing batch.size allows the producer to accumulate more messages into a single batch, improving compression and reducing the number of requests sent to the broker. Increasing linger.ms gives the producer more time to fill up batches before sending them, which improves batching efficiency and throughput.This combination is a best practice for maximizing throughput, especially when message volume is high or consistent latency is not a strict requirement.
When using Kafka ACLs, when is the resource authorization checked?
Answer(s): A
Kafka ACLs (Access Control Lists) perform authorization checks every time a client attempts to access a resource (e.g., topic, consumer group). This ensures continuous enforcement of permissions, not just at connection time or intervals. This approach provides fine-grained security, preventing unauthorized actions at any time during a session.
An employee in the reporting department needs assistance because their data feed is slowing down. You start by quickly checking the consumer lag for the clients on the data stream. Which command will allow you to quickly check for lag on the consumers?
Answer(s): B
The kafka-consumer-groups.sh script is used to inspect consumer group details, including consumer lag, which indicates how far behind a consumer is from the latest data in the partition. The typical usage is bin/kafka-consumer-groups.sh --bootstrap-server <broker> --describe --group <group_id>
What are benefits to gracefully shutting down brokers? (Choose two.)
Answer(s): A,B
A graceful shutdown ensures that logs are flushed to disk, minimizing recovery time during restart. Kafka performs controlled leader migration during a graceful shutdown to avoid disruption and ensure availability.
How does Kafka guarantee message integrity after a message is written on a disk?
Kafka ensures message immutability for data integrity. Once a message is written to a Kafka topic and persisted to disk, it cannot be modified. This immutability guarantees that consumers always receive the original message content, which is critical for auditability, fault tolerance, and data reliability.
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