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Apache Kafka 面接の質問と回答

質問 31. What is Data Log in Kafka?

As we know, messages are retained for a considerable amount of time in Kafka. Moreover, there is flexibility for consumers that they can read as per their convenience. Although, there is a possible case that if Kafka is configured to keep messages for 24 hours and possibly that time consumer is down for time greater than 24 hours, then the consumer may lose those messages. However, still, we can read those messages from last known offset, but only at a condition that the downtime on part of the consumer is just 60 minutes. Moreover, on what consumers are reading from a topic Kafka doesn’t keep state.

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質問 32. Explain how to Tune Kafka for Optimal Performance.

So, ways to tune Apache Kafka it is to tune its several components:
  • Tuning Kafka Producers
  • Kafka Brokers Tuning 
  • Tuning Kafka Consumers

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質問 33. State Disadvantages of Apache Kafka.

Limitations of Kafka are:
  • No Complete Set of Monitoring Tools.
  • Issues with Message Tweaking.
  • Not support wildcard topic selection.
  • Lack of Pace.

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質問 34. Enlist all Apache Kafka Operations.

Apache Kafka Operations are:

  • Addition and Deletion of Kafka Topics
  • How to modify the Kafka Topics
  • Distinguished Turnoff
  • Mirroring Data between Kafka Clusters
  • Finding the position of the Consumer
  • Expanding Your Kafka Cluster
  • Migration of Data Automatically
  • Retiring Servers
  • Datacenters

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質問 35. Explain Apache Kafka Use Cases?

Apache Kafka has so many use cases, such as:
  • Kafka Metrics: It is possible to use Kafka for operational monitoring data. Also, to produce centralized feeds of operational data, it involves aggregating statistics from distributed applications.
  • Kafka Log Aggregation: Moreover, to gather logs from multiple services across an organization.
  • Stream Processing: While stream processing, Kafka’s strong durability is very useful.

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