Design Microservices Architecture with Patterns and Principles - Apache Kafka Use Cases

The video tutorial discusses various use cases of Kafka, including messaging, metrics, log aggregation, stream processing, website activity tracking, and event sourcing. Kafka acts as a message broker to decouple services, aggregates operational data for monitoring, centralizes logs from multiple services, processes data in pipelines using frameworks like Storm and Spark, tracks website activity in real-time, and supports event-driven architectures for event sourcing.

What is one of the primary roles of Kafka in an event-driven architecture?

• To serve as an event router

• To function as a web server

• To replace microservices

• To act as a database

How does Kafka contribute to operational monitoring?

• By providing a user interface for monitoring

• By replacing traditional monitoring tools

• By aggregating statistics from distributed applications

• By storing data in a cloud service

What is a key benefit of using Kafka for log aggregation?

• It encrypts all log data

• It centralizes logs from multiple services

• It deletes old logs automatically

• It visualizes log data in real-time

Which frameworks are commonly used with Kafka for stream processing?

• Storm and Spark

• Hadoop and Hive

• TensorFlow and PyTorch

• Angular and React

In what way does Kafka assist with website activity tracking?

• By storing user passwords

• By providing real-time publish-subscribe feeds

• By generating static reports

• By blocking unwanted users