Apache Kafka

What is event streaming?

• The practice of capturing data in real-time from event sources

• The technological foundation for the 'always-on' world

• The digital equivalent of the human body's central nervous system

• All of the above

What is Kafka used for?

• Capturing data in real-time from event sources

• Building software-defined and automated businesses

• Enabling communication between software applications

• All of the above

What are the main components of Kafka?

• Producer API

• Consumer API

• Streams API

• All of the above

What is an event in Kafka?

• A record or message that represents something that happened

• A folder that stores data in Kafka

• A client application that publishes events to Kafka

• A client application that subscribes to events in Kafka

What are producers and consumers in Kafka?

• Producers are client applications that publish events, while consumers are client applications that subscribe to and process events

• Producers are client applications that subscribe to and process events, while consumers are client applications that publish events

• Producers and consumers are the same thing in Kafka

• Producers and consumers are not used in Kafka

What is a topic in Kafka?

• A folder that stores events in Kafka

• A record or message that represents something that happened

• A partitioned and durably stored collection of events

• A client application that publishes events to Kafka

What is one of the popular use cases for Apache Kafka?

• Building and running reusable data import/export connectors

• Replacing traditional message brokers

• Implementing stream processing applications

• Capturing every change to a set of tables in a relational database

What was the original use case for Kafka?

• Building and running reusable data import/export connectors

• Replacing traditional message brokers

• Implementing stream processing applications

• Rebuilding a user activity tracking pipeline

What is Kafka often used for in operational monitoring?

• Capturing every change to a set of tables in a relational database

• Aggregating statistics from distributed applications

• Replacing traditional message brokers

• Building and running reusable data import/export connectors