Why connectors integrate external systems in Kafka - Challenge Your Understanding

Challenge - 5 Problems

🧠 Conceptual

intermediate

Purpose of Kafka Connectors

Why do Kafka connectors integrate external systems with Kafka?

A To monitor Kafka cluster health continuously

B To enable seamless data flow between Kafka and other systems without custom coding

C To encrypt Kafka messages automatically

D To replace Kafka brokers with external databases

💡 Hint

Think about how connectors help move data easily.

Kafka connectors are designed to connect Kafka with external systems to move data in and out without writing custom code.

🧠 Conceptual

intermediate

Role of Source Connectors

What is the main role of a Kafka source connector?

A To receive data from external systems into Kafka topics

B To manage Kafka cluster configurations

C To send data from Kafka to external systems

D To compress Kafka messages

💡 Hint

Source means where data comes from.

Source connectors pull data from external systems and write it into Kafka topics.

❓ Predict Output

advanced

Output of Kafka Connect Configuration

Given this Kafka Connect configuration snippet, what is the expected behavior?

Kafka

name=jdbc-source-connector
connector.class=io.confluent.connect.jdbc.JdbcSourceConnector
topic.prefix=jdbc_
connection.url=jdbc:postgresql://localhost:5432/mydb
mode=incrementing
incrementing.column.name=id

A Kafka Connect will fail due to missing sink configuration

B Kafka will send data to PostgreSQL database continuously

C Data from PostgreSQL table will be streamed into Kafka topics prefixed with 'jdbc_' incrementally

D Data will be deleted from PostgreSQL after streaming

💡 Hint

Look at the connector class and mode.

This configuration sets up a source connector that reads new rows incrementally from PostgreSQL and writes them to Kafka topics with prefix 'jdbc_'.

❓ Predict Output

advanced

Result of Sink Connector Behavior

What happens when a Kafka sink connector is configured to write to an external system?

Kafka

name=s3-sink-connector
connector.class=io.confluent.connect.s3.S3SinkConnector
topics=my_topic
s3.bucket.name=my-bucket
flush.size=1000

A Messages are deleted from Kafka after 1000 records

B Data is read from S3 and sent to Kafka topic 'my_topic'

C Kafka Connect will produce an error because flush.size is invalid

D Messages from 'my_topic' are batched and saved to S3 bucket 'my-bucket' every 1000 records

💡 Hint

Sink connectors write data out of Kafka.

The S3 sink connector batches messages from the Kafka topic and writes them to the specified S3 bucket after reaching the flush size.

🧠 Conceptual

expert

Why Use Kafka Connect Instead of Custom Code?

What is the main advantage of using Kafka Connect to integrate external systems instead of writing custom integration code?

A Kafka Connect provides a scalable, fault-tolerant, and reusable framework that reduces development effort

B Custom code always runs faster than Kafka Connect

C Kafka Connect requires no configuration and works automatically

D Custom code is easier to maintain than Kafka Connect connectors

💡 Hint

Think about maintenance and scalability benefits.

Kafka Connect offers a ready-made framework that handles scaling, fault tolerance, and common integration patterns, saving time and effort.