CQRS pattern in Kafka - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does CQRS stand for?

CQRS stands for Command Query Responsibility Segregation. It means separating the part of a system that changes data (commands) from the part that reads data (queries).

beginner

In CQRS, what is the role of commands?

Commands are requests to change data. They tell the system to do something, like add or update information. Commands do not return data, only success or failure.

intermediate

How does Kafka help implement CQRS?

Kafka acts as a message broker that transports commands and events between services. It helps keep the command and query sides separate and syncs data changes through event streams.

intermediate

Why separate read and write models in CQRS?

Separating read and write models allows each to be optimized independently. Writes can focus on data integrity, while reads can be fast and scalable, improving overall system performance.

beginner

What is an event in CQRS and Kafka context?

An event is a record of something that happened, like 'OrderPlaced'. In Kafka, events are messages sent to topics that other parts of the system listen to and react upon.

What is the main purpose of the 'Command' in CQRS?

A To change data in the system

B To display data to users

C To store data permanently

D To request data without changing it

Commands are used to change data, like creating or updating records.

In CQRS, which side handles queries?

A Query side

B Command side

C Both command and query sides

D Neither side

The query side handles reading data without changing it.

How does Kafka support CQRS architecture?

A By storing data in databases

B By replacing the query side

C By directly updating user interfaces

D By sending commands and events as messages

Kafka sends commands and events as messages to keep command and query sides in sync.

Why might you want to separate read and write models in CQRS?

A To combine all logic in one place

B To make the system slower

C To optimize each model for its purpose

D To avoid using events

Separating models lets you optimize writes for consistency and reads for speed.

What is an event in the context of CQRS and Kafka?

A A command to change data

B A message describing something that happened

C A database query

D A user interface component

Events describe things that happened and are sent as messages in Kafka.

Explain the CQRS pattern and how Kafka can be used to implement it.

Think about how commands and queries are handled separately and how Kafka moves messages between parts.

Describe the benefits of separating read and write models in a CQRS system.

Consider why different parts of a system might need different designs.

Practice

1. What is the main idea behind the CQRS pattern in Kafka-based systems?

easy

A. Separating commands (writes) and queries (reads) into different parts

B. Using a single topic for both commands and queries

C. Storing all data in one database without separation

D. Ignoring events and focusing only on commands

Solution

1. Step 1: Understand CQRS basics

   CQRS stands for Command Query Responsibility Segregation, which means separating write and read operations.

2. Step 2: Apply to Kafka context

   In Kafka, commands and queries are handled separately, often using different topics for clarity and scalability.

3. Final Answer:

   Separating commands (writes) and queries (reads) into different parts -> Option A

4. Quick Check:

   CQRS = Separate commands and queries [OK]

Hint: Remember CQRS splits writes and reads separately [OK]

Common Mistakes:

• Thinking commands and queries share the same topic
• Confusing CQRS with event sourcing
• Assuming CQRS means no events are used

2. Which Kafka topic setup correctly follows the CQRS pattern?

easy

A. One topic for all commands, events, and queries

B. One topic for commands and a separate topic for events

C. Multiple topics for queries only

D. No topics, just direct database writes

Solution

1. Step 1: Recall CQRS topic separation

   CQRS uses separate topics for commands (writes) and events (results of commands) to keep communication clear.

2. Step 2: Evaluate options

   One topic for commands and a separate topic for events correctly separates commands and events into different topics, matching CQRS principles.

3. Final Answer:

   One topic for commands and a separate topic for events -> Option B

4. Quick Check:

   Separate topics for commands and events = One topic for commands and a separate topic for events [OK]

Hint: Separate commands and events into different topics [OK]

Common Mistakes:

• Mixing commands and queries in one topic
• Ignoring event topics
• Using no Kafka topics at all

3. Given this Kafka setup for CQRS:

commands_topic = ['CreateOrder', 'UpdateOrder']
events_topic = ['OrderCreated', 'OrderUpdated']

Which topic should a read service subscribe to for query data?

medium

A. commands_topic

B. Both commands_topic and events_topic

C. events_topic

D. Neither, it reads directly from the database

Solution

1. Step 1: Identify read service role

   Read services in CQRS listen to events that represent state changes, not commands which are requests.

2. Step 2: Match topic to read service

   Events_topic contains 'OrderCreated' and 'OrderUpdated' which reflect changes; read service subscribes here.

3. Final Answer:

   events_topic -> Option C

4. Quick Check:

   Read service subscribes to events_topic [OK]

Hint: Reads listen to events, not commands [OK]

Common Mistakes:

• Subscribing read service to commands_topic
• Subscribing to both topics unnecessarily
• Assuming reads bypass Kafka

4. You have this Kafka CQRS code snippet:

producer.send('commands', 'CreateOrder')
consumer.subscribe(['commands', 'events'])

What is the main problem here?

medium

A. Consumer should not subscribe to both 'commands' and 'events' topics

B. Producer should send to 'events' topic, not 'commands'

C. Producer must send JSON, not strings

D. Consumer must subscribe only to 'commands' topic

Solution

1. Step 1: Understand CQRS topic roles

   Commands topic is for writes; events topic is for read updates. Consumers usually subscribe to one role.

2. Step 2: Analyze consumer subscription

   Subscribing to both commands and events mixes responsibilities and can cause confusion or errors.

3. Final Answer:

   Consumer should not subscribe to both 'commands' and 'events' topics -> Option A

4. Quick Check:

   Consumer subscribes to one topic type only [OK]

Hint: Consumers should subscribe to either commands or events, not both [OK]

Common Mistakes:

• Thinking producer must send events on commands topic
• Assuming consumer can handle both topics safely
• Ignoring message format requirements

5. How can you design a Kafka-based CQRS system to handle high read traffic without slowing down writes?

hard

A. Use only one consumer group for both commands and events

B. Combine commands and events in one topic to reduce overhead

C. Write all data directly to the database and skip Kafka for reads

D. Use separate Kafka topics for commands and events, and scale read consumers independently

Solution

1. Step 1: Apply CQRS scalability principle

   Separating commands and events allows independent scaling of write and read sides.

2. Step 2: Design Kafka topics and consumers

   Using separate topics for commands and events lets read consumers scale without affecting write performance.

3. Final Answer:

   Use separate Kafka topics for commands and events, and scale read consumers independently -> Option D

4. Quick Check:

   Separate topics and scale reads independently [OK]

Hint: Separate topics and scale read consumers for high traffic [OK]

Common Mistakes:

• Combining commands and events causing bottlenecks
• Skipping Kafka for reads losing scalability
• Using one consumer group for all messages