Confluent Cloud overview in Kafka - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a Kafka producer in Confluent Cloud.

Kafka

from confluent_kafka import Producer

conf = {'bootstrap.servers': '[1]', 'sasl.mechanism': 'PLAIN'}
producer = Producer(conf)

Drag options to blanks, or click blank then click option'

Apkc-xyz.us-west1.gcp.confluent.cloud:9092

Blocalhost:9092

C127.0.0.1:9092

Dkafka:9092

Attempts:

3 left

💡 Hint

Common Mistakes

Using localhost or 127.0.0.1 instead of the cloud endpoint.

Omitting the port number 9092.

The correct bootstrap server for Confluent Cloud includes the cluster endpoint with port 9092.

2fill in blank

medium

Complete the code to send a message to a topic in Confluent Cloud.

Kafka

producer.produce('[1]', key='key1', value='Hello, Confluent!')
producer.flush()

Drag options to blanks, or click blank then click option'

Aconfluent_topic

Btest_topic

Cmy_topic

Dcloud_topic

Attempts:

3 left

💡 Hint

Common Mistakes

Using a topic name that does not exist in the cloud cluster.

Leaving the topic name blank.

The topic name must match the one created in Confluent Cloud; here, 'test_topic' is the example topic.

3fill in blank

hard

Fix the error in the configuration to connect securely to Confluent Cloud.

Kafka

conf = {
  'bootstrap.servers': 'pkc-xyz.us-west1.gcp.confluent.cloud:9092',
  'security.protocol': '[1]',
  'sasl.mechanism': 'PLAIN',
  'sasl.username': 'API_KEY',
  'sasl.password': 'API_SECRET'
}

Drag options to blanks, or click blank then click option'

APLAINTEXT

BSSL

CSASL_SSL

DSASL_PLAINTEXT

Attempts:

3 left

💡 Hint

Common Mistakes

Using PLAINTEXT or SSL without SASL.

Using SASL_PLAINTEXT which is insecure and not supported.

Confluent Cloud requires SASL_SSL for secure authentication and encryption.

4fill in blank

hard

Fill both blanks to create a consumer that subscribes to a topic and polls messages.

Kafka

from confluent_kafka import Consumer

conf = {
  'bootstrap.servers': 'pkc-xyz.us-west1.gcp.confluent.cloud:9092',
  'group.id': '[1]',
  'auto.offset.reset': '[2]',
  'security.protocol': 'SASL_SSL',
  'sasl.mechanism': 'PLAIN',
  'sasl.username': 'API_KEY',
  'sasl.password': 'API_SECRET'
}
consumer = Consumer(conf)
consumer.subscribe(['test_topic'])

Drag options to blanks, or click blank then click option'

Amy_group

Bearliest

Clatest

Ddefault

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'default' which is not a valid offset reset value.

Not setting a group id.

The consumer group id is 'my_group' and 'auto.offset.reset' is set to 'earliest' to read from the beginning if no offset is found.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps topic names to their partition counts if partitions are more than 1.

Kafka

topics = {'topic1': 1, 'topic2': 3, 'topic3': 2}
partition_map = { [1]: [2] for [3] in topics if topics[[3]] > 1 }

Drag options to blanks, or click blank then click option'

Atopic

Btopics[topic]

Dpartitions

Attempts:

3 left

💡 Hint

Common Mistakes

Using a variable name not defined in the loop.

Mixing keys and values incorrectly.

The comprehension iterates over topic names as 'topic', maps each to its partition count 'topics[topic]', and filters where partitions > 1.

Practice

1. What is the main purpose of Confluent Cloud in Kafka usage?

easy

A. It provides a managed Kafka service for easy data streaming.

B. It is a tool to write SQL queries on Kafka topics.

C. It is a database for storing Kafka messages permanently.

D. It is a programming language for Kafka applications.

Solution

1. Step 1: Understand Confluent Cloud's role

   Confluent Cloud is described as a managed Kafka service that simplifies data streaming.

2. Step 2: Compare options with this role

   Only It provides a managed Kafka service for easy data streaming. matches this description; others describe unrelated tools or concepts.

3. Final Answer:

   It provides a managed Kafka service for easy data streaming. -> Option A

4. Quick Check:

   Managed Kafka service = It provides a managed Kafka service for easy data streaming. [OK]

Hint: Remember: Confluent Cloud manages Kafka for you [OK]

Common Mistakes:

• Confusing Confluent Cloud with a database
• Thinking it is a programming language
• Assuming it runs SQL queries directly

2. Which of the following is the correct way to describe a Kafka topic in Confluent Cloud?

easy

A. A topic is a user account in Confluent Cloud.

B. A topic is a programming function to send messages.

C. A topic is a type of database index.

D. A topic is a place where messages are stored and organized.

Solution

1. Step 1: Define Kafka topic concept

   A Kafka topic is a category or feed name to which messages are published and stored.

2. Step 2: Match definition to options

   A topic is a place where messages are stored and organized. correctly states that a topic stores and organizes messages; others are incorrect.

3. Final Answer:

   A topic is a place where messages are stored and organized. -> Option D

4. Quick Check:

   Topic = message storage location [OK]

Hint: Topics hold messages, not functions or users [OK]

Common Mistakes:

• Confusing topics with user accounts
• Thinking topics are functions or indexes
• Mixing topics with database concepts

3. Given the following code snippet for producing a message in Confluent Cloud Kafka client:

producer.produce(topic='orders', value='order123')

What happens when this code runs successfully?

medium

A. The 'orders' topic is deleted.

B. The message 'order123' is sent to the 'orders' topic.

C. The producer client shuts down.

D. An error occurs because 'value' must be a number.

Solution

1. Step 1: Understand produce method

   The produce method sends a message to a specified topic with the given value.

2. Step 2: Analyze the code behavior

   Here, 'order123' is sent as a message to the 'orders' topic; no deletion or shutdown occurs.

3. Final Answer:

   The message 'order123' is sent to the 'orders' topic. -> Option B

4. Quick Check:

   Produce sends message to topic [OK]

Hint: Produce sends data to topic, no deletion or shutdown [OK]

Common Mistakes:

• Thinking produce deletes topics
• Assuming value must be numeric
• Confusing produce with client shutdown

4. You wrote this code to consume messages from a Confluent Cloud topic:

consumer.subscribe(['payments'])
message = consumer.poll(1.0)
print(message.value())

But you get an error: 'NoneType' object has no attribute 'value'. What is the likely cause?

medium

A. The print statement syntax is incorrect.

B. The topic 'payments' does not exist.

C. No messages were available to consume during poll timeout.

D. The consumer client was not connected to Confluent Cloud.

Solution

1. Step 1: Understand poll method behavior

   poll returns None if no messages are received within the timeout period.

2. Step 2: Analyze error cause

   Calling value() on None causes the error; this means no messages arrived during poll.

3. Final Answer:

   No messages were available to consume during poll timeout. -> Option C

4. Quick Check:

   poll returns None if no messages [OK]

Hint: poll returns None if no messages, check before accessing [OK]

Common Mistakes:

• Assuming topic absence causes this error
• Blaming connection issues without checking poll
• Thinking print syntax is wrong

5. You want to create a Confluent Cloud Kafka topic that automatically deletes messages after 7 days. Which configuration should you apply when creating the topic?

hard

A. Set the topic's retention.ms to 604800000 (7 days in milliseconds).

B. Set the topic's cleanup.policy to 'compact'.

C. Set the topic's max.message.bytes to 7.

D. Set the topic's partitions to 7.

Solution

1. Step 1: Understand retention.ms setting

   retention.ms controls how long messages are kept before deletion, in milliseconds.

2. Step 2: Calculate 7 days in milliseconds

   7 days x 24 hours x 60 minutes x 60 seconds x 1000 = 604800000 ms.

3. Step 3: Match configuration to requirement

   Setting retention.ms to 604800000 ensures messages delete after 7 days; other options do not control retention time.

4. Final Answer:

   Set the topic's retention.ms to 604800000 (7 days in milliseconds). -> Option A

5. Quick Check:

   retention.ms = 7 days in ms [OK]

Hint: Use retention.ms for message lifetime in ms [OK]

Common Mistakes:

• Confusing cleanup.policy with retention time
• Setting max.message.bytes instead of retention
• Changing partitions unrelated to retention