Amazon MSK in Kafka - Mini Project: Build & Apply

Amazon MSK Basic Producer and Consumer

📖 Scenario: You are working with Amazon Managed Streaming for Apache Kafka (MSK) to send and receive messages in a real-time application. You will create a simple Kafka producer and consumer setup to understand how data flows through MSK.

🎯 Goal: Build a basic Kafka producer that sends messages to a topic and a consumer that reads messages from that topic using Amazon MSK.

📋 What You'll Learn

Create a Kafka topic named test-topic

Write a producer script that sends 3 specific messages to test-topic

Write a consumer script that reads messages from test-topic

Print the consumed messages to the console

💡 Why This Matters

🌍 Real World

Amazon MSK is used to build real-time data pipelines and streaming applications that require reliable message delivery and scalability.

💼 Career

Understanding how to produce and consume messages with Amazon MSK is essential for roles in data engineering, backend development, and cloud architecture.

1

Create Kafka topic configuration

Create a variable called topic_name and set it to the string 'test-topic'.

Kafka

# Create a variable called topic_name and set it to 'test-topic'
topic_name = ''
# Your code here

Hint

Use a simple string assignment to set the topic name.

2

Set up Kafka producer messages

Create a list called messages containing these exact strings: 'Hello MSK', 'Kafka is cool', and 'Streaming data'.

Kafka

topic_name = 'test-topic'
# Create a list called messages with the specified strings
messages = []
# Your code here

Hint

Use a Python list with the exact strings in the correct order.

3

Write Kafka producer loop to send messages

Write a for loop using message as the iterator to send each message in messages to the Kafka topic topic_name using producer.send(topic_name, value=message.encode()). Assume producer is already created.

Kafka

topic_name = 'test-topic'
messages = ['Hello MSK', 'Kafka is cool', 'Streaming data']
# Send each message to the Kafka topic using producer.send
# Your code here

Hint

Use a for loop to iterate over messages and send each one encoded as bytes.

4

Consume and print messages from Kafka topic

Write a for loop using msg as the iterator to consume messages from consumer. For each msg, print the decoded message value using print(msg.value.decode()). Assume consumer is already subscribed to topic_name.

Kafka

topic_name = 'test-topic'
messages = ['Hello MSK', 'Kafka is cool', 'Streaming data']
for message in messages:
    producer.send(topic_name, value=message.encode())
# Consume messages from consumer and print each decoded message
# Your code here

Hint

Use a for loop to read messages from consumer and print each decoded message.

Practice

1. What is the main benefit of using Amazon MSK for Kafka users?

easy

A. It manages Kafka servers for you, so you don't have to.

B. It replaces Kafka with a different messaging system.

C. It requires you to manually configure all Kafka brokers.

D. It only works with AWS Lambda functions.

Solution

1. Step 1: Understand Amazon MSK's purpose

   Amazon MSK is a managed service that runs Kafka clusters for you.

2. Step 2: Compare options with MSK features

   Only It manages Kafka servers for you, so you don't have to. correctly states that MSK manages Kafka servers, removing manual server management.

3. Final Answer:

   It manages Kafka servers for you, so you don't have to. -> Option A

4. Quick Check:

   Managed Kafka service = It manages servers [OK]

Hint: Remember MSK means managed Kafka servers [OK]

Common Mistakes:

• Thinking MSK replaces Kafka
• Assuming manual server setup is needed
• Believing MSK only works with Lambda

2. Which of the following is the correct way to specify the bootstrap servers when connecting to an Amazon MSK cluster in Kafka client configuration?

easy

A. "localhost:9092"

B. "msk://cluster-endpoint"

C. "127.0.0.1:2181"

D. "b-1.mskcluster.abcd1234.kafka.us-east-1.amazonaws.com:9092,b-2.mskcluster.abcd1234.kafka.us-east-1.amazonaws.com:9092"

Solution

1. Step 1: Identify MSK cluster endpoints format

   Amazon MSK provides bootstrap servers as DNS names with ports, like in "b-1.mskcluster.abcd1234.kafka.us-east-1.amazonaws.com:9092,b-2.mskcluster.abcd1234.kafka.us-east-1.amazonaws.com:9092".

2. Step 2: Eliminate incorrect formats

   "localhost:9092" is localhost, not MSK. "127.0.0.1:2181" is Zookeeper port, not Kafka. "msk://cluster-endpoint" is not a valid Kafka bootstrap server format.

3. Final Answer:

   "b-1.mskcluster.abcd1234.kafka.us-east-1.amazonaws.com:9092,b-2.mskcluster.abcd1234.kafka.us-east-1.amazonaws.com:9092" -> Option D

4. Quick Check:

   MSK bootstrap servers = DNS names with ports [OK]

Hint: MSK bootstrap servers are DNS names with port 9092 [OK]

Common Mistakes:

• Using localhost instead of MSK endpoints
• Confusing Zookeeper port with Kafka port
• Using invalid URI schemes like msk://

3. Given the following Kafka producer code snippet connecting to Amazon MSK, what will be the output if the message is sent successfully?

producer.send(new ProducerRecord<>("my-topic", "key1", "Hello MSK"));
System.out.println("Message sent successfully");

medium

A. Error: Connection refused

B. Message sent successfully

C. No output

D. Message failed to send

Solution

1. Step 1: Understand producer.send behavior

   The send method is asynchronous but the print statement runs immediately after.

2. Step 2: Check output after send call

   Since no error handling is shown and send is called, the print statement will output "Message sent successfully".

3. Final Answer:

   Message sent successfully -> Option B

4. Quick Check:

   Producer send + print = Message sent successfully [OK]

Hint: Print after send shows success unless exception thrown [OK]

Common Mistakes:

• Assuming send blocks until confirmed
• Expecting error without exception handling
• Thinking no output means success

4. You have this Kafka consumer code connecting to Amazon MSK:

Properties props = new Properties();
props.put("bootstrap.servers", "b-1.mskcluster.kafka:9092");
props.put("group.id", "test-group");
props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
KafkaConsumer consumer = new KafkaConsumer<>(props);
consumer.subscribe(Collections.singletonList("my-topic"));
consumer.poll(Duration.ofMillis(100));

The consumer throws a runtime error about deserializer class not found. What is the likely cause?

medium

A. The topic name is invalid.

B. The bootstrap server address is wrong.

C. The deserializer class names are incorrect or misspelled.

D. The group.id property is missing.

Solution

1. Step 1: Analyze the error message

   The error says deserializer class not found, so the problem is with deserializer class names.

2. Step 2: Check deserializer class names in code

   They must be fully qualified and spelled exactly. Any typo causes class not found error.

3. Final Answer:

   The deserializer class names are incorrect or misspelled. -> Option C

4. Quick Check:

   Deserializer class error = wrong class name [OK]

Hint: Check spelling of deserializer class names first [OK]

Common Mistakes:

• Ignoring class name typos
• Assuming bootstrap server causes deserializer error
• Missing group.id but error is about deserializer

5. You want to create a Kafka consumer in Java that connects to an Amazon MSK cluster and only processes messages with keys starting with "user-". Which approach correctly applies this filter after receiving messages?

hard

A. Use a Kafka Streams application with a filter on the key prefix.

B. Set the consumer property "key.filter.prefix" to "user-".

C. Subscribe only to topics named "user-*".

D. Configure the producer to send only keys starting with "user-".

Solution

1. Step 1: Understand Kafka consumer filtering options

   Kafka consumers do not support filtering by key prefix via configuration properties.

2. Step 2: Identify correct filtering method

   Kafka Streams allows processing and filtering messages by key prefix programmatically.

3. Step 3: Evaluate other options

   There is no Kafka consumer property like "key.filter.prefix". Subscribing to topics named "user-*" filters by topic name, not message keys. Producer configuration controls what is sent, not what the consumer processes.

4. Final Answer:

   Use a Kafka Streams application with a filter on the key prefix. -> Option A

5. Quick Check:

   Filter keys after consuming = Kafka Streams filter [OK]

Hint: Filter keys in Kafka Streams, not consumer config [OK]

Common Mistakes:

• Expecting consumer config to filter keys
• Filtering by topic name instead of message key
• Trying to filter on producer side only