Key broker metrics in Kafka - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the role of the Broker in Kafka?

A Kafka broker is a server that stores data and serves clients. It handles read and write requests for topics and manages data replication.

beginner

What does the MessagesInPerSec metric measure in a Kafka broker?

It measures the number of messages the broker receives per second from producers.

intermediate

Explain the UnderReplicatedPartitions metric.

This metric shows how many partitions have fewer replicas in sync than expected, indicating potential data loss risk.

intermediate

What does the RequestHandlerAvgIdlePercent metric indicate?

It shows the average percentage of time the broker's request handler threads are idle, helping to understand broker load.

beginner

Why is monitoring BytesInPerSec and BytesOutPerSec important?

These metrics track the data volume flowing into and out of the broker, helping to detect bottlenecks or unusual traffic.

Which Kafka broker metric shows the number of messages received per second?

A RequestHandlerAvgIdlePercent

B BytesOutPerSec

C UnderReplicatedPartitions

D MessagesInPerSec

MessagesInPerSec counts how many messages the broker receives each second.

What does a high value in UnderReplicatedPartitions mean?

A Some partitions have fewer replicas than expected

B More partitions are fully replicated

C Broker is idle

D High message throughput

UnderReplicatedPartitions indicates partitions with fewer replicas in sync, which is risky.

If RequestHandlerAvgIdlePercent is very low, what does it suggest?

A Broker threads are mostly idle

B No messages are being processed

C Broker threads are mostly busy

D Broker is offline

Low idle percent means request handler threads are busy handling requests.

Which metric helps monitor the data volume sent from the broker to consumers?

A BytesInPerSec

B BytesOutPerSec

C MessagesInPerSec

D UnderReplicatedPartitions

BytesOutPerSec tracks data sent out from the broker.

Why is it important to monitor BytesInPerSec?

A To track data volume coming into the broker

B To measure broker CPU usage

C To check how many messages are consumed

D To count under-replicated partitions

BytesInPerSec measures the data volume entering the broker from producers.

Describe the key Kafka broker metrics you would monitor to ensure broker health and performance.

Think about message flow, replication status, and thread activity.

Explain why UnderReplicatedPartitions is critical for Kafka reliability.

Consider what happens if replicas are not in sync.

Practice

1.

What does the MessagesInPerSec metric in Kafka broker monitoring indicate?

easy

A. The number of messages the broker receives per second

B. The number of active connections to the broker

C. The total disk space used by the broker

D. The number of partitions in the broker

Solution

1. Step 1: Understand the metric name

   The metric MessagesInPerSec literally means messages coming in per second to the broker.

2. Step 2: Match the metric to its meaning

   This metric counts how many messages the broker receives every second, showing its input load.

3. Final Answer:

   The number of messages the broker receives per second -> Option A

4. Quick Check:

   MessagesInPerSec = messages received per second [OK]

Hint: Look for 'In' to find incoming message rate [OK]

Common Mistakes:

• Confusing message count with connection count
• Thinking it measures disk usage
• Mixing it up with partition count

2.

Which of the following is the correct JMX metric name to monitor the broker's outgoing bytes per second?

easy

A. MessagesOutPerSec

B. BytesInPerSec

C. BytesOutPerSec

D. BytesTotalPerSec

Solution

1. Step 1: Identify the direction of data flow

   Outgoing bytes means data sent out from the broker, so the metric should say 'Out'.

2. Step 2: Match the exact metric name

   The correct metric for outgoing bytes per second is BytesOutPerSec.

3. Final Answer:

   BytesOutPerSec -> Option C

4. Quick Check:

   Outgoing bytes = BytesOutPerSec [OK]

Hint: Look for 'Out' and 'Bytes' in metric name [OK]

Common Mistakes:

• Choosing BytesInPerSec which is incoming data
• Confusing messages with bytes
• Using a non-existent metric name

3.

Given the following JMX metric values for a Kafka broker:
MessagesInPerSec = 500
BytesInPerSec = 1024000
BytesOutPerSec = 2048000
What does this tell you about the broker's activity?

medium

A. The broker's incoming and outgoing bytes are equal

B. The broker is receiving more messages than it sends out

C. The broker is idle with no message traffic

D. The broker is sending out twice as much data as it receives in messages

Solution

1. Step 1: Analyze the metric values

   MessagesInPerSec is 500, BytesInPerSec is 1,024,000 bytes, BytesOutPerSec is 2,048,000 bytes.

2. Step 2: Compare incoming and outgoing bytes

   Outgoing bytes (2,048,000) is exactly twice the incoming bytes (1,024,000), meaning the broker sends out twice as much data as it receives.

3. Final Answer:

   The broker is sending out twice as much data as it receives in messages -> Option D

4. Quick Check:

   BytesOutPerSec = 2 x BytesInPerSec [OK]

Hint: Compare BytesOutPerSec and BytesInPerSec values [OK]

Common Mistakes:

• Ignoring the difference between bytes and messages
• Assuming equal incoming and outgoing bytes
• Misreading the numeric values

4.

Consider this snippet monitoring Kafka broker metrics in Java:

double bytesIn = jmxClient.getAttribute("kafka.server:type=BrokerTopicMetrics,name=BytesInPerSec");
double bytesOut = jmxClient.getAttribute("kafka.server:type=BrokerTopicMetrics,name=BytesOutPerSec");
if (bytesIn > bytesOut) {
    System.out.println("More incoming data");
} else {
    System.out.println("More outgoing data");
}

What is the likely bug in this code?

medium

A. The code does not handle the case when bytesIn equals bytesOut

B. The comparison should use >= to handle equal values

C. The metric names are incorrect and will cause an error

D. The JMX attribute values should be cast to int, not double

Solution

1. Step 1: Review the if-else logic

   The code checks if bytesIn is greater than bytesOut, else prints "More outgoing data".

2. Step 2: Identify missing case handling

   If bytesIn equals bytesOut, the else block runs, printing "More outgoing data" which is misleading.

3. Final Answer:

   The code does not handle the case when bytesIn equals bytesOut -> Option A

4. Quick Check:

   Equal values need explicit handling [OK]

Hint: Check if equal values are handled in if-else [OK]

Common Mistakes:

• Assuming metric names are wrong
• Ignoring equal value scenario
• Casting to wrong data type without error

5.

You want to alert if the Kafka broker's RequestHandlerAvgIdlePercent metric drops below 20%, indicating high load. Which approach correctly implements this check in pseudocode?

1. Fetch RequestHandlerAvgIdlePercent metric value
2. If value < 20 then alert 'High broker load'

hard

A. if (RequestHandlerAvgIdlePercent > 20) { alert('High broker load'); }

B. if (RequestHandlerAvgIdlePercent < 20) { alert('High broker load'); }

C. if (RequestHandlerAvgIdlePercent == 20) { alert('High broker load'); }

D. if (RequestHandlerAvgIdlePercent != 20) { alert('High broker load'); }

Solution

1. Step 1: Understand the metric meaning

   RequestHandlerAvgIdlePercent shows how idle the request handler threads are; lower means busier.

2. Step 2: Apply the alert condition

   If this value is less than 20%, it means the broker is busy, so alerting on < 20 is correct.

3. Final Answer:

   if (RequestHandlerAvgIdlePercent < 20) { alert('High broker load'); } -> Option B

4. Quick Check:

   Idle percent < 20 means high load [OK]

Hint: Alert when idle percent is less than threshold [OK]

Common Mistakes:

• Using greater than instead of less than
• Checking equality only
• Using not equal which triggers too often