Key broker metrics in Kafka - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to print the total number of messages produced to the broker.

Kafka

total_messages = broker_metrics.[1]

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

Amessages_in_per_sec

Bbytes_out_total

Cbytes_in_total

Dmessages_in_total

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing a per second rate metric instead of total count.

The messages_in_total metric shows the total number of messages produced to the broker.

2fill in blank

medium

Complete the code to get the current rate of bytes sent out by the broker per second.

Kafka

bytes_out_rate = broker_metrics.[1]

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

Abytes_out_total

Bmessages_out_per_sec

Cbytes_out_per_sec

Dbytes_in_per_sec

Attempts:

3 left

💡 Hint

Common Mistakes

Using total bytes instead of per second rate.

The bytes_out_per_sec metric gives the current rate of bytes sent out by the broker each second.

3fill in blank

hard

Fix the error in accessing the broker's request handler average idle percent.

Kafka

idle_percent = broker_metrics.[1]

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

Arequest_handler_avg_idle_percent

Brequest_handler_idle_avg_percent

Crequest_handler_avg_idle

Drequest_handler_idle_percent_avg

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing the order of words in the metric name.

The correct metric name is request_handler_avg_idle_percent which shows the average idle percent of request handlers.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each topic to its total bytes in.

Kafka

topic_bytes_in = {topic: broker_metrics[topic][1] for topic in topics if broker_metrics[topic][1] [2] 0}

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

A['bytes_in_total']

B>

C>= 0

D['messages_in_total']

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong metric keys or wrong comparison operators.

The first blank accesses the bytes_in_total metric for each topic. The second blank filters topics with bytes in greater than zero.

5fill in blank

hard

Fill all three blanks to create a filtered dictionary of topics with messages in per second greater than 1000, mapping topic to that rate.

Kafka

high_rate_topics = { [1] : broker_metrics[[2]][3] for [2] in topics if broker_metrics[[2]][3] > 1000 }

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

Atopic

B'messages_in_per_sec'

C[ 'messages_in_per_sec' ]

Dmessages_in_per_sec

Attempts:

3 left

💡 Hint

Common Mistakes

Using variable names instead of string keys for metrics.

The dictionary maps each topic to its messages_in_per_sec metric value. The metric is accessed with square brackets and the string key.

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