Prometheus and Grafana integration in Kafka - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to expose Kafka metrics for Prometheus scraping.

Kafka

metricsReporter = new [1]();

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

APrometheusReporter

BJmxReporter

CConsoleReporter

DSlf4jReporter

Attempts:

3 left

💡 Hint

Common Mistakes

Using JmxReporter which exposes JMX metrics but not Prometheus format.

Using ConsoleReporter which prints metrics to console only.

The PrometheusReporter exposes Kafka metrics in a format Prometheus can scrape.

2fill in blank

medium

Complete the Prometheus scrape configuration to monitor Kafka metrics.

Kafka

- job_name: 'kafka'
  static_configs:
    - targets: ['[1]']

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

Alocalhost:7071

Blocalhost:9092

Clocalhost:8080

Dlocalhost:1234

Attempts:

3 left

💡 Hint

Common Mistakes

Using Kafka broker port 9092 which is for client connections, not metrics.

Using random ports like 8080 or 1234.

Kafka Prometheus metrics are usually exposed on port 7071 by default.

3fill in blank

hard

Fix the error in the Grafana data source URL for Prometheus.

Kafka

url = 'http://[1]/api/v1';

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

Alocalhost:9090

Bprometheus:8080

Cprometheus:9090

Dlocalhost:8081

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong port like 8080 or 8081.

Using localhost when Prometheus runs in a container named 'prometheus'.

Grafana connects to Prometheus at port 9090, the default Prometheus port.

4fill in blank

hard

Complete the code to create a Prometheus alert rule for Kafka consumer lag.

Kafka

alert: KafkaConsumerLagHigh
expr: kafka_consumer_lag > [1]
for: 5m

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

B1000

C100

Dsum

Attempts:

3 left

💡 Hint

Common Mistakes

Adding operators like 'sum' directly after metric name.

Using too low threshold like 100 which may cause false alerts.

The expression checks if kafka_consumer_lag is greater than 1000. No extra operator is needed after the metric name.

5fill in blank

hard

Fill all three blanks to configure Kafka JMX exporter for Prometheus.

Kafka

jmx_prometheus_javaagent=[1]=[2]:[3]

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

Ajavaagent.jar

Blocalhost

C7071

Dkafka-jmx-exporter.jar

Attempts:

3 left

💡 Hint

Common Mistakes

Using generic javaagent.jar instead of Kafka specific jar.

Wrong host or port for metrics endpoint.

The JMX exporter jar is kafka-jmx-exporter.jar, running on localhost at port 7071.

Practice

1. What is the main role of Prometheus in Kafka monitoring when integrated with Grafana?

easy

A. To collect Kafka metrics by scraping the metrics endpoint

B. To display visual dashboards of Kafka metrics

C. To send alerts directly to Kafka topics

D. To store Kafka messages for backup

Solution

1. Step 1: Understand Prometheus function

   Prometheus collects metrics by scraping endpoints exposed by applications like Kafka.

2. Step 2: Differentiate roles of Prometheus and Grafana

   Grafana is used for visualization, not data collection.

3. Final Answer:

   To collect Kafka metrics by scraping the metrics endpoint -> Option A

4. Quick Check:

   Prometheus collects metrics = A [OK]

Hint: Remember: Prometheus collects, Grafana displays [OK]

Common Mistakes:

• Confusing Grafana as the collector
• Thinking Prometheus stores Kafka messages
• Assuming Prometheus sends alerts to Kafka

2. Which of the following is the correct Prometheus scrape configuration snippet to monitor Kafka metrics exposed at port 9090?

easy

A. - job_name: 'kafka'\n static_configs:\n - targets: ['localhost:9090']

B. - job_name: 'kafka'\n static_configs:\n - targets: ['localhost:2181']

C. - job_name: 'kafka'\n static_configs:\n - targets: ['localhost:8080']

D. - job_name: 'kafka'\n static_configs:\n - targets: ['localhost:1234']

Solution

1. Step 1: Identify Kafka metrics port

   Kafka metrics exporter commonly exposes metrics on port 9090.

2. Step 2: Match correct target in Prometheus config

   Only - job_name: 'kafka'\n static_configs:\n - targets: ['localhost:9090'] uses port 9090, which is correct for scraping Kafka metrics.

3. Final Answer:

   - job_name: 'kafka'\n static_configs:\n - targets: ['localhost:9090'] -> Option A

4. Quick Check:

   Port 9090 for Kafka metrics = A [OK]

Hint: Kafka metrics usually on port 9090, check targets carefully [OK]

Common Mistakes:

• Using Kafka broker port 2181 (Zookeeper port) instead of metrics port
• Confusing HTTP ports like 8080 for metrics
• Using random ports not related to Kafka metrics

3. Given this Prometheus query to monitor Kafka consumer lag:
sum(kafka_consumer_group_lag) by (group)
What output will this query produce?

medium

A. Current CPU usage of Kafka brokers

B. Total lag per consumer group as a number

C. Number of active Kafka brokers

D. List of all Kafka topics with their lag

Solution

1. Step 1: Understand the metric and aggregation

   The metric kafka_consumer_group_lag measures lag per consumer group and partition. Summing by group aggregates lag per group.

2. Step 2: Interpret the query output

   The query returns total lag number for each consumer group, not topics or CPU usage.

3. Final Answer:

   Total lag per consumer group as a number -> Option B

4. Quick Check:

   sum by group = total lag per group [OK]

Hint: sum(... by (group)) means total per group [OK]

Common Mistakes:

• Thinking it lists topics instead of groups
• Confusing lag with broker count
• Assuming CPU metrics from Kafka lag metric

4. You configured Prometheus to scrape Kafka metrics but Grafana shows no data. Which is the most likely cause?

medium

A. Prometheus scrape interval is too short

B. Grafana dashboard is not connected to Prometheus

C. Kafka metrics endpoint is not exposed or unreachable

D. Kafka broker is down

Solution

1. Step 1: Check Prometheus scraping setup

   If Kafka metrics endpoint is not exposed or unreachable, Prometheus cannot collect data.

2. Step 2: Understand impact on Grafana

   Without data in Prometheus, Grafana dashboards show no metrics.

3. Final Answer:

   Kafka metrics endpoint is not exposed or unreachable -> Option C

4. Quick Check:

   No data means no scrape target reachable [OK]

Hint: No data? Check if metrics endpoint is reachable first [OK]

Common Mistakes:

• Blaming Grafana connection before checking Prometheus data
• Assuming Kafka broker down always causes no data
• Thinking scrape interval too short causes no data

5. You want to create a Grafana dashboard showing Kafka broker CPU usage and consumer lag side by side. Which data sources and queries should you use?

hard

A. Connect Grafana to Prometheus; use queries kafka_cpu_usage and kafka_topic_lag

B. Connect Grafana directly to Kafka; use queries kafka_cpu and kafka_lag

C. Connect Grafana to Kafka Connect; use queries cpu_usage and consumer_lag

D. Connect Grafana to Prometheus; use queries kafka_broker_cpu_usage and sum(kafka_consumer_group_lag) by (group)

Solution

1. Step 1: Identify correct data source for metrics

   Prometheus collects Kafka metrics; Grafana connects to Prometheus for queries.

2. Step 2: Choose correct metric names and queries

   Common metrics are kafka_broker_cpu_usage and kafka_consumer_group_lag aggregated by group.

3. Final Answer:

   Connect Grafana to Prometheus; use queries kafka_broker_cpu_usage and sum(kafka_consumer_group_lag) by (group) -> Option D

4. Quick Check:

   Prometheus + correct queries = C [OK]

Hint: Grafana queries Prometheus metrics, not Kafka directly [OK]

Common Mistakes:

• Trying to connect Grafana directly to Kafka brokers
• Using wrong metric names or unaggregated lag
• Confusing Kafka Connect with Kafka broker metrics