Kafka Topics

A Topic is a unit or component where streaming and publishing data is stored. Multiple streaming data can be stored and can be published to one or more channels or consumers. The Kafka Topics dashboard displays a list view of all topics created in the Kafka cluster.

You can view the following metrics for existing topics in a Kafka cluster.

Note

Click a topic to view the Kafka Topic Details page.

Adding Metrics

By clicking on the Table Settings icon on the right side of the screen, you can now add the appropriate metrics. The following example demonstrates this.


Metric

Description

Name

The name of the topic.

Online

This state shows that the Kafka topic is online and receiving messages from the producer.

# of Partitions

Number of partitions created in the topic.

Replication Factor

Defines the number of copies a topic has in a Kafka cluster. These copies are used in the event of a failover. If Replication Factor is N, Kafka can tolerate up to N-1 failures.

% in sync

The percentage value at which the topics are in sync with the topics in replication factor.

Data In/Out

Amount of data streamed in and streamed out of a topic.

Total Replica Fetcher Lag

The Fetcher Lag measures the lag in the quantity of messages per follower replica.

Bytes In Mean Rate

Average rate of incoming data.

Bytes Out Mean Rate

Average rate of outgoing data.

# of Consumers

Number of consumers or subscribers of a topic.

# of Consumer Groups

Number of groups fetching data from a topic.

Consumer Lag

Represents how far the consumer unit is from fetching data from the producer.

Unassigned Leaders

Number of partitions with leaders not assigned.

Retention

The time limit for message retention. Messages get discarded after the displayed period. Note If no values are displayed, then the default value is taken for retention.

Avg Size

The average partition size of a topic.

Under Replicated

Number of partitions that are under replicated.

Total Size

The total size of the topic.

# Offline Partitions

Number of offline (unavailable) partitions.

Min Fetch Lag

Minimum lag between the current consumer offset and the highest offset.

Max Fetch Lag

Maximum lag between the current consumer offset and the highest offset.

Tips

Click to download the metrics data in XLSX format.

Click on Table Settings on the top right corner to view and select columns.

Grouping by Brokers

To group the topics by Brokers, click the Group by drop down and select Brokers.

Grouping by Brokers displays the following metrics.

Note

To view the topics in a broker, click the row of a broker.

Metric

Description

Broker Id

The ID of the broker in the Kafka cluster.

# of Partitions

Number of partitions created in the broker.

# of Leaders

Number of leaders that Zookeeper elects for coordination.

Under Replicated Partitions

Number of partitions yet to be replicated.

Bytes in/out

Amount of incoming and outgoing data.

Request Handler Idle Ratio

Ratio of time or fraction of time at which the request handler is idle. The values can be 0 or 1 or any value between 0 and 1. 0 represents that no resources are available to use and 1 represents that all resources are available.