Apache Kafka is a distributed system where a topic is partitioned as well as replicated across various nodes. It also supports fault tolerance as well as durability. There may be chances of troubleshooting. Therefore, it is required to manage and monitor different Kafka activities. Various Kafka monitoring tools are used to monitor and display the corrective actions.
There are following activities performed under Kafka monitoring:
1) Keeping tracks of utilized system resources
The Kafka application manager enables users to monitor and discover the Kafka servers automatically. It also tracks the details of resource utilization, such as disk storage, CPU, memory, etc. This helps the manager to ensure that the user is not running out of resources The manager also ensures that the server is operating continuously with the alerts, sent whenever an increment in the resource consumption occurs.
2) Keeps an eye on threads and JVM usage
Apache Kafka depends on the java garbage collector for freeing up memory. It is because the java application runs in the java virtual machine generally. Thus, more activities performed in the Kafka cluster leads to more execution of the garbage collector. It becomes simple to track JVM heap sizes using the monitoring tool. The tool also allows the user to track the thread utilization with the metrics such as peak, live thread count and, daemon. This prevents the system performance.
3) Understands controller, broker, and replication statistics
In the Kafka cluster, there is only one leader(broker) which controls and manages the partitions and replicas state. It becomes easy to view the active leader with the Kafka monitoring tools. The active controllers can find out the active leader at the time of some issue. The application manager also monitors the Log flush latency of the broker. The Log flush latency is directly proportional to the number of pipelines.
4) Monitors the network as well as Topic Details
The application manager monitoring tool keeps the record of the network usage and aggregates outgoing and incoming byte rate on the broker topics in order to gather more information.
5) Manages faults and troubleshoot fastly
Apache Kafka has the feature of fault tolerance. Therefore, it becomes easy to determine and analyze the faults. This increases the performance of the Kafka Cluster.
6) Provides data-rich reports on each performance metrics
The Kafka monitoring tool creates evaluated reports on each necessary performance attributes. These extensive reports help users to know the overall performance metrics.
Note: Apache Kafka offers remote monitoring feature also. This feature is enabled through JMX by setting an environment variable 'JMX_PORT'. It performs graphs and alerts on the essential Kafka metrics. Visit the documentation of the official website of the Apache Kafka to know more.