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Kafka Monitoring Tools

Kafka performance monitoring is crucial for ensuring optimum performance and availability of your Kafka clusters, given the exponential growth and increasing complexity of deployments. As Kafka runs on multiple partitions across nodes, scales dynamically, and handles large data volumes, managing and monitoring these clusters can be challenging. Kafka monitoring contributes to better uptime and cluster performance by tracking key metrics, identifying issues in real time and ensuring quick fixes.

Applications Manager offers production-ready Kafka monitoring suite that helps track the Kafka messaging ecosystem effectively and help organizations maintain high availability and efficiency in messaging and data transfer for seamless business operations. Designed to meet enterprise requirements, our Kafka monitoring tool aids you to reduce the time taken to resolve production issues, thereby allowing engineering teams to work more effectively in system deployment.

Applications Manager: The only Kafka monitoring tool you need

Whether you are a seasoned Kafka administrator or new to the ecosystem, Kafka monitoring software like Applications Manager can provide the visibility and control you need to keep your Kafka clusters running smoothly. Applications Manager's Kafka monitor allows you to keep track of following metrics in our Kafka monitoring dashboard:

Track the resource utilization of your Kafka servers

Obtain detailed insights into the resource usage statistics of your Kafka servers to get a clear idea of the utilization capacity of your Kafka server. With Applications Manager's Kafka monitoring, you can monitor key resource usage metrics, such as physical memory, virtual memory, and swap memory, to find out how much RAM your Kafka server is utilizing and get notified in case of a sudden increase in resource consumption. Also, get detailed stats on the JVM heap and non-heap memory of your Kafka server to discover how much data is being stored and to detect memory leaks, if any.

Kafka Monitoring - ManageEngine Applications Manager

Analyze thread usage details

Keep a close eye on the threads that are used in your Kafka servers to handle multiple messaging requests and prevent bottlenecks, such as memory overloads, thread deadlocks, and thread starvation. Applications Manager's Kafka monitoring helps you analyze thread details by tracking metrics such as daemon, peak, and live thread count to identify which thread is actually causing the issues in case of performance abnormalities.

Kafka Monitoring Tool - ManageEngine Applications Manager

Gain deep insights into the performance of your Kafka clusters

Monitor the core metrics of your Kafka clusters from Kafka dashboard and get in-depth visibility into the performance of the below components with Kafka cluster monitoring:

Broker statistics

Get complete information on the topics that are running within the broker of a Kafka cluster, and configure alerts in case any topic is performing abnormally. Keep a close eye on key metrics of your topics, such as bytes in or out, messages in, and failed fetch or produce requests, and compare their performance across topics to make informed decisions about allocating resources or load balancing among topics.

Applications Manager's Kafka topic monitoring tracks the following key metrics of Kafka topics:

Parameter Description
Log Details
Log Flush Rate The asynchronous disk log flush rate.
Broker Topic Metrics
Bytes In / Min The aggregate incoming byte rate (amount of data written to topic on this broker) per minute.
Bytes Out / Min The aggregate outgoing byte rate per minute.
Bytes Rejected / Min The amount of data in messages rejected by broker per minute.
Failed Fetch Requests / Min The number of data read requests from consumers that brokers failed to process for this topic per minute.
Failed Produce Requests / Min The number of requests from producer that have failed.
Messages In / Min The number of Messages that comes into the Kafka broker.
Replication Manager
IsrExpands / Min The number of "in-sync" replica expansions.
IsrShrinks / Min The number of "in-sync" replica shrinks.
Leader Count The number of partitions for which a particular host is the leader.
Partition Count The number of partitions in the cluster.
Under Replicated Partitions This indicates the number of partitions in the cluster are under-replicated.
Request Handler Avg Idle Percent The average fraction of time the request handler threads are idle.

Controller statistics

Obtain detailed information on the Kafka brokers that serve as the controller for managing the partitions, leaders, and replicas in a Kafka cluster. Keep track of active controllers to identify the broker that was the leader at the time the issue occurred in the cluster along with the exact count of offline partitions for quick troubleshooting and incident resolution.

Here are the key metrics of a Kafka controller that you need to keep an eye on:

Parameter Description
Kafka Controller Details
Active Controller Count Number of active controllers in the cluster.
Offline Partitions Count The number of unavailable partitions.
Leader Election Rate The rate of leader elections.
Unclean Leader Election Rate The rate of Unclean Leader Elections.

Network details

Obtain a comprehensive overview of the messaging details of your Kafka server and monitor the request throughput or total incoming and outgoing byte rate on your broker topics to identify possible bottlenecks and to take appropriate measures, such as implementing end-to-end compression for your messages, if required.

Here are the list of key metrics that need to be monitored in your Kafka network:

Parameter Description
Requests Process Rate
Request Produce / Min The number of messages written to topic on this broker.
Request Fetch Consumer / Min The amount of data that the consumers fetched from this topic on this broker.
Request Fetch Follower / Min The requests from brokers that are the followers of a partition to get new data.
Time Taken For Requests
Total Time Produce / Min The total time to serve the specified request.
Total Time Fetch Consumer / Min The total time that the consumers fetched data from this topic on this broker.
Total Time Fetch Follower / Min The total time that is taken by the followers of a partition to get new data
Network Processor Rate
Network Processor Avg Idle Percent / Min The average free capacity of the network processors per minutes.

Topic details

Get complete information on the topics that are running within the broker of a Kafka cluster, and configure alerts in case any topic is performing abnormally. Keep a close eye on key metrics of your topics, such as bytes in or out, messages in, and failed fetch or produce requests, and compare their performance across topics to make informed decisions about allocating resources or load balancing among topics.

Applications Manager monitors the following key metrics of Kafka topics:

Parameter Description
Topic Details
Topic Name Specifies the name of the topic.
Bytes in / Min The aggregate incoming byte rate (amount of data written to topic on this broker) per minute.
Bytes Out / Min The aggregate outgoing byte rate per minute.
Failed Fetch Requests / Min The total number of failed Fetch Requests per minute.
Failed Produce Requests / Min The total number of failed producer requests.
Messages In / Min The number of messages that comes into the Kafka broker.

Keep track of ZooKeeper performance metrics

Manage your Kafka clusters with Apache ZooKeeper by tracking clusters, brokers, and topic configurations, and also dealing with electing partition leaders. Since ZooKeeper stores metadata about Kafka’s brokers, topics, and partitions, and deals with administrative tasks such as electing partition leaders, keep a close eye on ZooKeeper metrics to prevent unwanted performance outages or slowness and to maintain a healthy Kafka cluster.

Kafka Monitoring Dashboard - ManageEngine Applications Manager

Intelligent alerting and reporting for faster incident resolution

Streamline incident detection and resolution by identifying performance issues in Kafka clusters, such as consumer lag or offline partitions, and receiving immediate notifications via email, text, or Slack. You can send these alerts to external incident management tools, such as ServiceNow or ManageEngine ServiceDesk Plus. You can also respond quickly to incidents by automating corrective actions, such as using webhooks to start external actions.

Leverage the power of machine learning for predictive reporting on Kafka cluster performance as well as AI-driven alerting and reporting capabilities to simplify Kafka performance monitoring and troubleshooting, ensuring uninterrupted business operations.

Kafka Performance Monitoring - ManageEngine Applications Manager

Simplify Kafka monitoring with Applications Manager

Unlock seamless Kafka monitoring experience with Applications Manager. Track all your critical Kafka performance indicators along with the rest of your applications stack. Get the latest version now!

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Common questions asked on Kafka monitoring

What is Apache Kafka monitoring and how do you monitor Kafka?

 

Kafka monitoring is the process of supervising the resource usage and underlying operations in Kafka to ensure its performance isn't affected. Kafka has grown considerably in terms of both volume and complexity, and being a crucial component in IT infrastructure, it's necessary to implement dedicated Kafka monitoring software—like ManageEngine Applications Manager—to track its operations, identify and resolve bottlenecks, and optimize performance.

What are the benefits of monitoring Kafka?

 

Monitoring Kafka helps ensure system uptime and optimum efficiency. Detailed insights on metrics like throughput, latency and resource consumption in real time help admins identify performance anomalies and rectify them promptly. Code-level visibility aids in troubleshooting issues quicker and ensure quick fixes. This improves Kafka availability and enhances end user experience. Utilizing historic analyses to predict Kafka performance promotes proactive Kafka management and comes handy while planning capacity and growth, ensuring smooth operation of Kafka clusters.

How much does it cost to monitor Kafka clusters?

 

Applications Manager's Kafka monitoring tool starts at $395/year to monitor up to 10 Kafka clusters. It is one of the most cost-effective Kafka monitoring solutions for your business and enables you to scale your monitoring as your Kafka deployment grows in size.

How do I set up Kafka monitoring in Applications Manager?

 

It's easy to set up Apache Kafka monitoring with Applications Manager. Just enable JMX on the Kafka broker and set up the Kafka monitor in Applications Manager by specifying the JMX credentials, including username, password, JMX port, and JNDI path.

What Kafka performance metrics can I collect with Applications Manager?

 

You can collect detailed Kafka monitoring metrics related to the health and performance of all the following Kafka components:

  • Kafka broker
  • Consumer
  • Producer
  • Controller
  • Topics
  • Network
  • Configuration
  • JVM usage
  • Threads

Refer to our Kakfa monitoring help page to learn more.

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