Contents
- 1 How do I monitor my Kafka messages?
- 2 How do I monitor Kafka metrics?
- 3 How do I monitor Kafka with Grafana?
- 4 How do I check Kafka latency?
- 5 How do I monitor confluent Kafka?
- 6 Can Grafana connect to Kafka?
- 7 Which is the best tool for Kafka cluster management?
- 8 How to start a Kafka monitor on GitHub?
- 9 What’s the purpose of the Kafka monitor framework?
How do I monitor my Kafka messages?
Key Kafka metrics to monitor
- Messages in/out.
- Network handler idle time.
- Request handler idle time.
- Under-Replicated partitions.
- Leader Elections.
- CPU idle time.
- Host Network in/out.
How do I monitor Kafka metrics?
Top 10 Kafka Metrics to Focus on First
- Network Request Rate.
- Network Error Rate.
- Under-replicated Partitions.
- Offline Partition Count.
- Total Broker Partitions.
- Log Flush Latency.
- Consumer Message Rate.
- Consumer Max Lag.
How do I monitor Kafka with Grafana?
Let’s get to it!
- Import the dashboards into Grafana using JSON files.
- Log in to your Grafana instance from the web browser.
- Navigate to Dashboards > Manage.
- Click Import.
- Click Upload .
- Import the relevant dashboard ( kafka-overview.
How do I view a Kafka topic?
How to check if Kafka topics and data is created
- Run the command to log on to the Kafka container: kubectl exec -it broker-0 bash -n
- Run the command to list the Kafka topics: ./bin/kafka-topics.sh –list –zookeeper itom-di-zk-svc:2181.
How many messages can Kafka handle?
Also, since Aiven Kafka services are offered only over encrypted TLS connections, we included the configuration for these, namely the required certificates and keys. librdkafka defaults to a maximum batch size of 10000 messages or to a maximun request size of one million bytes per request, whichever is met first.
How do I check Kafka latency?
The simplest way to check the offsets and lag of a given consumer group is by using the CLI tools provided with Kafka. In the diagram above, you can see the details on a consumer group called my-group . The command output shows the details per partition within the topic.
How do I monitor confluent Kafka?
Apache Kafka® brokers and clients report many internal metrics. JMX is the default reporter, though you can add any pluggable reporter. You can deploy Confluent Control Center for out-of-the-box Kafka cluster monitoring so you don’t have to build your own monitoring system.
Can Grafana connect to Kafka?
The integration with Kafka is available now for Grafana Cloud users. If you’re not already using Grafana Cloud, we have new free and paid plans to suit every use case — sign up for free now. It’s the easiest way to get started observing metrics, logs, traces, and dashboards.
How do I view kafka partitions?
Go to your kafka/bin directory. You should see what you need under PartitionCount . Note that I just needed to pull out partition IDs, but you can additionally retrieve any other partition metadata, like leader , isr , replicas , And BrokerInfo is just a simple POJO that has host and port fields.
Which is the open source monitoring tool for Apache Kafka?
Other views provide overviews of cluster load and underlying server resource usage statistics. Burrow is an open source monitoring tool to track consumer lag in Apache Kafka clusters.
Which is the best tool for Kafka cluster management?
Kafka Tool Kafka Tool is a GUI framework for Apache Kafka cluster management and use. It offers an intuitive user interface that easily accesses objects in a Kafka cluster and the cluster topics’ messages. This provides functionality targeted at developers and administrators.
How to start a Kafka monitor on GitHub?
You begin by cloning and building the GitHub repository: The bin/kafka-monitor-start.sh script is used to run Kafka Monitor and begin executing checks against your Kafka clusters. Although it uses the word “test”, this implies a runtime monitoring check.
What’s the purpose of the Kafka monitor framework?
As described on the Kafka Monitor GitHub page, the goal of the Kafka Monitor framework is to make it as easy as possible to develop and execute long-running Kafka-specific system tests in real clusters and monitor application performance.