Five recommended excellent kafka visualization tools to help improve work efficiency

Essential tools to improve work efficiency: Five excellent Kafka visualization tool recommendations

Introduction:
In the era of rapid development of modern information technology, big data processing has become It is an essential tool for various industries to improve efficiency and create value. As a high-throughput distributed messaging system, Kafka is widely used in big data scenarios and provides reliable message delivery and processing capabilities. However, Kafka management and monitoring is a relatively tedious task, which requires the use of some excellent visualization tools to manage and monitor Kafka clusters and improve work efficiency. This article will recommend five excellent Kafka visualization tools and provide code examples to demonstrate their specific practicality.

1. Kafka Manager

Kafka Manager is an open source Kafka cluster management tool developed by Yahoo and contributed to the Apache Kafka community. Kafka Manager provides an intuitive and powerful interface for managing, monitoring, and operating Kafka clusters. The following is a sample code snippet that uses Kafka Manager to query topic information in a Kafka cluster:

val kafkaManager = ZkUtils.createKafkaManager(config)
val topics = kafkaManager.getClusterMetadata().get().topicsMetadata.map(_.topic)
topics.foreach(println)

2. Kafka Tool

Kafka Tool is a powerful visual Kafka management tool that can be used to create , modify and monitor Kafka topics, brokers and consumers, etc. Kafka Tool has an intuitive user interface that can easily monitor the status of the Kafka cluster and perform various management operations. The following is a sample code for using Kafka Tool to create a new Kafka topic:

./kafka-topics.sh --create --topic my_topic --partitions 3 --replication-factor 2 --zookeeper localhost:2181

3. Burrow

Burrow is a Kafka monitoring tool developed by LinkedIn, specifically used to monitor Kafka consumers ( Consumer) health status. It can inspect consumer groups in a Kafka cluster and provide real-time health reports and alerts. The following is a sample code snippet that uses Burrow to query consumer group information in a Kafka cluster:

curl -s localhost:8000/v2/kafka/local/consumer | jq '.status'

4. Kafka Eagle

Kafka Eagle is an open source Kafka management and monitoring tool with powerful Functional and user-friendly interface. Kafka Eagle can monitor the status of the Kafka cluster and consumer offset (Consumer Offset) in real time, and provides functions such as charts, reports, and alarms to assist management work. The following is a sample code snippet for using Kafka Eagle to query Kafka topics information:

Properties props = new Properties();
props.put("bootstrap.servers", "localhost:9092");
props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
AdminClient adminClient = KafkaAdminClient.create(props);
ListTopicsResult topicsResult = adminClient.listTopics();
KafkaFuture<Set<String>> names = topicsResult.names();
Set<String> topicNames = names.get();
topicNames.forEach(System.out::println);

5. Kafka Offset Monitor

Kafka Offset Monitor is a Kafka offset monitoring tool developed by the Yahoo team. Manage and monitor the consumption progress of Kafka consumer groups. It provides an intuitive user interface to help users monitor the consumption progress and latency of Kafka consumer groups on different partitions in real time. The following is a sample code for using Kafka Offset Monitor to query Kafka consumer group offset information:

curl http://localhost:8080/offsets/topic_name/group_id

Conclusion:
The five excellent Kafka visualization tools recommended above can help us manage and monitor Kafka more efficiently Cluster to improve work efficiency. Both beginners and experienced technicians can benefit from it. At the same time, the code examples of these tools also provide us with a better reference to facilitate secondary development and customization according to our own needs. I hope this article can provide some help to everyone in the management and monitoring of Kafka.

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