Kafka, a distributed event streaming platform, can be run in various environments, including containerized setups, and is often used alongside ZooKeeper for storing configuration information. Monitoring Kafka involves tracking both the Kafka brokers and the associated ZooKeeper instances using tools like Elastic Observability, Metricbeat, and Filebeat. Kafka operates on a publish/subscribe model where events are published to topics, and consumers subscribe to these topics to receive updates. The system can be configured to control message distribution among consumers using consumer groups and partitions, with consumer lag being a critical metric indicating the need for additional consumers if it perpetually increases. The blog emphasizes the importance of using hints-based autodiscovery for dynamic monitoring in containerized environments, allowing Metricbeat and Filebeat to gather service-specific logs and metrics without manual reconfiguration. Additionally, Jolokia is used for retrieving JMX-based metrics from Kafka brokers, which are then processed through an Elasticsearch ingest pipeline to enhance data visualization capabilities in Kibana. This setup enables comprehensive monitoring and visualization of Kafka and ZooKeeper performance, ensuring efficient management of the streaming platform.