As a result, teams become efficient as a single unit, but the byproduct of such performant autonomy is a lack of insight into other parts of the organization. Each team has certain responsibilities and is constantly searching for tools that can address specific requirements in the best possible way. But tools can tend to grow in number, require additional maintenance, and most importantly, create silos. As engineers we all love great tools that help our teams work productively, resolve problems faster, be better. And tell us what you’d like to see! You can chat with the Cloud Integrations team on our Community Slack.Tools. Stay tuned for future content on how to best utilize the Grafana Cloud integrations. It’s the easiest way to get started observing metrics, logs, traces, and dashboards.įor more information on monitoring and alerting on Grafana Cloud and Kafka, check out our docs or join the #integrations channel in the Grafana Community Slack. 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. The integration with Kafka is available now for Grafana Cloud users. This is a comprehensive dashboard covering a large range of your ksqldb cluster metrics: the number of active, running, stopped, and idle the status of each query the life of your cluster message throughput JMV metrics and more. The dashboard also shows the overall health of your Kafka Connect Cluster JVM. Going down, panels show more technical details about your tasks, such as network, IO, authentication, and connection statistics, along with batch size, offset, and task error metrics. This dashboard focuses on the Kafka Connect tasks, showing how many tasks are running, paused, failed, unassigned, and destroyed. This dashboard is focused on your Schema Registry, showing the number of registered, created, and deleted schemas along with JMV and throughput metrics. This dashboard gives you a general overview of your Zookeeper cluster, focusing on JMV metrics, number of nodes online, active connections, and throughput. It is fed by the external exporter, which is embedded in the Grafana Agent. This dashboard shows the consumption lag of each topic, including offset lag in quantity, estimated time in seconds, and message throughput per minute and second. This dashboard provides a deep dive into each topic’s health and shows the throughput in bytes and number of messages as well as the offsets. This is a comprehensive dashboard showing the overall healthiness of your Kafka cluster, including how many brokers are alive in the cluster metrics for your partitions JVM, throughput, requests, and response queues size Zookeeper connections and producer and consumer metrics. The details on how to configure the JMX Exporters and the Grafana Agent can be found here.īelow is a brief explanation of each dashboard. Only the lag consumption dashboard is fed by an external exporter, which is embedded in the Grafana Agent for ease of use. Most of the dashboards rely on collecting data through a JMX exporter running alongside each instance of your Kafka components, as an agent. Our Grafana Cloud integration, which is heavily based on this blog post from Confluent, provides dashboards for your Kafka Broker clusters, Zookeeper clusters, Kafka Connect clusters, Schema Registry clusters, and ksqldb clusters, along with a specific dashboard for topics information and consumption lag. Kafka is the most used event streaming platform worldwide, and its ecosystem includes a wide variety of pieces for data governance, querying, batch processing, and connectors. We are happy to announce that the Kafka integration is available for Grafana Cloud, our composable observability platform bringing together metrics, logs, and traces with Grafana.Īpache Kafka is an open source distributed event streaming platform that provides high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.
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