As it runs, WebLogic Server generates a rich set of metrics and runtime state information that provides detailed performance and diagnostic data about the servers, clusters, applications, and other resources that are running in a WebLogic domain. To give our users the best possible experience when running WebLogic domains in Docker/Kubernetes environments, we have developed the WebLogic Monitoring Exporter. This new tool exposes WebLogic Server metrics that can be read and collected by monitoring tools such as Prometheus, and displayed in Grafana.
We are also making the WebLogic Monitoring Exporter tool available as open source on GitHub, which will allow our community to contribute to this project and be part of enhancing it.
The WebLogic Monitoring Exporter is implemented as a web application that is deployed to the WebLogic Server instances that are to be monitored. The exporter uses the WebLogic Server 12.2.1.x RESTful Management Interface for accessing runtime state and metrics. With a single HTTP query, and no special setup, it provides an easy way to select the metrics that are monitored for a managed server.
For detailed information about the design and implementation of the WebLogic Monitoring Exporter, see Exporting Metrics from WebLogic Server.
Prometheus collects the metrics that have been scraped by the WebLogic Monitoring Exporter. By constructing Prometheus-defined queries, you can generate any data output you require to monitor and diagnose the servers, applications, and resources that are running in your WebLogic domain.
We can use Grafana to display these metrics in graphical form. Connect Grafana to Prometheus, and create queries that take the metrics scraped by the WebLogic Monitoring Exporter and display them in dashboards.
For more information, see Using Prometheus and Grafana to Monitor WebLogic Server on Kubernetes.
Get started building and deploying the WebLogic Monitoring Exporter, setup Prometheus and Grafana, and monitor the metrics from the WebLogic Managed servers in a domain/cluster running in Kubernetes.
We welcome you to try this out. It's a good start to making the transition to open source monitoring tools. We can work together to enhance it and take full advantage of its functionality in Docker/Kubernetes environments.
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