Grafana is an awesome visualization tool for seeing real-time metrics from your applications, and you can combine it with MicroProfile and similar tools to create one dashboard for multiple projects. Different projects use different names for metrics, however, so it is often necessary (and tedious) to handcraft the metrics for each project. Moreover, each project can expose its own custom metrics, and each MicroProfile vendor can also produce custom metrics, so there are many manual steps involved if you want to see all of your metrics in one place.
What if you could simply examine a running app and generate a dashboard with all of its exposed metrics? That is exactly what you can do with the MicroProfile Metrics Generator, a new open source tool that I created to dynamically generate Grafana dashboards for any MicroProfile project by capturing and monitoring all of your project metrics. Once you’ve created a dashboard, you can use it with Grafana, customize it to suit specific needs, and save it as a JSON file. You can also periodically regenerate your dashboards to bring in new metrics that you’ve exposed in your application.
In this article, you will learn how to do just that: Use the MicroProfile Metrics Generator to create a unified dashboard for all of your project’s metrics.
Continue reading “Generate automated Grafana metrics dashboards for MicroProfile apps”
Open Liberty 184.108.40.206 provides support for MicroProfile 3.3 which includes updates to MicroProfile Rest Client, Fault Tolerance, Metrics, Health, and Config. Improved developer experience is also achieved with support for yum/apt-get installs and the ability to track use patterns with JAX-RS 2.1.
Continue reading MicroProfile 3.3 now available on Open Liberty 220.127.116.11, brings updated features, yum/apt-get support, pattern tracking
Monitoring systems are usually composed of three layers: a database layer that hosts metrics data, a layer to display the stored metric data graphically in dashboards, and an alerting layer to send out notifications via methods such as email, on-call notification systems, and chat platforms. This article presents an overview of the components used in Red Hat OpenShift‘s Application Monitoring Operator, how to install them using the Operator, and an example of the Operator in action.
Continue reading “Understanding Red Hat OpenShift’s Application Monitoring Operator”
Air pollution is a major problem in many cities around the globe. Some people in Stuttgart, Germany have developed cheap smog sensors that people can install on their balconies and other convenient places and then report data to a central site. I have written about that on OpenSource.com. The data is sent to a central server, from where it is visualized on a map. At the time of writing the above article, there was no way of seeing how the value has changed over time. Meanwhile, there is a visualization of the last 24 hours available on the map.
Continue reading “Visualizing Smog Sensor Data with the help of Vert.x, Prometheus, and Grafana”