At that point, you might consider allocating more resources to the servers handling those services in the regions experiencing issues. Once you’ve identified the top countries with users experiencing long_tasks, you can dive deeper by examining the RUM events to see which services are showing slowdowns.
The below example shows the distribution of unique user sessions ( generating the most long_task events, which happen when a task blocks the main thread for at least 50 ms and could indicate high latency and degraded user experience.
Datadog automatically records the geographic location for all incoming RUM metrics, so you can group any RUM data by country ISO code ( to visualize it using a geomap. Geomaps are fully integrated with Datadog RUM, which means that you can use RUM Analytics to visualize frontend metrics, such as requests, latency, and errors, that impact user experience. log-based custom metrics to detect business patterns and guide development.application log data for security insights.RUM metrics to monitor frontend performance globally.In this post, we’ll look at how you can use geomaps to visualize: You can also map data from any of your log and custom metrics that contain an attribute with a value in the standard country ISO code format. You can use geomaps to visualize your frontend metrics from Datadog RUM out of the box. This provides key business and application performance insights and also helps you make informed decisions about where to focus any troubleshooting efforts. This helps you understand geographic patterns at a glance, including where users are experiencing outages, app revenue by country, or if a surge in requests is coming from one particular location.
Now, you can use Datadog geomaps to visualize data on a color-coded world map. It can provide visibility into where errors and latency might be occurring, where security threats might be originating, and more. Being able to track and aggregate data by region is important when monitoring your application.