Operations | Monitoring | ITSM | DevOps | Cloud

If you've ever had a Java application slow down in production and struggled to pinpoint the cause, you know the pain of performance issues. Java is a powerful, high-level language, but it doesn’t come without challenges—especially when it comes to resource management, garbage collection, and thread handling. This guide will take you through everything you need to know about Java performance monitoring, from key metrics to tools and best practices.

Modern application observability is essential for ensuring system performance, diagnosing issues, and optimizing user experiences. OpenTelemetry (Otel) and Grafana serve as two key components in achieving end-to-end visibility. While OpenTelemetry focuses on instrumenting applications to collect telemetry data, Grafana specializes in visualizing this data, making it actionable and insightful.

If you’ve ever struggled with understanding distributed traces, managing metrics, or debugging complex applications, OpenTelemetry is your best friend. But what about the OpenTelemetry UI? How do you visualize and interact with all that telemetry data? In this guide, we’ll explore the best ways to use OpenTelemetry’s UI options, from setting up a proper observability stack to choosing the right front-end visualization tools.

When discussing observability, the “big 3” - logs, metrics, and traces, always get mentioned. But for some, more data doesn’t always mean better. Our lead engineer, JJ, had some advice to share about how logs may not be necessary for everyone. Simplifying your observability stack isn’t difficult - you just need to be intentional with implementation. Check out more MetricFire blog posts below, and our hosted Graphite service! Get a free trial and start using MetricFire now!