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Merge pull request mendix#10807 from jdiehl/patch-471448
Enhance tracing introduction with key benefits
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content/en/docs/refguide/runtime/tracing-in-runtime.md

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@@ -7,7 +7,20 @@ description: "Describes how to setup and use tracing in the Mendix Runtime."
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## Introduction
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Mendix supports tracing via OpenTelemetry. When tracing is enabled, the runtime generates traces that help you analyze errors and performance.
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These traces can be sent to observability tools like [Jaeger](https://www.jaegertracing.io/) or [Datadog](https://www.datadoghq.com/).
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Tracing provides a deep insight into applications' performance and stability by collecting and analyzing runtime data during operation. It offers these key benefits:
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* End‑to‑end request visibility – tracing can follow a single request across all involved services.
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* Clear causality and root‑cause analysis – traces show exactly where an issue occurred and how it propagated.
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* Precise latency attribution – tracing pinpoints which operation or dependency affected response times the most.
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* Correlation across telemetry signals – traces can be correlated with logs and metrics for holistic performance and error analysis.
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* Vendor‑neutral, future‑proof instrumentation – OpenTelemetry is an open industry standard and best practice.
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Tracing is an important tool for maintaining critical applications, ensuring application performance, and troubleshooting issues with applications in production.
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## Prerequisites
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To view these traces, you will need an observability tool such as [Jaeger](https://www.jaegertracing.io/) or [Datadog](https://www.datadoghq.com/).
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Tracing is currently supported only via [Datadog integration](/developerportal/operate/datadog-metrics/) on Mendix Cloud.

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