> ## Documentation Index
> Fetch the complete documentation index at: https://launchdarkly-preview.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Autogenerated metrics

> This topic explains the metrics LaunchDarkly automatically generates from SDK events and how you can use them to monitor the health of your applications.

> For the complete documentation index, see [llms.txt](/llms.txt). For the full documentation snapshot, see [llms-full.txt](/llms-full.txt).

## Overview

This section explains the metrics LaunchDarkly automatically generates from SDK events and how you can use them to monitor the health of your applications.

## Metric events

An "event" happens when someone takes an action in your app, such as clicking on a button, or when a system takes an action, such as loading a page. Your SDKs send these metric events to LaunchDarkly, where, for certain event kinds, LaunchDarkly can automatically create metrics from those events. You can use these metrics with [experiments](/home/experimentation) and [guarded rollouts](/home/releases/guarded-rollouts) to track how your flag changes affect your customers' behavior.

LaunchDarkly autogenerates metrics from events that are sent:

* from [AI SDKs](/sdk/ai) used in conjunction with [AI Configs](/home/ai-configs)
* during document load, for browser apps, if you are using the [Observability SDKs](/sdk/observability)
* as part of OpenTelemetry traces using the [OpenTelemetry](/sdk/features/opentelemetry-server-side) feature for server-side SDKs

Autogenerated metrics are marked on the [**Metrics** list](/home/metrics) with an "autogenerated" [tag](/home/account/tags). You can view the events that autogenerated these metrics from the **Metrics** list by clicking **View**, then **Events**.

To learn more, read [Events](/home/metrics/metric-events) and [Metric components](/home/metrics/components).

## Analysis units for autogenerated metrics

LaunchDarkly sets the analysis unit for autogenerated metrics to your account's default context kind for experiments and guarded rollouts. For most accounts, the default context kind is "user". However, you may have updated your default context kind to "account", "device", or some other context kind you use in experiments most often. To learn how to set the default context kind for experiments, read [Mark context kinds available for experiments](/home/experimentation/randomization#mark-context-kinds-available-for-experiments).

All autogenerated metrics are designed to work with an analysis unit of either "user" or "request". Depending on your account's default context kind for experiments, you may need to manually update the analysis unit for autogenerated metrics as needed. The recommended analysis units for each autogenerated metric are listed in the tables below. To learn how to manually update the analysis unit for a metric, read [Edit metrics](/home/metrics/manage-metrics#edit-metrics).

To learn more, read [Analysis units](/home/metrics/components#analysis-units).

## Related content

The remaining topics in this category describe the metrics that LaunchDarkly autogenerates from different event types:

* [AI Config metrics](/home/metrics/autogen/ai)
* [Observability metrics](/home/metrics/autogen/observability)
* [OpenTelemetry metrics](/home/metrics/autogen/opentelemetry)