Skip to main content

Documentation Index

Fetch the complete documentation index at: https://launchdarkly-preview.mintlify.app/llms.txt

Use this file to discover all available pages before exploring further.

​
Overview

This topic describes metrics that LaunchDarkly autogenerates from observability events. The LaunchDarkly observability SDKs provide error monitoring and metric collection for errors, web vitals, and document loading in your browser application. The functionality is in separate plugins, which you enable in the initialization options for the LaunchDarkly SDK. The observability plugins collect and send data to LaunchDarkly, where you can review metrics, events, and errors from your application. The observability events are prefixed with $ld:telemetry and LaunchDarkly automatically generates metrics from these events. These expandable sections explain the metrics that LaunchDarkly autogenerates from events recorded by the observability plugins for LaunchDarkly browser SDKs:
Metric kind: Custom numericSuggested analysis unit: UserDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: Average
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the average largest burst per context of layout shift scores for every unexpected layout shift that occurs during the entire lifecycle of a page.Example usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: RequestDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: P95
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the 95th percentile largest burst per context of layout shift scores for every unexpected layout shift that occurs during the entire lifecycle of a page.Example usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: RequestDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: P99
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the 99th percentile largest burst per context of layout shift scores for every unexpected layout shift that occurs during the entire lifecycle of a page.Example usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: UserDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: Average
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the average DOM load duration in milliseconds per contextExample usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: RequestDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: P95
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the 95th percentile DOM load duration in milliseconds per contextExample usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: RequestDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: P99
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the 99th percentile DOM load duration in milliseconds per contextExample usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom conversion binarySuggested analysis unit: UserDefinition:
  • Measurement method: Occurrence
  • Unit aggregation method: Average
  • Analysis method: Average
  • Success criterion: lower is better
  • Units without events: Include units and set the value to 0
Description: Measures the percentage of contexts that encountered an error at least once. This metric is autogenerated by an initial $ld:telemetry:session:init event and populated by subsequent $ld:telemetry:error events. This means you can use the metric even if your app has not yet generated any errors.Example usage: Running a guarded rollout to make sure the error change doesn’t result in a higher error rate
Metric kind: Custom numericSuggested analysis unit: UserDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: Average
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the average time in milliseconds per context between first navigation to a page and when any part of the page’s content is rendered.Example usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: RequestDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: P95
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the 95th percentile time in milliseconds per context between first navigation to a page and when any part of the page’s content is rendered.Example usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: RequestDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: P99
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the 99th percentile time in milliseconds per context between first navigation to a page and when any part of the page’s content is rendered.Example usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: UserDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: Average
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the average time in milliseconds per context between a user’s first interaction (click, tap, or key press) and the time when the browser starts processing event handlers in response to that interaction.Example usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: RequestDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: P95
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the 95th percentile time, in milliseconds per context, between a user’s first interaction (click, tap, or key press) and the time when the browser starts processing event handlers in response to that interaction.Example usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: RequestDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: P99
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the 99th percentile time, in milliseconds per context, between a user’s first interaction (click, tap, or key press) and the time when the browser starts processing event handlers in response to that interaction.Example usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: UserDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: Average
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the average response time in milliseconds per context of all click, tap, and keyboard interactions during the lifespan of a visit to a page.Example usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: RequestDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: P95
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the 95th percentile response time in milliseconds per context of all click, tap, and keyboard interactions during the lifespan of a visit to a page.Example usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: RequestDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: P99
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the 99th percentile response time in milliseconds per context of all click, tap, and keyboard interactions during the lifespan of a visit to a page.Example usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: UserDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: Average
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the average time in milliseconds per context to render the largest image, text block, or video visible when first navigating to a pageExample usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: RequestDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: P95
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the 95th percentile time in milliseconds per context to render the largest image, text block, or video visible when first navigating to a pageExample usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: RequestDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: P99
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the 99th percentile time in milliseconds per context to render the largest image, text block, or video visible when first navigating to a pageExample usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: UserDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: Average
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the average time in milliseconds per context between the request for a resource and when the first byte of a response begins to arrive.Example usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: RequestDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: P95
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the 95th percentile time in milliseconds per context between the request for a resource and when the first byte of a response begins to arrive.Example usage: Observing the latency of interactions an end user makes with your application
Metric kind: Custom numericSuggested analysis unit: RequestDefinition:
  • Measurement method: Value/size
  • Unit aggregation method: Average
  • Analysis method: P99
  • Success criterion: lower is better
  • Units without events: Exclude units that generate no events
Description: Measures the 99th percentile time in milliseconds per context between the request for a resource and when the first byte of a response begins to arrive.Example usage: Observing the latency of interactions an end user makes with your application