Metric insights

Overview

This topic explains how to use metric insights to understand your guarded rollouts.

View metric insights

To view more information about a metric's performance, click the name of the metric from the flag's targeting page. The metric's time series chart and table appears:

Each metric you add to the flag generates a time series chart that displays the metric's results over time for each variation, and a table with the lower and upper bounds of the metric results for each variation. To learn more, read Time series charts and tables.

To view more information about the performance of all attached metrics, click View results:

This opens the flag's Insights page.

The Insights page

After you add a metric to a flag, the flag's Insights page displays information about the guarded rollout and each metric's performance.

The Insights page includes the following information about the guarded rollout:

• The date and time of the guarded rollout
• The name of the monitored rule, and if automatic rollback is enabled
• The percentage of a rule's traffic you assigned to be monitored
• The length of the monitoring window
• The number of contexts monitored during the monitoring window

You can monitor subsequent rollouts on the the same flag if you toggle the flag off and then on again, or if you change the variation served for a particular rule.

To view the results of a past rollout on a flag, change the date range from the date selection menu:

Time series charts and tables

Each metric you include in a guarded rollout generates the following:

• A time series chart that displays the metric's results over time for each variation. The solid line represents the point estimate of the metric, which is the estimated mean of the metric values for the variation. The larger shaded area represents the range that contains 90% of the metric's probable values for the variation, called the credible interval. The longer the metric collects data, the narrower and more precise the credible interval should become.
• A table listing the lower and upper bounds of the confidence interval for each variation at the end of the monitoring period. In the time series chart, the confidence interval is the shaded area surrounding the solid line for each variation. Any variation that had a regression is highlighted in the table in red.

This illustration shows where the upper and lower bounds are for two variations in an example time series chart:

LaunchDarkly uses the upper and lower bounds to determine if the guarded release has had a regression.

LaunchDarkly considers the following scenarios a regression:

• For metrics where a lower value is better, LaunchDarkly considers it a regression when the lower bound of the treatment’s confidence interval exceeds the upper bound of the control’s confidence interval.
• For metrics where a higher value is better, LaunchDarkly considers it a regression when the upper bound is less than zero.

This graphic displays the confidence interval for an example numeric metric for which lower values are better, and what a regression looks like: