Auto-apply overview

Auto-apply is a setting that applies new recommendations as they’re generated, so you don’t have to open the list and choose which to apply. The mode you choose decides whether recommendations that add series are applied too, so some recommendations can still wait for you to apply them. If you want to keep certain metrics as they are, create an exemption. It keeps a metric, or a label, out of recommendations. A label is a name and value pair attached to a series, such as service="checkout".

You turn auto-apply on for a segment. A series is a single list of values recorded over time, identified by its labels. A metric is all the series that share a metric name. A segment groups series by a label you choose, such as one team’s series, so one metric can have series in more than one segment. Adaptive Metrics recommends changes for each metric in each segment, so the same metric can get different recommendations in different segments. The Default segment contains the series that aren’t assigned to a named segment.

For example, you turn on auto-apply for the Default segment. For the series in that segment, Adaptive Metrics then applies the new recommendations your mode allows as they’re generated. If you’ve exempted the latency metrics for your checkout service, auto-apply leaves those metrics as they are.

Why use it?

• Less manual work: New recommendations are applied without you opening the list each time.
• Keeps up with your usage: As Adaptive Metrics updates its recommendations, your segment stays tuned for cost and observability.
• Control by segment: You turn it on for the segments you choose and leave it off for the rest.