Skip to main content
In a consumption model, configure budgets to take action and protect against overspending. For each budget, define thresholds and priorities to define the actions to take when a threshold is exceeded, and control the data that gets dropped. You can then attach budgets to a partition. The consumption model includes the following concepts, which are volume-based licensing resources for telemetry data that you can spend credits on.

​
Logging license consumption

Spend credits flexibly across the following log resources in the consumption model:
  • Persisted bytes: Log bytes stored in the database.
  • Processed bytes: Log bytes matched for transformation and reshaping.

​
Tracing license consumption

Spend credits flexibly across the following trace resources in the consumption model.
  • Persisted bytes: Trace bytes stored in the database.
  • Processed bytes: Trace bytes matched for transformation and reshaping.

​
Metrics license consumption

Spend credits flexibly across the following metric resources in the consumption model.

​
Metrics persisted series

A metrics persisted series is a time series, defined as a unique combination of metric name and labels, that Observability Platform persists to storage. One persisted series is incurred for a time series if no identical time series has been persisted within the rolling 48-hour window. After 48 hours without a write, the series is no longer tracked and a subsequent write incurs a new persisted series. Persisted series pricing varies by storage retention tier.

​
Metrics persisted datapoint

A metrics persisted datapoint is an individual, timestamped datapoint that Observability Platform persists to storage. Each persisted datapoint counts as exactly one unit, regardless of metric type. Persisted datapoint pricing varies by effective datapoint resolution (EDR). EDR is the average time between consecutive persisted data points of a time series, computed across all persisted series and data points in your tenant.

​
Metrics persisted histogram datapoint bucket

A metrics persisted histogram datapoint bucket is a bucket within a histogram datapoint that Observability Platform persists to storage. One persisted histogram datapoint bucket is incurred for each non-zero bucket within a persisted histogram datapoint. Only populated bucket positions in the histogram’s sparse encoding are counted.

​
Metrics matched datapoint

A metrics matched datapoint is a datapoint matched for aggregation. One matched datapoint is incurred for each aggregation rule matched for each datapoint. If a datapoint matches one rule, that’s one matched datapoint. If a datapoint matches two rules, that’s two matched data points. Recording rules don’t count toward matched data points.

​
Metrics matched histogram datapoint bucket

A metrics matched histogram datapoint bucket is a bucket within a histogram datapoint matched for aggregation. One matched histogram datapoint bucket is incurred for each non-zero bucket within a matched histogram datapoint, multiplied by the number of aggregation rules matched.