Fill
| Function | Description | Example |
|---|
fill() | Interpolate missing metric values for the metric. | <METRIC_NAME>{*}.fill(<METHOD>, <LIMIT>) |
The fill() function has two parameters:
METHOD: The function to use as an interpolation method; choose from:
- linear: Gives you a linear interpolation between the beginning and the end of the gap.
- last: Fills the gap with the last value of the gap.
- zero: Fills the gap with a zero value.
- null: Deactivates the interpolation.
LIMIT [optional, default=300, maximum=600]: The interpolation limit (in seconds) that represents the maximum size of a gap you want to interpolate.
Read Interpolation and the Fill Modifier for a detailed explanation of the .fill() function and its impact on interpolation.
Default zero
| Function | Description | Example |
|---|
default_zero() | Adds a default value to sparse metrics. | default_zero(system.load.1{*}) |
The default_zero() function fills empty time intervals using the value 0 or, if interpolation is enabled, with interpolation. Note: Interpolation is enabled by default for GAUGE type metrics. Like most functions, default_zero() is applied after time and space aggregation.
Use cases
The default_zero() function is intended to address the following use cases (though it may also work for other use cases):
- Aligning gauges as 0 when performing arithmetic on sparse metrics (note:
COUNT or RATE type metrics queried as_count() or as_rate() are always aligned as 0, so using default_zero() does not change how they are aligned; it only affects GAUGE type metrics). - Resolving monitors from a no-data condition. This works for both simple and multi alerts, but the value 0 must not cause the monitor to trigger. For example, this would not work for a monitor with the query
avg(last_10m):avg:system.cpu.idle{*} < 10 because this monitor triggers (instead of resolving) when it evaluates to 0. Avoid using this function for error rate monitors with as_count() queries. See the as_count() in Monitor Evaluations guide for more details. - Filling in empty intervals in sparse (but nonempty) series for visual reasons or to affect the min/max/average of a timeseries in a monitor evaluation. If the evaluation window doesn’t contain any points of data,
default_zero() has no effect. - Showing the value 0 on the timeseries widget when there is no data.
Example
To demonstrate how the default_zero() function works, consider this single point created for a custom metric using DogStatsD:
$ echo -n "custom_metric:1|g" | nc -4u -w0 127.0.0.1 8125
When this metric is queried over the past 30 minutes, there is a single timestamp, because only one of the query’s rollup intervals has a point:
avg:custom_metric{*}
+---------------------+---------------+
| Timestamp | custom_metric |
+---------------------+---------------+
| --------- | --------- |
| 2019-04-17 17:45:00 | 1 |
+---------------------+---------------+
The default_zero() function interpolates this point five minutes forward in time (the default interpolation limit for gauges), then fills the remaining empty intervals with zeros:
default_zero(avg:custom_metric{*})
+---------------------+-----------------------------+
| Timestamp | default_zero(custom_metric) |
+---------------------+-----------------------------+
| --------- | --------- |
| 2019-04-17 17:30:00 | 0 |
| 2019-04-17 17:31:00 | 0 |
...
| 2019-04-17 17:44:00 | 0 |
| 2019-04-17 17:45:00 | 1 |
| 2019-04-17 17:46:00 | 1 |
| 2019-04-17 17:47:00 | 1 |
| 2019-04-17 17:48:00 | 1 |
| 2019-04-17 17:49:00 | 1 |
| 2019-04-17 17:50:00 | 1 |
| 2019-04-17 17:51:00 | 0 |
| 2019-04-17 17:52:00 | 0 |
...
+---------------------+-----------------------------+
Further reading
Additional helpful documentation, links, and articles:
