metrics.timeseries

metrics.timeseries data queries aggregates metrics statistics over a date range. This can retrieve multiple series each with a different metric and function (avg, sum, min, max, count). A series can also be aggregated or filtered by any combination of metric dimensions.

type:metrics.timeseries
period:hour
range:"-24 hours to now"
series.avg:(
  label:Average
  metric:cerb.tickets.open
  function:avg
)
series.min:(
  label:Min
  metric:cerb.tickets.open
  function:min
)
series.avg:(
  label:Max
  metric:cerb.tickets.open
  function:max
)
timezone:Europe/Berlin
format:timeseries

The 'Chart: Metrics Explorer' widget can write one of these queries for you with Copy » Data Query. Expect two differences from the example above: it uses the faceted_* functions rather than avg, min, and max, and it templates the metric as metric:"{{record_name}}". That placeholder only resolves against a metric record, so pasting the query anywhere else returns nothing until you replace it with the metric's name.

period:
range:
series.*:
- series.*.query:
timeout:
timezone:
format:

period:

The period is the metric's level of detail:

`minute`	5-minute statistics (up to the past 24 hours)
`hour`	hourly statistics (up to the past 2 weeks)
`day`	daily statistics (no limit)
`week`	weekly statistics starting on Monday (no limit)
`week-sun`	weekly statistics starting on Sunday (no limit)
`month`	monthly statistics (no limit)
`year`	yearly statistics (no limit)

range:

The date range to show statistics for, grouped by the period.

this week

this month

-1 year

Jan 1 2025 to Dec 31 2025

series.*:

Each series.* series should provide:

Key	Description
`metric:`	The metric name
`by:`	A comma-separated list of dimension keys to group by
`function:`	`sum`, `min`, `max`, `average`, `samples`, `distinct`, `faceted_average`, `faceted_min`, `faceted_max`. The faceted functions sum samples with different dimensions into a single total.
`label:`	A human-readable label for this series
`missing:`	How to handle missing sample periods: `null` (default), `zero` (set to 0), or `carry` (carry the last sample)
`query:`	An optional query using dimension keys to filter samples.

series.*.query:

Dimension filters can use negation. For instance, query:(worker_id:![1,2,3])

This makes proportional charts straightforward – one series for a dimension and another for everything else, stacked against each other:

series.mine:(
  label:Mine
  metric:cerb.tickets.open
  query:(group_id:1)
)
series.others:(
  label:Others
  metric:cerb.tickets.open
  query:(group_id:!1)
)

Record-based dimension can use deep search filers.

timeout:

The query will be aborted after this many milliseconds have elapsed with no response.

The default is 20000 milliseconds (20 seconds).

timezone:

Statistics are stored in GMT/UTC. The timezone: location shifts timestamps when grouping metrics by period.

Day-based period units collapse into UTC consistently, so a day boundary means the same thing regardless of where the query runs.

For example:

America/Los_Angeles

Europe/Berlin

Asia/Tokyo

If omitted, this defaults to the timezone of the current worker or the server.

format:

The metric results can be returned in various formats:

Format
`dictionaries`	Returns series data suitable for a sheet or automation.
`timeblock`	Returns data suitable for a timeblocks widget
`timeseries`	(Default) Returns series-based data suitable for a time-series chart (with the 'x' axis values as timestamps)

Cerb

Metrics Timeseries