1aced0a130
as we will use distinct Influx and Grafana instances for the different stages/environments.
14 lines
805 B
Plaintext
14 lines
805 B
Plaintext
import "strings"
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import "date"
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myWindowPeriod = if int(v: v.windowPeriod) > int(v: 2m) then duration(v: int(v: v.windowPeriod) * 30) else duration(v: int(v: v.windowPeriod) * 15)
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result = from(bucket: "poseidon")
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|> range(start: date.truncate(t: v.timeRangeStart, unit: 1m), stop: date.truncate(t: v.timeRangeStop, unit: 1m))
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|> filter(fn: (r) => r["_measurement"] == "poseidon_used_runners")
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|> filter(fn: (r) => contains(value: r["environment_id"], set: ${environment_ids:json}))
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|> filter(fn: (r) => r["event_type"] == "creation")
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|> group(columns: ["environment_id", "stage"], mode:"by")
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|> aggregateWindow(every: 1m, fn: count, createEmpty: true)
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|> keep(columns: ["_value", "_time", "environment_id", "stage"])
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|> aggregateWindow(every: myWindowPeriod, fn: mean, createEmpty: true)
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