influxdata / influxdata/kapacitor
Drop/Ignore back-filled points
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- Dominant language
- Go
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Description
We have a deadman alert to fire if we don't see points in some measurement after 5 minutes. It works great in steady state, but we have had some false negatives due to older points getting backfilled into InfluxDB.
The general sequence of events is:
- Points stop being produced. 5 mins later alert fires
- We backfill points from 2 weeks ago. Alert goes back to OK state
We would like to avoid getting into an OK state if a point older than 5 minutes is inserted for that measurement. How can we only consider points with a relevant timestamp?
The tickscript looks like this:
```
var b = stream
|from()
.database('myDb')
.retentionPolicy('autogen')
.measurement('myMeasurement')
.where(lambda: "field" =~ /^regex$/)
b
|deadman(1.0, 5m, lambda: (MATCHES_CRON))
.id('alertId')
.message('{{ .ID }} is {{ .Level }}: {{ index .Fields "emitted" | printf "%.0f" }} points seen in last 5m')
.stateChangesOnly()
.post('http://myalertsystem.com')
```
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The entry point is the shown TICKscript stream and deadman pipeline; start by tracing how deadman counts points within its 5m window and handles point timestamps. Done means inserting points older than five minutes cannot move the alert from fired back to OK, while current points still do.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- go
- Domain
- observability, stream-processing
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100