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Document new staleness (#3380)
Remove "interpolation" for this heading, that hasn't been in these docs for a long time.
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@ -177,7 +177,7 @@ in detail in the [expression language functions](functions.md) page.
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## Gotchas
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### Interpolation and staleness
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### Staleness
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When queries are run, timestamps at which to sample data are selected
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independently of the actual present time series data. This is mainly to support
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@ -186,14 +186,22 @@ time series do not exactly align in time. Because of their independence,
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Prometheus needs to assign a value at those timestamps for each relevant time
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series. It does so by simply taking the newest sample before this timestamp.
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If no stored sample is found (by default) 5 minutes before a sampling timestamp,
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no value is assigned for this time series at this point in time. This
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effectively means that time series "disappear" from graphs at times where their
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latest collected sample is older than 5 minutes.
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If a target scrape or rule evaluation no longer returns a sample for a time
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series that was previously present, that time series will be marked as stale.
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If a target is removed, its previously returned time series will be marked as
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stale soon afterwards.
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NOTE: <b>NOTE:</b> Staleness and interpolation handling might change. See
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https://github.com/prometheus/prometheus/issues/398 and
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https://github.com/prometheus/prometheus/issues/581.
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If a query is evaluated at a sampling timestamp after a time series is marked
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stale, then no value is returned for that time series. If new samples are
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subsequently ingested for that time series, they will be returned as normal.
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If no sample is found (by default) 5 minutes before a sampling timestamp,
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no value is returned for that time series at this point in time. This
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effectively means that time series "disappear" from graphs at times where their
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latest collected sample is older than 5 minutes or after they are marked stale.
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Staleness will not be marked for time series that have timestamps included in
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their scrapes. Only the 5 minute threshold will be applied in that case.
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### Avoiding slow queries and overloads
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