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