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docs/Single-server-VictoriaMetrics.md: cosmetic fixes after 23369321f1

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15
README.md
View file

@ -1898,18 +1898,21 @@ See how to request a free trial license [here](https://victoriametrics.com/produ
* `-downsampling.period=30d:5m,180d:1h` instructs VictoriaMetrics to deduplicate samples older than 30 days with 5 minutes interval and to deduplicate samples older than 180 days with 1 hour interval.
Downsampling is applied independently per each time series and leaves a single [raw sample](https://docs.victoriametrics.com/keyConcepts.html#raw-samples)
with the biggest [timestamp](https://en.wikipedia.org/wiki/Unix_time) on the interval, in the same way as [deduplication](#deduplication).
with the biggest [timestamp](https://en.wikipedia.org/wiki/Unix_time) on the configured interval, in the same way as [deduplication](#deduplication) does.
It works the best for [counters](https://docs.victoriametrics.com/keyConcepts.html#counter) and [histograms](https://docs.victoriametrics.com/keyConcepts.html#histogram),
as their values are always increasing. But downsampling [gauges](https://docs.victoriametrics.com/keyConcepts.html#gauge)
and [summaries](https://docs.victoriametrics.com/keyConcepts.html#summary)
would mean losing the changes within the downsampling interval. Please note, you can use [recording rules](https://docs.victoriametrics.com/vmalert.html#rules)
or [steaming aggregation](https://docs.victoriametrics.com/stream-aggregation.html)
to apply custom aggregation functions, like min/max/avg etc., in order to make gauges more resilient to downsampling.
Downsampling can reduce disk space usage and improve query performance if it is applied to time series with big number
of samples per each series. The downsampling doesn't improve query performance if the database contains big number
Downsampling can reduce disk space usage and improve query performance if it is applied to time series with big number
of samples per each series. The downsampling doesn't improve query performance if the database contains big number
of time series with small number of samples per each series (aka [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate)),
since downsampling doesn't reduce the number of time series. So the majority of time is spent on searching for the matching time series.
It is possible to use [stream aggregation](https://docs.victoriametrics.com/stream-aggregation.html) in vmagent or
recording rules in [vmalert](https://docs.victoriametrics.com/vmalert.html) in order to
since downsampling doesn't reduce the number of time series. In this case the majority of query time is spent on searching for the matching time series
instead of processing the found samples.
It is possible to use [stream aggregation](https://docs.victoriametrics.com/stream-aggregation.html) in [vmagent](https://docs.victoriametrics.com/vmagent.html)
or recording rules in [vmalert](https://docs.victoriametrics.com/vmalert.html) in order to
[reduce the number of time series](https://docs.victoriametrics.com/vmalert.html#downsampling-and-aggregation-via-vmalert).
Downsampling happens during [background merges](https://docs.victoriametrics.com/#storage)

18
docs/README.md
View file

@ -1901,18 +1901,21 @@ See how to request a free trial license [here](https://victoriametrics.com/produ
* `-downsampling.period=30d:5m,180d:1h` instructs VictoriaMetrics to deduplicate samples older than 30 days with 5 minutes interval and to deduplicate samples older than 180 days with 1 hour interval.
Downsampling is applied independently per each time series and leaves a single [raw sample](https://docs.victoriametrics.com/keyConcepts.html#raw-samples)
with the biggest [timestamp](https://en.wikipedia.org/wiki/Unix_time) on the interval, in the same way as [deduplication](#deduplication).
with the biggest [timestamp](https://en.wikipedia.org/wiki/Unix_time) on the configured interval, in the same way as [deduplication](#deduplication) does.
It works the best for [counters](https://docs.victoriametrics.com/keyConcepts.html#counter) and [histograms](https://docs.victoriametrics.com/keyConcepts.html#histogram),
as their values are always increasing. But downsampling [gauges](https://docs.victoriametrics.com/keyConcepts.html#gauge)
and [summaries](https://docs.victoriametrics.com/keyConcepts.html#summary)
would mean losing the changes within the downsampling interval. Please note, you can use [recording rules](https://docs.victoriametrics.com/vmalert.html#rules)
or [steaming aggregation](https://docs.victoriametrics.com/stream-aggregation.html)
to apply custom aggregation functions, like min/max/avg etc., in order to make gauges more resilient to downsampling.
Downsampling can reduce disk space usage and improve query performance if it is applied to time series with big number
of samples per each series. The downsampling doesn't improve query performance if the database contains big number
Downsampling can reduce disk space usage and improve query performance if it is applied to time series with big number
of samples per each series. The downsampling doesn't improve query performance if the database contains big number
of time series with small number of samples per each series (aka [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate)),
since downsampling doesn't reduce the number of time series. So the majority of time is spent on searching for the matching time series.
It is possible to use [stream aggregation](https://docs.victoriametrics.com/stream-aggregation.html) in vmagent or
recording rules in [vmalert](https://docs.victoriametrics.com/vmalert.html) in order to
since downsampling doesn't reduce the number of time series. In this case the majority of query time is spent on searching for the matching time series
instead of processing the found samples.
It is possible to use [stream aggregation](https://docs.victoriametrics.com/stream-aggregation.html) in [vmagent](https://docs.victoriametrics.com/vmagent.html)
or recording rules in [vmalert](https://docs.victoriametrics.com/vmalert.html) in order to
[reduce the number of time series](https://docs.victoriametrics.com/vmalert.html#downsampling-and-aggregation-via-vmalert).
Downsampling happens during [background merges](https://docs.victoriametrics.com/#storage)
@ -1963,7 +1966,6 @@ VictoriaMetrics provides the following security-related command-line flags:
* `-tls`, `-tlsCertFile` and `-tlsKeyFile` for switching from HTTP to HTTPS.
* `-httpAuth.username` and `-httpAuth.password` for protecting all the HTTP endpoints
with [HTTP Basic Authentication](https://en.wikipedia.org/wiki/Basic_access_authentication).
* `-http.header.hsts`, `-http.header.csp`, and `-http.header.frameOptions` for serving `Strict-Transport-Security`, `Content-Security-Policy` and `X-Frame-Options` HTTP response headers.
* `-deleteAuthKey` for protecting `/api/v1/admin/tsdb/delete_series` endpoint. See [how to delete time series](#how-to-delete-time-series).
* `-snapshotAuthKey` for protecting `/snapshot*` endpoints. See [how to work with snapshots](#how-to-work-with-snapshots).
* `-forceMergeAuthKey` for protecting `/internal/force_merge` endpoint. See [force merge docs](#forced-merge).
@ -1972,6 +1974,8 @@ VictoriaMetrics provides the following security-related command-line flags:
* `-flagsAuthKey` for protecting `/flags` endpoint.
* `-pprofAuthKey` for protecting `/debug/pprof/*` endpoints, which can be used for [profiling](#profiling).
* `-denyQueryTracing` for disallowing [query tracing](#query-tracing).
* `-http.header.hsts`, `-http.header.csp`, and `-http.header.frameOptions` for serving `Strict-Transport-Security`, `Content-Security-Policy`
and `X-Frame-Options` HTTP response headers.
Explicitly set internal network interface for TCP and UDP ports for data ingestion with Graphite and OpenTSDB formats.
For example, substitute `-graphiteListenAddr=:2003` with `-graphiteListenAddr=<internal_iface_ip>:2003`. This protects from unexpected requests from untrusted network interfaces.

18
docs/Single-server-VictoriaMetrics.md
View file

@ -1909,18 +1909,21 @@ See how to request a free trial license [here](https://victoriametrics.com/produ
* `-downsampling.period=30d:5m,180d:1h` instructs VictoriaMetrics to deduplicate samples older than 30 days with 5 minutes interval and to deduplicate samples older than 180 days with 1 hour interval.
Downsampling is applied independently per each time series and leaves a single [raw sample](https://docs.victoriametrics.com/keyConcepts.html#raw-samples)
with the biggest [timestamp](https://en.wikipedia.org/wiki/Unix_time) on the interval, in the same way as [deduplication](#deduplication).
with the biggest [timestamp](https://en.wikipedia.org/wiki/Unix_time) on the configured interval, in the same way as [deduplication](#deduplication) does.
It works the best for [counters](https://docs.victoriametrics.com/keyConcepts.html#counter) and [histograms](https://docs.victoriametrics.com/keyConcepts.html#histogram),
as their values are always increasing. But downsampling [gauges](https://docs.victoriametrics.com/keyConcepts.html#gauge)
and [summaries](https://docs.victoriametrics.com/keyConcepts.html#summary)
would mean losing the changes within the downsampling interval. Please note, you can use [recording rules](https://docs.victoriametrics.com/vmalert.html#rules)
or [steaming aggregation](https://docs.victoriametrics.com/stream-aggregation.html)
to apply custom aggregation functions, like min/max/avg etc., in order to make gauges more resilient to downsampling.
Downsampling can reduce disk space usage and improve query performance if it is applied to time series with big number
of samples per each series. The downsampling doesn't improve query performance if the database contains big number
Downsampling can reduce disk space usage and improve query performance if it is applied to time series with big number
of samples per each series. The downsampling doesn't improve query performance if the database contains big number
of time series with small number of samples per each series (aka [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate)),
since downsampling doesn't reduce the number of time series. So the majority of time is spent on searching for the matching time series.
It is possible to use [stream aggregation](https://docs.victoriametrics.com/stream-aggregation.html) in vmagent or
recording rules in [vmalert](https://docs.victoriametrics.com/vmalert.html) in order to
since downsampling doesn't reduce the number of time series. In this case the majority of query time is spent on searching for the matching time series
instead of processing the found samples.
It is possible to use [stream aggregation](https://docs.victoriametrics.com/stream-aggregation.html) in [vmagent](https://docs.victoriametrics.com/vmagent.html)
or recording rules in [vmalert](https://docs.victoriametrics.com/vmalert.html) in order to
[reduce the number of time series](https://docs.victoriametrics.com/vmalert.html#downsampling-and-aggregation-via-vmalert).
Downsampling happens during [background merges](https://docs.victoriametrics.com/#storage)
@ -1971,7 +1974,6 @@ VictoriaMetrics provides the following security-related command-line flags:
* `-tls`, `-tlsCertFile` and `-tlsKeyFile` for switching from HTTP to HTTPS.
* `-httpAuth.username` and `-httpAuth.password` for protecting all the HTTP endpoints
with [HTTP Basic Authentication](https://en.wikipedia.org/wiki/Basic_access_authentication).
* `-http.header.hsts`, `-http.header.csp`, and `-http.header.frameOptions` for serving `Strict-Transport-Security`, `Content-Security-Policy` and `X-Frame-Options` HTTP response headers.
* `-deleteAuthKey` for protecting `/api/v1/admin/tsdb/delete_series` endpoint. See [how to delete time series](#how-to-delete-time-series).
* `-snapshotAuthKey` for protecting `/snapshot*` endpoints. See [how to work with snapshots](#how-to-work-with-snapshots).
* `-forceMergeAuthKey` for protecting `/internal/force_merge` endpoint. See [force merge docs](#forced-merge).
@ -1980,6 +1982,8 @@ VictoriaMetrics provides the following security-related command-line flags:
* `-flagsAuthKey` for protecting `/flags` endpoint.
* `-pprofAuthKey` for protecting `/debug/pprof/*` endpoints, which can be used for [profiling](#profiling).
* `-denyQueryTracing` for disallowing [query tracing](#query-tracing).
* `-http.header.hsts`, `-http.header.csp`, and `-http.header.frameOptions` for serving `Strict-Transport-Security`, `Content-Security-Policy`
and `X-Frame-Options` HTTP response headers.
Explicitly set internal network interface for TCP and UDP ports for data ingestion with Graphite and OpenTSDB formats.
For example, substitute `-graphiteListenAddr=:2003` with `-graphiteListenAddr=<internal_iface_ip>:2003`. This protects from unexpected requests from untrusted network interfaces.