From ec181c364ff5e7ec8846bc56b047a011449a014d Mon Sep 17 00:00:00 2001 From: Roman Khavronenko <roman@victoriametrics.com> Date: Mon, 24 Jul 2023 16:11:15 +0200 Subject: [PATCH] docs: mention lambdas and cloud functions for aggregation (#4705) * docs: mention lambdas and cloud functions for aggregation Signed-off-by: hagen1778 <roman@victoriametrics.com> --- docs/stream-aggregation.md | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) diff --git a/docs/stream-aggregation.md b/docs/stream-aggregation.md index 22311a4daf..09de6e768d 100644 --- a/docs/stream-aggregation.md +++ b/docs/stream-aggregation.md @@ -418,11 +418,13 @@ For example: <img alt="total aggregation counter reset" src="stream-aggregation-check-total-reset.png"> The same behavior will occur when creating or deleting new series in an aggregation group - -`total` will increase monotonically considering the values of the series set. - +`total` will increase monotonically considering the values of the series set. An example of changing a set of series can be restarting a pod in the Kubernetes. This changes a label with pod's name in the series, but `total` account for such a scenario and do not reset the state of aggregated metric. +Aggregating irregular and sporadic metrics (received from [Lambdas](https://aws.amazon.com/lambda/) +or [Cloud Functions](https://cloud.google.com/functions)) can be controlled via [staleness_inteval](#stream-aggregation-config). + ### increase `increase` returns the increase of input [counters](https://docs.victoriametrics.com/keyConcepts.html#counter). @@ -434,6 +436,9 @@ For example, see below time series produced by config with aggregation interval <img alt="increase aggregation" src="stream-aggregation-check-increase.png"> +Aggregating irregular and sporadic metrics (received from [Lambdas](https://aws.amazon.com/lambda/) +or [Cloud Functions](https://cloud.google.com/functions)) can be controlled via [staleness_inteval](#stream-aggregation-config). + ### count_series `count_series` counts the number of unique [time series](https://docs.victoriametrics.com/keyConcepts.html#time-series). @@ -523,6 +528,9 @@ See how to aggregate regular histograms [here](#aggregating-histograms). The results of `histogram_bucket` with aggregation interval of `1m` is equal to the `histogram_over_time(some_histogram_bucket[1m])` query. +Aggregating irregular and sporadic metrics (received from [Lambdas](https://aws.amazon.com/lambda/) +or [Cloud Functions](https://cloud.google.com/functions)) can be controlled via [staleness_inteval](#stream-aggregation-config). + ### quantiles `quantiles(phi1, ..., phiN)` returns [percentiles](https://en.wikipedia.org/wiki/Percentile) for the given `phi*`