On Mon, Jun 22, 2020 at 9:12 PM Paul Dubuc <[email protected]> wrote:

> I have a question about this for some clarification. How does the
> '--metric-interval' affect the cardinality of the metric data?  Does it
> have the same multplier effect that '--series-interval' does in that every
> 120 seconds (default) a whole new set of unique metrics are generated on
> top of those generated at the '--series-interval'?
>

Yes.


>
> Also you you know if setting these intervals to 0 would keep the changes
> from taking effect?
>

No. Just set `--metric-interval` to the value exceeding your test duration
if you need suppressing churn rate. Something like the following should
work: --metric-interval=100000


>
> Thanks.
>
> On Thursday, December 5, 2019 at 2:09:55 PM UTC-5, Aliaksandr Valialkin
> wrote:
>>
>> Note that `avalanche` introduces high churn rate for time series, i.e.
>> old time series are constantly substituted by new time series every
>> `--series-interval` seconds. Default value for `--series-interval` is 60
>> seconds, i.e. every 60 seconds new time series are created. So for
>> `--metrics-count=1000 --series-count=1000` case `avalanche` introduces new
>> 1M time series every minute. In 30 minutes Prometheus scrapes 30M time
>> series from `avalanche`. See also `--metric-interval` command-line flag,
>> which has almost the same meaning as `--series-interval`.
>>
>> BTW, how much RAM is available for your Prometheus setup?
>>
>> On Thu, Dec 5, 2019 at 9:34 AM Rupesh Tripathi <[email protected]>
>> wrote:
>>
>>> Hello Folks,
>>>
>>> I performed some load/stress tests on Prometheus, Please find the
>>> details and outcome below. I observed that prometheus docker container
>>> abruptly disappeared/crashed in few instances. Can someone please help us
>>> explaining what are the limitation of prometheus in terms of number of
>>> unique metrics with high cardinality data?
>>>
>>> Steps:
>>>
>>>
>>>
>>>    1. Start Avalanche for producing unique metrics
>>>       1. docker run -d --net=host quay.io/freshtracks.io/avalanche
>>>       --metric-count=1000 --series-count=1000 --port=9001
>>>       2. This will create 1000 unique metrics name each with 1000
>>>       unique tag values, overall 1000*1000 unique metrics.
>>>       3. Avalanche runs on 9001 port by default but we can change by
>>>       providing port value.
>>>
>>>
>>>    1. *Start prometheus docker container pointing to 9001/metrics to
>>>    fetch metrics from Avalanche *
>>>       1. docker run -d --net=host --rm -v
>>>       $(pwd)/prometheus0_eu2.yml:/etc/prometheus/prometheus.yml -v
>>>       $(pwd)/prometheus0_eu2_data:/prometheus -u root --name 
>>> prometheus-0-eu2
>>>       prom/prometheus --config.file=/etc/prometheus/prometheus.yml
>>>       --storage.tsdb.path=/prometheus --web.listen-address=:9092
>>>       --web.enable-lifecycle --web.enable-admin-api
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>> Number of unique metrics
>>>
>>> Duration
>>>
>>> CPU Usage (Average)
>>>
>>> Memory Usage
>>>
>>> Issues/outcome
>>>
>>> 1000 * 1000 = 1000,000 (1000 unique metric names each with 1000 unique
>>> label/tag values)
>>>
>>> 10 - 15 minutes
>>>
>>> 15.0-20.0%
>>>
>>> 95-99%
>>>
>>> The prometheus container crashes and stops abruptly after 15-30 minutes,
>>> most likely due to out of memory.
>>>
>>> 100 * 1000 = 100,000 (100 unique metric names each with 1000 unique
>>> label/tag values)
>>>
>>> 1-1.5 hours
>>>
>>> 15.0-20.0%
>>>
>>> 90-99%(Starts increasing slowly and after an hour it grows to 90 %+
>>>
>>> Prometheus container stops abruptly after running for 3-4 hours.
>>>
>>> 100 * 100 = 10,000 (100 unique metric names each with 100 unique
>>> label/tag values)
>>>
>>> 2 days
>>>
>>> 5.0-7.0%
>>>
>>> 25-28%
>>>
>>> Prometheus service continues to run without any issues.
>>>
>>>
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>>> .
>>>
>>
>>
>> --
>> Best Regards,
>>
>> Aliaksandr
>>
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> .
>


-- 
Best Regards,

Aliaksandr Valialkin, CTO VictoriaMetrics

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