Hi Ben,
Thank you for the response. So for scraping and storing/writing the data
for this setup, prometheus would need ~30G memory .
i have a query on 2 Data Query scenarios-
scenario1: We run a query to get 3 years of load via grafana as -
node_load15{instance="$node",job="$job"}[$__rate_interval]
scenario2: we decide to query the system load worth 3 years for a single
server from the grafana, which uses following query:
avg_over_time(node_load15{instance="$node",job="$job"}[$__rate_interval]) *
100 / on(instance) group_left sum by
(instance)(irate(node_cpu_seconds_total{instance="$node",job="$job"}[$__rate_interval]))
this involves 2 series, plus 3 functions (avg_over_time,sum by , irate) and
a division operation
Is there a way to get a rough estimate of the amount of CPU and RAM
required for the queries mentioned in scenario1 and scenario2?
Regards,
Puneet
On Tuesday 20 February 2024 at 23:17:19 UTC+5:30 Ben Kochie wrote:
> Prometheus needs a minimum of about 4KiB per "active series". Retention
> policy doesn't affect the memory usage very much.
>
> If you have 10,000 metrics per server and 300 servers, that's 3 million
> series.
>
> 3 million * 4KiB = 11.4GiB of memory.
>
> Of course, you will also need some page cache and such. Usually 2x is more
> than good enough, but it depends on your query load. So 20-30GiB of memory
> should be enough.
>
> But of course, it highly depends on how many metrics per server you have.
>
> On Tue, Feb 20, 2024 at 6:24 PM Puneet Singh <singh.p...@gmail.com> wrote:
>
>> HI All,
>> I am planning to store 3 years of data from 300 server in a single
>> prometheus server. The data will primarily consist of default exporter
>> metrics and the server has 500G memory and 80 cores.
>>
>> I'd like to ensure that my solution is optimal in terms of resource
>> utilization, query performance and scalability. Is there a general
>> recommendation about the amount of resources i should be having on this
>> setup?
>>
>> Regards,
>> Puneet
>>
>>
>>
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