Yeah, at some scale it becomes common to run multiple or even many
Prometheus servers, segmented by different aspects like team, service,
datacenter, sharding level, ... On the other hand, many organizations start
out with a single Prometheus server and only split things up as that one
becomes too large and unwieldy to handle. A single Prometheus on a big
machine can take you quite far, but you'll have to experiment. In the end
it doesn't matter so much how many different systems or services you
monitor, but how many time series they produce, as that's the main scaling
bottleneck for Prometheus.

On Tue, May 5, 2020 at 1:05 PM Tim Schwenke <jellyfilledn...@gmail.com>
wrote:

> Hello,
>
> did I understood correctly that due to Prometheus being very light-weight
> (unlike an Elasticsearch) and efficient but having an upper-limit of xx
> millions of time series per instance it is recommended to have one
> Prometheus server/container per observed system (may it be an application
> or set of CI/CD job runners) than to host a single massive Prometheus?
>
> On one hand I see the advantage in scraping all my REST APIs across all
> apps with one Prometheus. On the other hand I also have a ton of
> application specific metrics I would have to separate with a prefix or so
> to not lose overview (labels work as well, but I have to pick a metric
> first to filter for a certain label value).
>
> Thanks in advance,
>
> Tim Schwenke
>
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