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Prometheus 3.0

prometheus.io

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Re: Prometheus 3.0

#31

Post by pentagrama »

remram wrote: post #28
pentagrama wrote: post #26

I didn't know this tool, and looking the homepage, is not clear to me if is something like Google Analytics to get metrics of website traffic, or something more dev oriented. Someone can explain to me please? Maybe I'm a bit lost because I'm not a dev. I'm a designer considering selfhosted Google Analytics alternatives and this one may be interesting to add to the research (so far I have Matomo, plausible, open panel…

It's usually meant to monitor infrastructure, like memory and CPU usage of various processes and machines, request per seconds for servers, number of HTTP errors returned, etc. https://prometheus.io/docs/introduction/overview/#what-are-m...

Thank you! Now is more clear to me.

Re: Prometheus 3.0

#32

Post by majewsky »

the_duke wrote: post #15

I'm curios: are many people here actually still running mainline Prometheus over one of the numerous compatible solutions that are more scalable and have better storage? (Mimir, Victoria, Cortex, OpenObserve, ...)

Regular Prometheus inside clusters for collection and alerting, Thanos for cross-cluster aggregation and long retention.

Re: Prometheus 3.0

#33

Post by mdaniel »

pentagrama wrote: post #26

I didn't know this tool, and looking the homepage, is not clear to me if is something like Google Analytics to get metrics of website traffic, or something more dev oriented. Someone can explain to me please? Maybe I'm a bit lost because I'm not a dev. I'm a designer considering selfhosted Google Analytics alternatives and this one may be interesting to add to the research (so far I have Matomo, plausible, open panel…

> I'm a designer considering selfhosted Google Analytics alternatives

I wanted to ensure that you saw this currently on the front page: https://news.ycombinator.com/item?id=42270389 (Show HN: Vince – A self hosted alternative to Google Analytics; 66 comments)

Re: Prometheus 3.0

#34

Post by hagen1778 »

never_inline wrote: post #23
the_duke wrote: post #15

I'm curios: are many people here actually still running mainline Prometheus over one of the numerous compatible solutions that are more scalable and have better storage? (Mimir, Victoria, Cortex, OpenObserve, ...)

I am curious to hear from people on this forum, at what point will people practically cross the limits of prometheus, and straightforward division (eg, different prometheus across clusters and environments) does not work?

It usually comes with increase of active series and churn rate. Of course, you can scale Prometheus horizontally by adding more replicas and by sharding scrape targets. But at some point you'd like to achieve the following:

1. Global query view. Ability to get metrics from all Prometheis with one request. Or just simply not thinking which Prometheus has data you're looking for.

2. Resource usage management. No matter how you try, scrape targets can't be sharded perfectly. So you'll end up with some Prometheis using more resources than others. This could backfire in future in weird ways, reducing stability of the whole system.

Re: Prometheus 3.0

#35

Post by pentagrama »

mdaniel wrote: post #33
pentagrama wrote: post #26

I didn't know this tool, and looking the homepage, is not clear to me if is something like Google Analytics to get metrics of website traffic, or something more dev oriented. Someone can explain to me please? Maybe I'm a bit lost because I'm not a dev. I'm a designer considering selfhosted Google Analytics alternatives and this one may be interesting to add to the research (so far I have Matomo, plausible, open panel…

> I'm a designer considering selfhosted Google Analytics alternatives I wanted to ensure that you saw this currently on the front page: https://news.ycombinator.com/item?id=42270389 (Show HN: Vince – A self hosted alternative to Google Analytics; 66 comments)

That is timing. Thank you, adding to my list.

Re: Prometheus 3.0

#36

Post by yla92 »

aorth wrote: post #29
the_duke wrote: post #15

I'm curios: are many people here actually still running mainline Prometheus over one of the numerous compatible solutions that are more scalable and have better storage? (Mimir, Victoria, Cortex, OpenObserve, ...)

Using Victoria Metrics here. Very easy to set up and run. I monitor under 100 hosts and resource usage is low, performance is good. One gripe is that they recently stopped publishing tarballs for LTS versions, which caused some grumbling in the community. Fair enough since they are developing for free, but felt like a bait and switch.

Same. It's rock solid, low resource usage and good performance. The "single" version mostly just works.

Re: Prometheus 3.0

#37

Post by robinhoodexe »

ChocolateGod wrote: post #30
robinhoodexe wrote: post #20

Earlier quoted context omitted.

We’re running standard Prometheus on Kubernetes (14 onprem Talos clusters, total of 191 nodes, 1.1k cpu cores, 4.75TiB memory and 4k pods). We use Thanos to store metrics in self-hosted S3 (seaweedfs) with 30 days retention, aggressively downsample after 3 days. It works pretty good tbh. I’m excited about upgrading to version 3, as is does take a lot of resources to keep going, especially on clusters with a lot of po…

> We use Thanos to store metrics in self-hosted S3 (seaweedfs) with 30 days retention, aggressively downsample after 3 days. Any reason to not just use Mimir for this?

I can’t recall the reason for using thanos over mimir to be honest. I think thanos seemed like a good choice given it’s part of the kube-prometheus-stack community helm charts.

Re: Prometheus 3.0

#38

Post by rapphil »

rad_gruchalski wrote: post #19
the_duke wrote: post #15

I'm curios: are many people here actually still running mainline Prometheus over one of the numerous compatible solutions that are more scalable and have better storage? (Mimir, Victoria, Cortex, OpenObserve, ...)

Mimir

There is also Cortex metrics, from which Mimir was forked from

Re: Prometheus 3.0

#40

Post by hinkley »

therealdrag0 wrote: post #21
hinkley wrote: post #16

Earlier quoted context omitted.

Developers tend to ignore C in order of complexity calculations but customers don’t. Game developers and HFTs seem to understand this, and very few regular devs I’ve interacted with do. I’ve seen customers say they switched to someone else for speed reasons. And I’ve worked on projects where the engineers were claiming this as fast as we can make it, and they were off by at least a factor of three. We like to think t…

Those margins also mean you have to pick your battles. Most software is not as performance sensitive as video games or HFT. I take an efficient market hypothesis on this. Obviously devs can make stuff faster, and they do where it matters, as can be seen in games and HFT. In other software it’s a discussion with product of trade offs.

In most of the scenarios I’ve mentioned, everyone but the devs disagreed about it being good enough. Too many people think the flame graph is the pinnacle of performance analysis and it’s just table stakes.
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