Understanding Prometheus Histograms | Motivation and Concepts, Instrumentation, Querying in PromQL

[@GuilhermePim-i8b]

this was so helpful, thanks so much!!

[@TheDiveO]

totally missed the prom chrome plugin, great little gem her, thank you very much!

[@Carlos1979Mad]

Thank you vey much Sir. I bough your training in PromLabs which so far has been very useful. For the histograms part in particular I struggled a bit until I took my time watching your video and trying thing on my own environment. This video was of great help and I think I got now the whole picture. Pls keep doing this. Thanks again

[@animeshkumar1606]

Great video, nicely explained

[@佐々木千奈]

Thanks for the very informative video! When you calculated the percentile you had set 5m for the period to get the range vector. You said 5m is a general value, however, I saw a blog that recommended using $__interval or $__rate_interval, which are global variables in Grafana. Could you give me some advice on this? (e.g., what values to use in what cases, etc.).

[@winfle]

Super nice explanation!

[@cars0n27]

Hi, just want to say that i chanced upon using prometheus while trying to conduct a load test. This is really interesting tool! I deployed a postgres exporter to expose certain metrics from my postgres instance. Encountered some issues as there wasnt too many tutorials about how to do this in azure managed prometheus. But nonetheless managed to figure it out. I watched most of your video in one ago just afew hours ago, and these are really useful knowledge, including those tips in grafana. thank you!

[@cryoexn7307]

These videos are amazing! I have been transitioning from influx to otel, and Prometheus for custom metrics and these are super helpful Just a question from something i noticed in the video, isn’t the count always going to be equal to the +Inf bucket since it’s a cumulative histogram? Was wondering if there’s a reason they are separate other than to avoid confusion?

[@PromLabs]

Thanks! Yes, the count is always going to be the same as the +Inf bucket, but it's still useful to have both: when working with histogram_quantile(), it's easier to just pass in all the *_bucket time series. When working with just the count to get a normal request rate, it's easier to just work with the _count series.

[@GeorgiKobilarov]

Great video! How do I display histograms in Grafana?

[@PromLabs]

Good question, I'll make a quick follow-up video about using heatmaps in Grafana soon!

[@yogeshsy7382]

Histogram from the horse's mouth ❤, understood and luved it ! Thank you! Any code examples of enabling this for Python and Java?

[@PromLabs]

Thanks! You can find Python examples at prometheus.github.io/client_python/instrumenting/histogram/ and Java at prometheus.github.io/client_java/getting-started/metric-types/#histogram

[@e-researcher]

Amazing

[@yogeshsy7382]

Great playlist, however it would be helpful if you can fix the order of the playlist from getting started to more advance topic like histogram and counter rates, etc

[@PromLabs]

Thanks for the suggestion, I reordered the videos a bit. They're not really meant to be building on each other in any particular order or curriculum, so not sure if the new order is that much better :)

[@NoBodyDroid]

What software you use for these visualizations?

[@PromLabs]

motioncanvas.io/ mostly :)

[@muhammaddaffaambiya5394]

Hi bro, how to backup and restore Prometheus Data ?

[@PromLabs]

You can use the snapshot API (prometheus.io/docs/prometheus/latest/querying/api/#snapshot) to create a snapshot of the entire TSDB that can be copied / backed-up to somewhere else. Just drop it back in place as Prometheus' data directory when you want to restore it. Triggering a snapshot via the API requires the admin API to be enabled via the "--web.enable-admin-api" command line flag.