Understanding Counter Rates and Increases in PromQL | Reset Handling, Extrapolation, Edge Cases

In this video, I explain the exact value calculation behaviors of the rate(), irate(), and increase() functions in PromQL for computing rates of increase for counter metrics, show how they are different, how they deal with counter resets, how and when they extrapolate values, and which one you should use.

Check out my Prometheus training courses if you want to learn Prometheus in a structured way from the ground up:

Chapters:
00:00 Introduction
00:45 Absolute Counter Values and Why We Want Rates
01:18 The Three Counter Increase Functions
02:36 Behavior of rate() and increase()
03:02 Handling Counter Resets
04:41 Calculating the rate() and increase() Slope
05:08 Extrapolating the Return Value for the increase() Function
06:42 Confusing Extrapolation for Slow-Moving Counters
07:37 Limiting Extrapolation for Series Starting or Ending Under the Window
08:26 Limiting Extrapolation to Zero Sample Values
08:52 The irate() Function
09:59 Which Function Should You Use?
10:30 Outro & PromLabs Trainings

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[marcosvm]

What a great video, not only for my own education but also to show our internal clients.

[mikoajsienkiewicz]

It's great that you add some "good practices/know-how" when talking about the overall concepts. I find it very helpful to get a general grasp and feeling of what the authors of specific mechanisms had in mind when creating certain things.

[myfamily]

Finally found a great video with visualization that helps understanding these 3 functions. Thank you so much!!

[yboy]

Finally, I understand the difference 🥳Thanks !

[JesseGoodier]

Just a note to say thank you for this video! I was using the functions randomly until now :)

[DenysVitali]

I love the visualizations and forwarded this video to my colleagues. I knew the concepts behind everything you explained, but they're so beautifully explained and represented that I'll just forward your video from now instead of trying to explain it in my words 😁

I hope you'd create more content like this. Keep up the good work!

[rohitmishra]

Wow! Just in time. I am writing my LF PCA certification next month and these tutorials are the perfect second shot I needed to circle-in my preparation. Thank you for these!

[edmundandbaldrick]

first class content julius, keep up the great work 😀

[merkispasha]

Awesome explanation through visualization!

[GarvitJain_]

Thank You for sharing this in such an awesome manner

[mickiXXX]

Thanks for the great explanations, in particular the charts helped me a lot to understand what is happening. Now the values I see start to make sense ;-)

[haouser]

Another amazing video. Thanks for share it!!

[babakhabibnejad]

turly amazing video! I have taken at least 3 courses on prometheus+grafana but non of them are properly detailed like your videos

[aksheengalundia]

This is great. Can you explain for the following scenario?
I want to set up an alert for average increase between two time window, but also dependent of the total number of increase in the same window.
For example, For 1st hour -> increase by 1, 2, 3 and for 2nd hour -> increase by 3, 4, 5, 6
avg increase in 1 hour -> 6/3 = 2 and avg increase in 2 hour -> 18/4 = 4.5
Difference between the hour is 4, 5 - 2 = 2.5

How can i set up such a metrics/alert?

[shiyan]

Thank you Julius, this is a brilliant video. Just wonder do you plan to produce more similar videos like this to embed into promlabs training courses?

[driodeiros]

This is outstanding Julius. Great work.
Prometheus deserved high quality visual materials. Not it has them. Keep up the good work.
May I ask you what software you use to create the videos? Specially the charts, they are pretty cool. I also like the background you use and the sound and video are fantastic.
Thank you.

[sylviohmartins]

Perfect! Do you have any PromQL examples that do what was demonstrated in: 03:02 Handling Counter Resets. Well, the 'rate' was used together with the 'increase', right?!