Links

• https://www.youtube.com/watch?v=TgINvIK9SYc&list=PLj6h78yzYM2ORxwcjTn4RLAOQOYjvQ2A3&index=6

Disclaimer

• Native Histograms are an experimental feature!
• Everything described here can stil lchange!
• Things might break or behave weirdly!

prometheus --enable-feature=native-histograms

Wishlist

• Everything that works well now should continue to work well.
• I never want to configure buckets again.
• All histograms should always be aggregatable with each other, across time and space.
• I want accurate quantile and percentage estimations across the whole range of observations.
• I want all of that at a lower cost thant current histograms so that I can finally partition histograms at will.

1. Resource consumption of the instrumented binary

2. Frequency of resets and resolution reduction

• Scraping 15 instances of the cloud-backend-gateway.

• Drop everything but the cortex_request_duration_seconds histograms.

• Scraping classic histograms:
  • 964 histograms (peak)
  • 16388 series (964 * 17)
  • 14460 buckets (964 * 15)
• Scraping native histograms:
  • 964 histograms (peak)
  • 964 series

Frequency of resets to reduce bucket count

• Top 10 rest histograms are all:
  • {route=~"api_prom_api_v1_query(_range)", status_code="200"}
• Even among thos typically just a handful of rests per day.
• Worst offender during the 15d of the experiment: 8 resets per day. (Please check the original video)
• Rarely touching the configured 1h limit.

Frequency of resolution reduction

• Only ever happended one stap (from growth factor 1.0905… to 1.1892…).
• Happens “occasionally”…

3. Prometheus resource consumption

4. Query Performance