OpenData Timeseries: Prometheus-compatible metrics on object storage

mdwaud

The "why should I care" is about 3/4 of the way down the page: > None of these numbers are exact, but the structural gap is clear: a handful of nodes costing roughly $560/month versus $10,000-20,000/month for a managed service at the same scale. As we explained earlier, it’s practical to operate OpenData Timeseries yourself and fully realize these massive cost savings since it isn’t a traditional distributed database that manages partitioned and replicated state. It doesn't look 100% turn-key, but those are compelling numbers.

davistreybig

Wow this is so, so much cheaper than alternatives

hagen1778

Comparing self-hosted prices with managed solutions isn't exactly apples to apples. But if you do compare, VictoriaMetrics cloud for 3Mil active series and twice higher ingestion rate (100K samples/s or 30s scrape interval) will cost you ~$1k/month + storage costs. See https://victoriametrics.cloud/#estimate-cost

valyala

Interesting solution! According to the provided numbers at "query latency" chapter, the query over cold data, which selects samples for 497 time series over 6 hours time range takes 15 seconds if the queried data isn't available in the cache. This means that typical queries over historical data will take eternity to execute ;(

hagen1778

I am curious to see more tests on the reading path. The article mentions matching 500 series over 6h window with 1m step - and it takes 2s for warmed caches. That doesn't sound good at all. Especially nowadays, when metrics from k8s ramping up churn rate to hundreds of thousands and millions series.