fat-apple

We’ve created a ticket to track our addition of commercial code to our repo: https://github.com/opstrace/opstrace/issues/319

We've done a deep dive into the cost model for metrics and posted more about it here: https://opstrace.com/blog/pulling-cost-curtain-back. We are still working on a full cost analysis for logs - I'd be happy to send it to you once we have it (feel free to email me [email protected] to chat about your use case). Our goal is to be super transparent (see https://news.ycombinator.com/item?id=25992081) with cost and to have a page on our website that helps someone determine what to expect (probably some sort of calculator with live data). Our UI will also show you exactly what your system is currently costing you with some breakdown for teams or services so you know who/what is driving your monitoring cost. We're doing user testing on our to-be-released UI now and would love to have people like yourself give us early feedback (since you mentioned the BigQuery interface).

(1) As it stands today, you can already use https://vector.dev/docs/reference/sinks/prometheus_remote_wr... to write metrics directly to our Prometheus API. You can also use https://vector.dev/docs/reference/sinks/loki/ to send your logs to our Loki API. Vector is very cool in our opinion and we’d love to see if there is more we can do with it. What are your thoughts?

(2) As for cost, our super early experiments (https://opstrace.com/blog/pulling-cost-curtain-back) indicate that ingesting 1M active series with 18-month retention is less than $30 per day. It is a very important topic and we've already spent quite a bit of time on exploring this. Our goal is to be super transparent (something you don’t get with SaaS vendors like Datadog) by adding a system cost tab in the UI. Clearly, the cost depends on the specific configuration and use case, i.e. on parameters such as load profile, redundancy, and retention. A credible general answer would come in the shape of some kind of formula, involving some of these parameters -- and empirically derived from real-world observations (testing, testing, testing!). For now, it's fair to say that we're in the observation phase -- from here, we'll certainly do many optimizations specifically towards reducing cost, and we'll also focus on providing good recommendations (because as we all know cost is just one dimension in a trade-off space). We're definitely excited about the idea of providing users useful, direct insight into the cost (say, daily cost) of their specific, current Opstrace setup (observation is key!). We've talked a lot about "total cost of ownership" (TCO) in the team.