agavra

If you do want a native CLI in-terminal for this, try out github.com/agavra/tuicr

Save you the read, here's the interesting part:

For $90/mo, we ran a benchmark pushing ~30 MiB/s of metrics data via Buffer. Using public pricing calculators, the equivalent Kafka service cost roughly $1,300/month for managed WarpStream and $8,500/month for self-hosted Apache Kafka.

This is the biggest gap in the 0.2.1 release. We have a pretty naive query execution engine because we've spent most of the time on core data structures and ingestion.

I have some prototypes of vectorized compute that takes that same query from 2s -> ~800ms, and it's just early days. If you want to contribute to help make it better, the query engine part of it is begging for help!

also super cool to see you on here valyala! we took a bunch of inspiration from your work at VM. kudos to all you've done :)

The other solution is to aggressively size your disk cache and keep effectively the full working set on disk, using object storage just as a durability layer. Then the main benefit is operational simplicity because you have a true shared-nothing architecture between the read replicas (there's no quorum or hash ring to maintain and no deduplication on read). Obviously you'll have a more expensive deployment topology if you do so, but it's still compelling IMO because you have the knobs to tune whether you want to cache on disk or not.

anecdotally I've heard confirmations of the challenge of running VictoriaMetrics clusters at scale. they're way better than Cortex/Thanos and they've built a pretty awesome product but still are a pretty significant operational burden.