Meh, I don't get it—what's stopping you from running the same benchmark on a Kubernetes cluster and sharing your own benchmark results, instead of just claiming that this benchmark is crap?
The company selling a product and trying to convince me with benchmarks should be the one putting in the honest effort. The point is to nudge them towards doing this themselves, because people who know about things (how to run distributed system benchmarks) will silently close the tab. HN gives feedback to each other so we can improve. Do you have a problem with that?
Another thing we try to do here is avoid comments that lower the level of discourse, it's in the guidelines.
It seems you are biased to OP, your comment does more harm than good to their effort. (why would I want to use this project if the people around it make snide remarks)
What's about configuring the codec correctly? Using mjpeg? Using VNC? Throwing all this shit into the trashcan and get just diff's in utf-8 from the coding agent?
Or maybe self-write the code to not create this hell of bullshit code that lead to the issues the article writes about?
This article discusses why TiDB, a distributed SQL database, migrated its observability platform from Prometheus to VictoriaMetrics.
The Problem with Prometheus
At scale, Prometheus started showing limitations, especially for large enterprise customers like Pinterest.The main issues were:
- High resource consumption: Prometheus used a lot of CPU and memory, leading to frequent out-of-memory (OOM) crashes.
- Long recovery times: After a crash, Prometheus needed a long time to recover, sometimes failing altogether.
- Limited query performance: Large queries would often fail or be very slow.
The Solution: VictoriaMetrics
TiDB switched to VictoriaMetrics and saw significant improvements:
- Better resource utilization: CPU and memory usage dropped significantly, eliminating OOM crashes.
- Improved query performance: Large queries that previously failed in Prometheus now run efficiently in VictoriaMetrics.
- Lower costs: Reduced resource consumption and better storage efficiency led to lower operational costs.
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