Story

Hey HN, I'm Kristiyan. I previously led Redis Insight (the official Redis GUI). When I started working with Valkey, I found the observability tooling lacking — so I started building BetterDB.

The core problem: Valkey and Redis expose useful operational data (slowlog, latency stats, client lists, memory breakdowns), but it's all ephemeral. Restart your server and it's gone. Existing tools show real-time charts but can't tell you what happened at 3am when your p99 spiked.

BetterDB persists this ephemeral data and turns it into actionable insights:

- Historical analytics for queries (slowlog and commandlog patterns aggregated by type), clients (commands, connections, buffers), and ACL activity - Anomaly detection and 99 Prometheus metrics - Cluster visualization with topology graphs and slot heatmaps - Automated latency and memory diagnostics - AI assistant for querying your instance in plain English (via local Ollama) - Sub-1% performance overhead

On that last point — I wrote up our interleaved A/B benchmarking methodology in detail: https://www.betterdb.com/blog/interleaved-testing. Most tools claim "minimal overhead" without showing their work. We open-sourced the benchmark suite so you can run it on your own hardware and verify.

You can try it right now:

    npx @betterdb/monitor

    docker run -d -p 3001:3001 betterdb/monitor

We're building this in public — the benchmark suite, the technical blog posts, and the roadmap are all out in the open. Would love feedback from production users of Valkey or Redis on what observability gaps you're still hitting.

GitHub: https://github.com/BetterDB-inc/monitor Blog: https://www.betterdb.com/blog