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The user suggests implementing 'Golden Signals' for Supabase, a concept from Google's SRE practice, to monitor system health effectively. These signals help identify real issues without being overwhelmed by unnecessary metrics.
The user introduces 'pgpulse', a Supabase-native observability platform designed to provide real-time insights, connection and latency tracking, and query health alerts. They highlight the challenges of monitoring Supabase projects and invite the community to join the beta phase for early access and feedback.
Thank you , follow us for explore more about supabase and pgpulse https://www.linkedin.com/company/pgpulse/
Observability overview is interesting, on observability , pgpulse have developed monitoring stack for supabase built on Metrics API all in one place (Grafana dashboards+alerts+advisory) at https://pgpulse.io
Latency jumping from \~200ms to \~800ms usually means something in the system changed rather than a sudden bug. As mentioned in this blog [https://pgpulse.io/blog/what-actually-breaks-first-in-supabase-apps/](https://pgpulse.io/blog/what-actually-breaks-first-in-supabase-apps/) * a query that was fast earlier now scanning more rows (missing index / table growth) * connection pressure if traffic increased * locks or long transactions blocking others * dead tuples accumulating so reads get slower * cache hit ratio dropping so the DB reads from disk instead of memory One thing that helps is looking at **query latency distribution (p95/p99)** and the **queries consuming the most total time** during the period when latency increased. observability platform like **https://p**gpulse.io make this easier because they show things like slow queries, lock waits, connection usage, cache hit ratio, and table bloat in one place. That makes it easier to see *what changed* compared to when things were fast. But the first thing I’d check is measuring **time spent in the DB query vs the rest of the edge function**, because sometimes the extra latency is actually coming from the runtime or external calls rather than Postgres.
I am giving updates about supabase observability in here [https://www.linkedin.com/company/pgpulse/?viewAsMember=true](https://www.linkedin.com/company/pgpulse/?viewAsMember=true)
I am giving updates about supabase observability in here [https://www.linkedin.com/company/pgpulse/?viewAsMember=true](https://www.linkedin.com/company/pgpulse/?viewAsMember=true)
anyway [pgpulse.io](http://pgpulse.io) helped to clear the way for me
thanks u/Better-Try-2970 and others for the feedback Totally agree with this — thanks for laying it out so clearly. I’ve also relied on the Query Performance page, slow query logs, the Advisor, and the Inspect CLI. All of those help, but once traffic picks up, the issues start overlapping — slow queries mixed with CPU/IO pressure, autovacuum, and especially connection pool saturation. Supabase does expose the signals, but since they’re split across different places, it can still take some effort to piece everything together. I recently tried a tool called **pgpulse** , [https://pgpulse.io](https://pgpulse.io) and their demo/early access helped me correlate slow queries with connections, CPU, IO, etc. in one view as dashboards. I have also checked with other features like alerts, Intelligent advisory. go check [https://pgpulse.io](https://pgpulse.io)
Looking forward for your opinion dear community
Hey @[CompleteCurve5554](https://www.reddit.com/user/CompleteCurve5554/) 👋 I’ve been through the same pain — Supabase’s Prometheus metrics are helpful but too coarse when you need query-level insights. That’s exactly what we’re solving with pgp[**ulse**]() — it connects to your Supabase/Postgres instance (no agent required) and gives you deep visibility into what’s actually happening inside your database: * 🔍 **Per-query metrics** (latency, CPU, I/O, wait events) * ⚙️ **Advisory engine** that detects inefficient queries automatically * 📈 **Real-time dashboards** for reads/writes, connections, and errors * 🚨 **Smart alerts** when query latency or error rates spike You can get started in minutes at [https://pgpulse.io/](https://pgpulse.io/) , if you need more info you can join as Beta user for Supabase native observability [https://pgpulse.io/early-access/](https://pgpulse.io/early-access/)
pgpulse iss providing solution exactly to monitor these issues, Supabase-native monitoring for performance and health. please consider using [https://pgpulse.io/](https://pgpulse.io/) , pgpulse instantly transform your data into **live dashboards, alerts, and actionable insights.** you can onboard your database with one click and observe memory leakages, response times, CPU usages in minutes , you can DM me or join our early user [https://pgpulse.io/early-access/](https://pgpulse.io/early-access/)
real time monitoring of your databases can be achieved with our solution at [https://pgpulse.io](https://pgpulse.io)