Hey everyone! 👋 I've been running a self-hosted Langfuse instance for a few months now to monitor and trace our AI-powered marketing campaigns, and overall it's been fantastic for gaining visibility into our workflows. We're currently using the default setup, but as our dataset grows, I'm starting to think about performance and long-term scalability.
I was poking around the docs and community discussions and saw mentions of a **Postgres direct connect option** for the self-hosted version. This really piqued my interest! We already have a managed Postgres instance (on AWS RDS) that we use for our core HubSpot and Salesforce data warehouse, so the idea of having Langfuse write directly to that same ecosystem is very appealing for a few reasons:
* **Unified data governance:** Keeping all observability data alongside our other marketing data would simplify access control and backup policies.
* **Potential for deeper integrations:** I could more easily join Langfuse trace data with our lead scoring tables or campaign attribution models.
* **Leveraging existing investments:** We could potentially use the same database performance tuning and monitoring tools we already have in place.
Before I dive into a weekend migration project, I was hoping to hear from anyone who has actually implemented this. My practical questions are:
* **What was your setup experience like?** Was it mostly a configuration change in the Langfuse environment variables, or were there tricky steps involved?
* **How has performance been?** Any noticeable differences in ingestion speed or query performance for the Langfuse UI compared to the default database?
* **Any gotchas or pitfalls?** I'm thinking about schema migrations, version upgrades, or anything that broke after you switched over.
* **Did it unlock any new workflows for you?** I'd love to hear if connecting directly to your own Postgres instance allowed you to build any cool custom dashboards, alerts, or integrations that weren't as easy before.
If you have any snippets of your config or lessons learned, sharing those would be incredibly helpful. I'm especially curious if anyone has done this while also feeding data from multiple sources (like our production LLM apps and our internal experiment environments) into the same instance.
Thanks in advance for sharing your wisdom—this community has been a goldmine for my marketing ops stack!
~Sarah
Data is the new oil