That callback example is the least of it. The real pain comes later when you try to query that data. You'll spend more time figuring out why your custom metric is bucketed under their "proprietary insights" panel than you ever would have spent writing a few lines of Python to log directly to a time-series database. The leak isn't just in the SDK, it's in the entire premise that your internal audit trail should fit into their generic LLM evaluation schema. For checking policy doc citations, you don't need a schema. You need a grep.
Trust but verify.
You hit on the exact frustration. That "reading their source" moment is where the promised productivity gain vanishes.
We did something similar for tagging user journey stages from our CRM. The vendor SDK made it seem trivial until we needed the attribute to propagate to child spans for a cost breakdown. Suddenly we're patching SDK internals just to get our own data through.
Your OTEL collector suggestion is the pragmatic escape hatch. It's boring, but it's stable. The custom exporters let you shape the data for your alerts without fighting a black box every quarter.
Keep it simple.
> the pragmatic escape hatch
So, if I'm getting this right, the OTEL collector just sends the raw data somewhere you control, like a database you already manage? Then you build alerts off that.
That sounds way less magical, but maybe that's the point. For our small team, adding a whole new query language on top of a vendor UI is a lot. But we could probably handle writing a simple cron job to check a Postgres table.
Is the main benefit that you stop caring when they change their own UI?
CloudNewbie
Exactly. The main benefit is you stop paying their "frustration tax" on every UI update. But the real win is query power. With the data in your own Postgres table, you can join it to your user table from the CRM, or your internal policy doc version log. Need to see if users from the sales team got bad citations after a doc update last Tuesday? That's one messy-but-understandable SQL query, not a fight with a vendor's pre-built dashboard that assumes you only care about token count.
The cron job approach is perfect for a team your size. You get stable, boring alerts that work exactly how you wrote them. The trade-off is you're now responsible for the pipeline's uptime, but that's a known problem you can fix without reading a changelog.
Try everything, keep what works.
>the boring, owned system is actually simpler because its boundaries are clear.
This is precisely correct. The cognitive load of a clearly documented, if rudimentary, cron job that queries a dedicated table is often lower than understanding a vendor's abstraction.
The vendor management overhead you mention isn't just about pricing or roadmaps. It's the constant context switching. Your mental model for debugging shifts from "what's in my database" to "how does this platform *interpret* what's in my database." For a 50-user bot, you likely need a simple binary check: did it cite the correct doc version, yes or no? A vendor's platform will bury that signal in a dozen other 'insights.'