Hey everyone. I've been lurking here for a while, reading all the migration posts—super helpful as we're in the middle of moving off our legacy CDP.
One thing that kept coming up in these stories was the surprise of finding out, days into the cutover, that the event schema in the new CDP wasn't quite what downstream tools expected. The validation usually happened after the fact, causing a lot of rework.
So, during our pre-migration testing phase, I built a simple real-time alert for this. The goal was to catch schema mismatches *as* events hit the new CDP's live stream, not later in a batch process.
Here's the basic idea: I set up a small service that subscribes to the raw event stream (in our case, via AWS Kinesis). It samples events and compares the actual keys and value types against a "golden" schema definition we maintain for critical events (like `order_completed` or `trial_started`). If it detects a new property, a missing expected property, or a type mismatch (e.g., a string where we expect a number), it pings a Slack channel immediately.
We're using a simple JSON Schema definition to validate against. This has already caught a few issues for us:
* A nested property that got flattened incorrectly during the schema translation step.
* A `timestamp` field coming in as a string instead of an integer from one source.
It's not a substitute for full historical backfill validation, but for the live switch, it gives us a lot of confidence. Has anyone else tried something similar? I'm curious if there are better ways to define and maintain that "golden" schema, especially when dealing with multiple source systems feeding the CDP.