My org has done a bunch of what's already covered here. We have a bunch of customers (SAAS), and though we have a good idea of what's going well in aggregate through observability, it's hard to gauge that any single org is having exactly repeatable results at they should expect vs. statistically acceptable volume for everyone. Because of this, we also setup synthetic accounts for test customers and regularly drive test scenarios through them to make sure the single customer doing the same old bring workloads are also doing alright. It tends to catch large issues that are caused changes that affect outputs without changing the volumes/latency. It's like end to end testing very common hot paths running forever in a real customer account flagged without billing. It tends to catch regressions way more often than it rightly should've.