I'd be interested to know a bit of detail as we're looking into Grafana/Promethus a bit.
You can be small with Prometheus and grow into needing an FTE for it - w/o having the migration hurdle of moving out-source to in-source
We run Prometheus in production and this hasn't been our experience at all.
A single machine can easily handle hundreds of thousands of time series, performance is good, and maintaining the alerting rules is a shared responsibility for the entire team (as it should be).
If you use it as a store for all time series data generated by your business, and you want to have indefinite or very-long-term storage, managing prometheus does become a challenge. (hence m3, chronosphere, endless other companies and tech built to scale the backend of prometheus).
IMO, this is a misuse of the technology, but a lot of unicorn startups have invested a lot of engineering resources into using it this way. And a lot of new companies are using it this way; hence the "one engineer's FT job".
After that, we needed some more effort to scale out horizontally with Thanos, but again, once it's set up, it maintains itself.