> Did you do any measurements and if so, on which dyno types? We found that using Performance-M dynos' gives us a rather large performance boost. Performance-m

> Did you do any measurements and if so, on which dyno types? We found that using Performance-M dynos' gives us a rather large performance boost. Performance-m dyno's are also more stable because they run on dedicatd hardware. They're expensive, but we don't run any apps in production without it. We did some measurements, but mostly focusing on the network bits (which you largely solved with CloudFlare): https://fly.io/blog/turboku/ https://fly.io/blog/turboku/ I was surprised at how much faster things seemed on our VMs vs Heroku's Dynos, to be honest. We only compared Standard dynos, but we should be even better price vs performance compared to the performance dynos since we run our own physical servers. A performance-m dyno on Heroku costs about the same as 8 cpus on fly. It's totally self serving, but if you feel like playing around with the Fly stuff I'd love to know how it compares. > This is going to be tricky. We weren't able to set up replication from Heroku Postgres databases to hosts outside of Heroku. Another thing to keep in mind that is it might be better to let the app decide what is a read query and what is a write query. We have some parts of the app that we need reading directly from the master, so we let the app handle it. The app receives two database URI's, both pointing to pgbouncer. This is why I think the in memory caching is such a good option. Usually if I'm building an app, I'll add a caching layer before a DB replica. Write through caching seems to fit my mental processes better. :D