I have a python Flask APIs deployed on cloud run. Autoscaling, CPU, concurrency everything is configurable in cloud run. Now the problem is with the actual load testing with around 40k concurrent users hitting APIs continuously.
Does cloud run handle these huge volumes or should we port our app to GKE? What are the factors decide Cloud run vs GKE?
Cloud Run is designed to handle exactly what you're talking about. It's very performant and scalable. You can set things like concurrency per container/service as well which can be handy where payloads might be larger.
Where you would use GKE is when you need to customise your platform, perform man in the middle or environment complexity, or to handle potentially long running compute, etc. You might find this in large enterprise or highly regulated environments. Kubernetes is almost like a private cloud though, it's very complex, has its own way of working, and requires ongoing maintenance.
This is obviously opinionated but if you can't think of a reason why you need Kubernetes/GKE specifically, Cloud Run wins for an API.
To provide more detail though; see Cloud Run Limits and Quotas.
The particularly interesting limit is the 1000 container instances but note that it can be increased at request.
