When to use Google App Engine Flex vs Google Cloud Run

Pricing/Autoscaling: The pricing model between GAE Flexible Environment and Cloud Run are a bit different.

• In GAE Flexible, you are always running at least 1 instance at any time. So even if your app is not getting any requests, you’re paying for that instance. Billing granularity is 1 minute.
• In Cloud Run, you are only paying when you are processing requests, and the billing granularity is 0.1 second. See here for an explanation of the Cloud Run billing model.

Underlying infrastructure: Since GAE Flexible is running on VMs, it is a bit slower than Cloud Run to deploy a new revision of your app, and scale up. Cloud Run deployments are faster.

Portability: Cloud Run uses the open source Knative API and its container contract. This gives you flexibility and freedom to a greater extent. If you wanted to run the same workload on an infra you manage (such as GKE), you could do it with "Cloud Run on GKE".

I'd actually suggest that you seriously consider Cloud Run over App Engine.

Over time, I've seen a few comments of a "new" App Engine in the works, and it really seems that Cloud Run is that answer. It is in beta, and that can be an issue. I've seen some companies use beta services in production and others wait. However, if I am going to start a new app today - it's going to be Cloud Run over App Engine Flex for sure.

Google is very deep into Kubernetes as a business function. As Cloud Run is sitting on GKE - this means that it is indirectly receiving development via other teams (The general GKE infrastructure).

Conversely, App Engine is on some older tech. Although it's not bad - it is "yesterday's" technology. Google, to me, seems to be a company that gets really excited about what is new and what is being highly adopted in the industry.

All this said - when you wrap your services in a container, you should be able to run them anywhere? Well, anywhere there is a container platform. You can front your services with something like Cloud Endpoints and you can deploy on both App Engine and Cloud Run - swap back and forth. Then, at that point, the limitations might be the services that are offered. For instance, Cloud Run currently doesn't support some items, like Cloud Load Balancing or Cloud Memorystore. That might be a blocker today.

Short story: Appengine is something real, relatively stable. Cloud Run is pretty much just a draft/idea, very unstable.

Long story: Being in alpha/beta Google Cloud Run may suffer many changes. If you are old enough you might remember how dramatically Appengine pricing has changed. It promised a CPU/RAM based pricing, then it decided that's not "possible" or at least not very profitable and moved to a VM based pricing, then they shipped a decent appengine release(Appengine Flex or whatever name it had at that time) but also increased the price again by adding a minimum instance model. Not to mention the countless APIs/breaking changes or the limits changes.

Cloud Run is based on gVisor which has some limitations so depending on the language/library you use and what you do, it may break(or just Google's implementation may break) at some point and there is nothing you can do (i.e. patch the system) and it will ruin your productivity and potentially your business. You may have a look on its current issues.

Free advice: Even if you choose Appengine or Cloud Run avoid proprietary APIs/services such Google Datastore. They may ruin your business. Pricing, APIs and limits will change. There is no real open source or paid alternative so your code is not portable. Your code is pretty worthless outside of Google cloud.

Disclaimer: I've been burned by appengine changes and datastore lock-in so my opinion may be biased.

I have a ML model with REST API interface as a micro service. When I tried to run with Cloud Run, it deploys but just does not work. I had to switch back to App Engine Flexible Env.

Cloud Run (fully managed) currently (Jul 2020) has RAM limitation of 2GB. For better hardware I should go for Anthose with GKE infra. But this has min instance needs of at least 4 instances to properly work. Mine being a tiny application I settled for App engine Flexible environment. Though autoscale settings required min 2 instances, in early days it could be managed with manual scaling and 1 instance as limit.

EDIT: As on Aug 22 2020, the RAM limit is 4GB and number of cores is 2, for fully managed GCP cloud Run.