However, the network effect in tech can be leapfrogged due to the zero marginal cost (as shown in this post). I.e. what network effect do you get from doing ML inference in the cloud?
The case for big tech today is still the economy of scale and not network effects (maybe facebook have those, but it exists only if the interface to facebook does not change).
The big tech players have economy of scale, due to their ability to use automation and offload the risk of managing complexity (I.e. one AWS engineer can manager 1000's of machines with AWS software).
No wonder, that the software that manages the public cloud is still closed source.
However, with Kubernetes operators, there is a way to move those capabilities into any Kubernetes cluser.
The case for big tech today is still the economy of scale and not network effects (maybe facebook have those, but it exists only if the interface to facebook does not change).
The big tech players have economy of scale, due to their ability to use automation and offload the risk of managing complexity (I.e. one AWS engineer can manager 1000's of machines with AWS software).
No wonder, that the software that manages the public cloud is still closed source.
However, with Kubernetes operators, there is a way to move those capabilities into any Kubernetes cluser.