The more services you have, the higher the latency, to a point it is unbearable. So you know what the engineers do? They have to go back and make some services monolithic again.

This is also applicable to microkernel model, where everything is almost processes intercommunicating either locally or remotely, but their performance is so bad they are either academically significant only or are simply abandoned.

There are also critical services that bottlenecks the entire service plane. When one of them critical services (such as authentication service, which brought down Google recently) dies, it still have the cascading failures that monolithic services usually have.

And sometimes it is impossible to properly make microservices when data consistency is highly important. These services (such as database and transaction based services) are critical by nature and is almost impossible to scale, and have to either using leader-election, which in a nutshell, distributed locks where the losers are merely standbys wasting resources on whether they can obtain the lock again, and will be highly susceptible to deadlock unless a reliable transactional memory source is involved (such as etcd leader lock in Kubernetes). Or replicate only. They are also what bugger up microservices to have degenerated into its monolithic equivalent or have to pay a great toll to get it scalable to survive in the microservice world.

Well, to be honest, microservices in practice are just multiple monolithic services strapped together; We need to redesign all our current infrastructure to remove these critical bottlenecks. That's how you do microservices right.