Comment by ants_everywhere
Comment by ants_everywhere 3 days ago
That's a pretty extreme definition in my opinion.
Google played a role in popularizing the microservice approach.
When I was at Google, a microservice would often be worked on with teams of 10-30 people and take a few years to implement. A small team of 4-5 people could get a service started, but it would often take additional headcount to productionize the service and go to market.
I have a feeling people overestimate how small microservices are and underestimate how big monorepos are. About 9 times out of ten when I see something called a monorepo it's for a single project as opposed to a repo that spans multiple projects. I think the same is true of microservices. Many things that Amazon or Google considers microservices might be considered monoliths by the outside world.
Kubernetes is a good example of a microservice architecture. It was designed in a way where each microservice work with other microservices in a way where the dependencies are not so coupled together.
For example, the API server only reads and writes resources to etcd. A separate microservice called the scheduler does the actual assignment of pods to nodes by watching for changes in the resource store against available nodes. And yet a different microservice that lives on each node accepts the assignment and boots up (or shuts down) pods assigned to its node. It is called the kublet. The API server does none of that.
You can run the kublet all on its own, or even replace it to change part of the architecture. Someone was building a kublet that uses systemd instead of docker, and Fly.io (who seems to hate kubernetes) wrote a kublet that could stand things up using their edge infrastructure.
The API server also does some validations, but it also allows for other microservices to insert itself into the validation chain through pod admission webhooks.
Other examples: deployment controllers, replicaset controllers, horizontal pod autoscalers, and cluster autoscalers to work independently of each other yet coordinated together to respond to changing circumstances. Operators are microservices that manage a specific application component, such as redis, rabbitmq, Postgresql, tailscale, etc.
One of the big benefits of this is that Kubernetes become very extensible. Third-party vendors can write custom microservices to work with their platform (for example, storage interfaces for GCP, AWS, Azure, or Ceph, etc). An organization implementing Kubernetes can tailor it to fit their needs, whether it is something minimal or something operating in highly regulated markets.
Ironically, Kubernetes is typically seen and understood by many to be a monolith. Kubernetes, and the domain it was designed to solve is complex, but incorrectly understanding Kubernetes as a monolith creates a lot of confusion for people working with it.