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We also wanted Kubernetes to run with a small number of dependencies, and with bounded compute and storage capacity: if we assumed a managed message bus that could store a week of events and an elastic compute platform to process them in parallel, the design would be different
Systems that require a key/value store for leader election and configuration, a database for persistence, an out-of-process cache for performance, a message bus for eventing, and a store for message bus persistence (3-5 stateful components) can be painful to operate.
This thread is pure gold! I always asked myself why not use a messaging system, e.g. Kafka with Streaming Semantics (by then, this did not exist of course, so just a thought experiment). This thread on the reasoning behind watches and REST/CRUD K8s API totally make sense now.
Yes, there are many ways the problem could be solved, and it is related to state replication, distributed cache synchronization, set reconciliation, and other distribution problems. We treat K8s as a key/value store, which is my next topic: the resource model
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