No. Shared data and chatty workflows can make the system more coupled.

A modular monolith can offer clear internal APIs and transaction boundaries with simple deployment. Services become useful for independent scaling, ownership, release cadence, security boundaries, or failure isolation when those benefits exceed operational complexity. Avoid a distributed monolith: many network calls that must all deploy together or share unrestricted writes to one schema. Define APIs and event contracts at ownership boundaries. The model maps each entity to one write owner and rejects conflicting registrations.

What the function promises: OwnershipRegistry is a local documentation/invariant model, not a service-discovery or authorization system.

class OwnershipRegistry:
    def __init__(self):
        self.owner = {}
    def register(self, entity, service):
        previous = self.owner.get(entity)
        if previous is not None and previous != service:
            raise ValueError("Conflicting write ownership")
        self.owner[entity] = service

registry = OwnershipRegistry()
registry.register("note", "notebook")
registry.register("note", "notebook")
assert registry.owner["note"] == "notebook"
try:
    registry.register("note", "notifications")
except ValueError:
    pass
else:
    raise AssertionError("Conflicting owners accepted")

Work and storage: Expected O(1) registry updates. Real service boundaries add deployment, observability, and network costs not represented here.

When to recognize it: If several services write the same business state without a contract, deployment separation may increase coupling instead of reducing it.

Check before applying it: Independent deployment is valuable only when its ownership and operational costs are justified.

Potentially. A queue and independently scalable delivery workers can isolate the workload. First define event ownership, retries, and failure behavior rather than splitting by class names.