Define service boundaries using change frequency
Put boundaries where change stops propagating, not where your org chart suggests it should.
Quick Take
Service boundaries fail when changes ripple across them every week. A practical way to draw boundaries is to follow change frequency: group parts that evolve together and separate parts that remain stable. This reduces coordination costs and prevents 'distributed refactors' from becoming your default mode.
Track what changes together before you split anything
Before introducing services, track change patterns in your codebase and product requirements. Look at recent pull requests and releases: which files and components tend to change in the same work item, and which changes repeatedly require coordination across multiple areas.
This gives you evidence. Boundaries should reduce cross-cutting work. If you split without understanding change patterns, you usually separate things that must move together and merge things that should not.
Use change frequency to decide what is one unit of ownership
High-frequency change areas should be grouped into a unit that one team can evolve without external approvals. Low-frequency or stable areas can become shared platforms or extracted services because they do not constantly demand synchronized changes.
A clean boundary shows up as "locality of change": most features in that area can be implemented by touching one boundary's code and data. If most work touches two or more boundaries, the boundary is either wrong or too early.
Avoid boundaries that create permanent coordination
A boundary that forces frequent cross-boundary schema changes, shared business rules, or synchronous call chains will feel stable at first and then degrade into constant alignment meetings and brittle integration tests.
When you must cross a boundary, prefer explicit contracts: stable APIs, versioned events, and data ownership rules. Crossing should be a deliberate act with visible cost, not an invisible dependency.
Signal
What usually breaks is not "the boundary," it's the change process: when teams normalize cross-service edits as routine, the architecture stops reducing complexity and starts manufacturing it.