Step-by-Step: How to Identify Over-Scoped Microservices

1. Map Your Current Microservices

Create a visual or list-based map of:

• All microservices

• Their responsibilities

• Their data ownership

• Their API contracts

• Inter-service communications (REST, events, etc.)

This will help you see overlaps and redundancies.

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2. Spot the Smells (Signs of Too Many Microservices)

Look for services that:

• Only wrap a database table (CRUD-only services)

• Are tightly coupled to others (e.g. always deployed together)

• Communicate too frequently (chatty services)

• Have no real domain meaning (e.g., NotificationDbService)

• Are owned by the same team and change together

These are candidates for consolidation.

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3. Group by Business Capability

Re-cluster services by business capabilities rather than technical responsibilities.

Example:

• UserProfileService, UserSettingsService, and UserNotificationPreferencesService might be better off as one UserAccountService.

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4. Review Service Interactions

If two services:

• Call each other frequently

• Share data models

• Are part of the same user flow (e.g. CartService + CartPricingService)

They probably shouldn't be separate unless there's a good scaling or ownership reason.

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5. Review Teams & Deployment

Ask:

• Are multiple services always deployed together?

• Are they maintained by the same team?

• Do they require coordination on every change?

If yes, consider merging them.

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6. Check for DDD Violations

If your services don’t align with business boundaries or bounded contexts, you're likely over-segmented.

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🧩 What to Merge vs What to Keep

Criteria	Merge	Keep Separate
Always deployed together	✅	❌
Same bounded context	✅	❌
High communication	✅	❌
Distinct business logic	❌	✅
Different scaling requirements	❌	✅
Owned by different teams	❌	✅

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🔄 Example

Let’s say you have:

• EmailService

• SMSService

• PushNotificationService

You could consolidate them into a single NotificationService with strategy pattern or plugins to handle different channels.

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🔧 Tooling Tips

• Use tools like Kiali, Zipkin, or Jaeger if you’re on a service mesh (Istio) to visualize service traffic and dependencies.

• For static analysis: build service dependency graphs based on your codebase or OpenAPI specs.