microservices-decomposition

Microservices Decomposition

Produce a complete microservices decomposition design for a system — whether decomposing an existing monolith or designing service boundaries for a new system. Ground the decomposition in Domain-Driven Design (DDD) concepts: identify bounded contexts first, then derive service boundaries from them. Include communication pattern decisions (sync vs. async, event vs. RPC), data ownership rules, and a pragmatic migration plan if decomposing a monolith. Conway's Law is real — include an organizational alignment section. The deliverable should be specific enough that a team can begin implementation, not an abstract architectural diagram.

Required Inputs

Ask for these if not already provided:

• System or domain description — what the system does, its core domain, and the key business processes it supports
• Current architecture — monolith (describe the tech stack and rough module structure), partial services (list existing services), or greenfield
• Team structure — number of teams, team names if known, and approximate team sizes; this drives service ownership
• Performance and scalability requirements — any specific SLAs, load characteristics, or scaling constraints per domain area
• Migration constraints — what cannot be rewritten all at once, hard deadlines, zero-downtime requirements, budget constraints
• Integration points — external systems, third-party APIs, or legacy systems that cannot be changed

If decomposing a monolith, also ask for: approximate codebase size, what is most painful to change today, and where the team experiences the most coupling-related friction.

Output Format

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Microservices Decomposition: [System Name]

Author: [Name / Team] Date: [Date] Architecture type: [Monolith decomposition / New system design] Current state: [One sentence describing what exists today] Target state: [One sentence describing the desired end state]

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1. Domain Analysis

Core Domain

[One paragraph: what is the core domain of this system? What does the business fundamentally do? What gives it competitive differentiation? The core domain gets the most investment and the cleanest service boundaries.]

Domain Map

List every significant subdomain before assigning service boundaries. Classify each subdomain:

Subdomain	Type	Description	Current Location in Monolith
[Subdomain, e.g., Order Management]	Core	[What it does and why it matters]	[Module/package name or "new"]
[Subdomain, e.g., Inventory]	Core	[Description]	[Location]
[Subdomain, e.g., Notifications]	Supporting	[Description]	[Location]
[Subdomain, e.g., Billing]	Supporting	[Description]	[Location]
[Subdomain, e.g., Reporting]	Generic	[Description — candidates for off-the-shelf solutions]	[Location]
[Subdomain, e.g., User Auth]	Generic	[Description]	[Location]

Subdomain types: Core = competitive differentiation, build with care; Supporting = necessary but not differentiating, build pragmatically; Generic = commodity, buy or use open source.

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2. Bounded Context Map (ASCII)

┌─────────────────────────────────────────────────────────────────┐
│                        [System Name]                            │
│                                                                 │
│  ┌──────────────────┐    ┌──────────────────┐                  │
│  │  [Context A]     │    │  [Context B]      │                  │
│  │                  │─ ─►│                  │                  │
│  │  [key concepts]  │    │  [key concepts]  │                  │
│  └──────────────────┘    └──────────────────┘                  │
│           │                       │                             │
│           │ event                 │ sync                        │
│           ▼                       ▼                             │
│  ┌──────────────────┐    ┌──────────────────┐                  │
│  │  [Context C]     │    │  [Context D]      │                  │
│  │                  │    │                  │                  │
│  │  [key concepts]  │    │  [key concepts]  │                  │
│  └──────────────────┘    └──────────────────┘                  │
│                                   │                             │
│                          ┌────────┘                             │
│                          ▼                                      │
│                 ┌──────────────────┐                            │
│                 │  [Context E]     │                            │
│                 │  [key concepts]  │                            │
│                 └──────────────────┘                            │
│                                                                 │
│  External: [Third-party system] ──► [Context that owns it]      │
└─────────────────────────────────────────────────────────────────┘

Legend:  ──► sync call   - -► async event   ═══ shared kernel

Render this map using the actual bounded contexts derived from the domain analysis. Place contexts that communicate frequently closer together. Label relationship types on arrows.

Context Relationships

Upstream Context	Downstream Context	Relationship Type	Integration Pattern
[Context A]	[Context B]	Customer-Supplier	REST API call
[Context B]	[Context C]	Published Language	Domain events via message bus
[Context X]	[Context Y]	Conformist	[Downstream conforms to upstream's model]
[Context X]	[Context Y]	Anti-Corruption Layer	[ACL translates upstream model to local model]

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3. Proposed Service Inventory

Service Name	Bounded Context	Core Responsibility	Team Owner	Tech Stack	Priority
[service-name]	[Context]	[One sentence: what this service owns and does]	[Team]	[Language/framework]	[P1/P2/P3]
[service-name]	[Context]	[Responsibility]	[Team]	[Stack]	[Priority]
[service-name]	[Context]	[Responsibility]	[Team]	[Stack]	[Priority]
[service-name]	[Context]	[Responsibility]	[Team]	[Stack]	[Priority]
[service-name]	[Context]	[Responsibility]	[Team]	[Stack]	[Priority]

Service count: [N proposed services] for [M bounded contexts]. [Note if any context maps to multiple services and why — e.g., "the Orders context splits into order-intake and order-fulfillment because they have different scalability requirements."]

Service Responsibility Rules (applied to every service above)

• Single bounded context ownership — a service does not straddle two bounded contexts
• Owns its own data — no direct database access by other services
• Independently deployable — no coordinated deploys required with other services
• Has a named team owner — no shared ownership of a single service across teams
• Exposes a defined API contract — not internal implementation

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4. Inter-Service Communication Patterns

Pattern Decision Matrix

Communication Need	Recommended Pattern	Rationale
Query another service's current state	Synchronous REST / gRPC	Low latency required; caller needs immediate response
Notify other services of a state change	Async domain event	Decouples services; multiple consumers; sender doesn't care when it's processed
Long-running workflow spanning services	Async saga (choreography or orchestration)	No single service owns the full workflow; rollback needed if steps fail
Read-heavy cross-service aggregation	CQRS read model / materialized view	Avoid chatty sync calls at read time; build purpose-fit read models
Real-time push to clients	WebSocket gateway service	Centralizes connection management; services emit events, gateway pushes

Per-Service Communication Decisions

Service	Calls (sync)	Publishes (events)	Subscribes to (events)
[service-name]	[service-name (endpoint)]	[EventName]	[EventName]
[service-name]	—	[EventName], [EventName]	[EventName]
[service-name]	[service-name (endpoint)]	—	[EventName]

Event Catalog

Event Name	Producer	Consumers	Payload (key fields)	Trigger
[OrderPlaced]	[order-service]	[inventory-service, notification-service]	orderId, customerId, lineItems, totalAmount	Customer submits order
[InventoryReserved]	[inventory-service]	[order-service]	orderId, reservationId, items	Inventory successfully reserved
[PaymentProcessed]	[payment-service]	[order-service, notification-service]	orderId, paymentId, amount, status	Payment confirmed

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5. Data Ownership Matrix

Each piece of data has exactly one owning service. Other services may cache or project a read model, but they do not write to the owner's database.

Data Entity	Owner Service	Authoritative Store	Consumers	Access Pattern
[Order]	[order-service]	[PostgreSQL]	[fulfillment-service, reporting-service]	Event subscription + read API
[Customer]	[customer-service]	[PostgreSQL]	[order-service, notification-service]	Sync API call
[Product Catalog]	[catalog-service]	[PostgreSQL]	[order-service, inventory-service]	Sync API + cached local copy
[Inventory Level]	[inventory-service]	[Redis + PostgreSQL]	[catalog-service (read only)]	Event subscription
[Payment Record]	[payment-service]	[PostgreSQL]	[order-service]	Event subscription

Data Migration (if decomposing a monolith)

Data Entity	Current Location	Target Service	Migration Approach	Data Volume	Risk
[Entity]	[monolith.orders table]	[order-service]	Dual-write then cut over	[X rows]	[High/Med/Low]
[Entity]	[monolith.users table]	[customer-service]	Extract and sync via CDC	[X rows]	[High/Med/Low]

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6. API Contract Definitions

Define the surface area for each service. Full OpenAPI specs are written separately; this section establishes the contract boundaries.

[service-name] API

Base path: /api/v1/[resource] Owner team: [Team] SLA: [p99 latency target, availability target]

Endpoint	Method	Description	Auth Required	Rate Limit
/[resources]	GET	List [resources] with pagination	Yes	[X req/min]
/[resources]/{id}	GET	Get single [resource] by ID	Yes	[X req/min]
/[resources]	POST	Create new [resource]	Yes	[X req/min]
/[resources]/{id}	PUT	Update [resource]	Yes	[X req/min]
/[resources]/{id}	DELETE	Soft-delete [resource]	Yes — elevated	[X req/min]

[Repeat for each service.]

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7. Strangler Fig Migration Plan (for monolith decomposition)

Use the strangler fig pattern: extract services incrementally, route traffic through a facade, and retire monolith modules one at a time.

Migration Phases

Phase 1: Foundation (Weeks 1–[N])
  - Deploy service infrastructure (CI/CD, observability, service mesh)
  - Extract lowest-risk, highest-value service first
  - Monolith continues to serve all traffic

Phase 2: First Extractions (Weeks [N]–[M])
  - Extract P1 services
  - API gateway routes selected traffic to new services
  - Monolith handles remaining traffic via facade pattern
  - Both paths write to shared DB during transition (dual-write)

Phase 3: Core Domain Services (Weeks [M]–[P])
  - Extract P1 core domain services
  - Data migration for extracted services
  - Remove dual-write paths for completed migrations

Phase 4: Monolith Retirement (Weeks [P]–[Q])
  - Extract remaining services
  - Monolith serves no production traffic
  - Decommission monolith infrastructure

Phase-by-Phase Roadmap

Phase	Service to Extract	Migration Approach	Team	Duration	Dependencies	Success Criteria
1	[service-name]	[Strangler facade / Branch by abstraction / Event interception]	[Team]	[X weeks]	[Infra ready, CI/CD pipeline]	[Traffic fully on new service, zero errors for 2 weeks]
2	[service-name]	[Approach]	[Team]	[X weeks]	[Phase 1 complete]	[Success metric]
3	[service-name]	[Approach]	[Team]	[X weeks]	[Phase 2 complete]	[Success metric]

Rollback Plan

For each migration phase, define the rollback trigger and mechanism:

• Rollback trigger: Error rate on new service > [X%] sustained for [Y minutes], or p99 latency > [threshold]
• Rollback mechanism: API gateway feature flag reverts all traffic to monolith path in < 5 minutes
• Data rollback: Dual-write maintained for [X weeks] after cutover to allow replay if needed

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8. Organizational Alignment (Conway's Law)

Conway's Law: the architecture of a system mirrors the communication structure of the organization that builds it. Design service ownership to match team boundaries — or change the team boundaries.

Service	Proposed Owner Team	Current Team Assignment	Change Required
[service-name]	[Team A]	[Same / Different]	[No change / Transfer to Team A / New team needed]
[service-name]	[Team B]	[Team A currently]	[Transfer ownership]

Misalignments identified:

• [Misalignment 1: e.g., "The notification service spans two teams today. Assign it entirely to Team B which already owns the messaging domain."]
• [Misalignment 2: e.g., "The reporting service is owned by Data Eng but consumers are Product teams — establish a clear API contract and SLA."]

Team topology recommendation: [Describe the recommended team structure — stream-aligned teams, platform team, enabling team — and how it maps to the proposed services.]

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9. Risk Register

Risk	Likelihood	Impact	Mitigation	Owner
Data consistency across services during migration	High	High	Dual-write with reconciliation job; event sourcing for critical domains	[Name]
Distributed transaction complexity (sagas)	Medium	High	Start with choreography; add orchestration only when choreography becomes unmanageable	[Name]
Service mesh operational overhead	Medium	Medium	Start without a mesh; add after 5+ services deployed	[Name]
Network latency replacing in-process calls	Medium	Medium	Cache aggressively; design read models to avoid chatty sync calls	[Name]
Conway's Law friction during transition	High	Medium	Align team structure before starting extraction, not after	[Name]
Over-decomposition (nanoservices)	Medium	High	Enforce minimum service size rule: a service must justify its own team/deployment overhead	[Name]
Observability gaps during migration	High	High	Deploy distributed tracing before first extraction; establish correlation IDs	[Name]
[Context-specific risk]	[Level]	[Level]	[Mitigation]	[Owner]

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Questions about this design: [Slack channel or contact]

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Quality Checks

• Bounded context map is an ASCII diagram with labeled relationships — not a prose description of the contexts
• Every service in the inventory table has a named team owner and a clear single-sentence responsibility statement
• Data ownership matrix assigns every key entity to exactly one owning service — no shared ownership
• Communication pattern decisions explain WHY sync vs. async was chosen for each interaction type
• If decomposing a monolith, the strangler fig migration plan has phases with durations, dependencies, and success criteria
• Risk register addresses at minimum: data consistency, distributed transactions, and Conway's Law alignment
• Organizational alignment section maps services to teams and identifies misalignments that need to be resolved