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设计与创意 · SKILL.md

microservice-researcher

microservice-researcher

【设计与创意】Guides research and analysis for microservices architecture decisions—domain decomposition, bounded contexts, service boundary options and trade-offs, sync vs async integration patterns, data ownership and consistency (eventual consistency, sagas at research level), API and contract evolution, Team Topologies alignment, build vs buy vs managed servic…

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name: microservice-researcher description: | Guides research and analysis for microservices architecture decisions—domain decomposition, bounded contexts, service boundary options and trade-offs, sync vs async integration patterns, data ownership and consistency (eventual consistency, sagas at research level), API and contract evolution, Team Topologies alignment, build vs buy vs managed services, monolith strangler migration, NFR impact (latency, reliability, operability), and decision records with options and recommendations. Use for microservice research, service boundaries, bounded context, strangler fig, monolith to microservices, saga vs two-phase commit, domain decomposition, microservices trade-off, team topologies, eventual consistency research, API versioning strategy—not assessing an existing estate (microservices-analyst), production service code (senior-software-engineer, platform-engineer), Kubernetes cluster ops only (cloud-engineer), pure network design (network-backbone-architect), or EDA implementation when building not researching

Microservice Researcher

When to Use

  • Research domain decomposition, bounded contexts, and candidate service boundaries
  • Compare microservices vs modular monolith (or other styles) with explicit trade-offs
  • Analyze sync vs async integration, data ownership, and consistency models at decision level
  • Evaluate saga vs 2PC, outbox, and choreography/orchestration without implementation tutorials
  • Define API and contract evolution strategy (versioning, compatibility, deprecation)
  • Plan monolith-to-microservices migration (strangler, parallel run, cutover criteria)
  • Align services with Team Topologies (stream-aligned, platform, enabling, complicated-subsystem)
  • Assess build vs buy vs managed for cross-cutting capabilities
  • Quantify NFR impact (latency budgets, reliability, operability, cost) per boundary option
  • Produce ADRs, options matrices, and research memos with a clear recommendation

When NOT to Use

  • Write or refactor production microservice code, handlers, or deployables → senior-software-engineer
  • Operate Kubernetes clusters, Terraform modules, or CI/CD pipelines only → platform-engineer, cloud-engineer, infrastructure-engineer
  • Design carrier/WAN routing, VPC topology, or physical network without application boundaries → network-backbone-architect
  • Implement brokers, outbox consumers, schema registry ops, or stream processing → event-driven-architecture (when building), microservices-developer
  • Enterprise portfolio strategy, operating model, and board-level where-to-play → enterprise-strategist
  • Load-test execution, caching implementation, and horizontal scale tuning only → high-concurrency-scalability
  • Cross-domain system architecture sign-off unrelated to service decomposition → senior-system-architecture (hand off when scope is whole-estate ADR)
  • Inventory, dependency maps, SLO gaps, API drift, or operational health on a live estate → microservices-analyst

Related skills

NeedSkill
Existing estate inventory, coupling, SLO/API drift, ops healthmicroservices-analyst
Cross-system ADRs, C4, estate-wide NFR sign-offsenior-system-architecture
Event contracts, brokers, outbox, sagas (implementation)event-driven-architecture
Service code, gRPC/REST, twelve-factor deployablessenior-software-engineer, microservices-developer
IDP, golden paths, paved roadsplatform-engineer
Cloud landing zone, IaC, cluster deliveryinfrastructure-engineer, cloud-engineer
Application throughput, caching, scale testinghigh-concurrency-scalability
Enterprise strategy, portfolio, org designenterprise-strategist
Enterprise API hub, iPaaS, B2B integration programsenterprise-integration-api-developer
Rollout, cutover, and rollback tacticsdeployment-strategist

Core Workflows

1. Frame the research question

Capture before comparing boundaries:

  • Business capability and measurable outcome
  • Constraints: teams, timeline, compliance, existing monolith/estate
  • Reversibility (one-way vs two-way door)
  • Non-goals and explicit out-of-scope peers

See references/microservice_researcher_scope.md.

2. Decompose the domain

Identify bounded contexts, ubiquitous language, and context maps (upstream/downstream, ACL, OHS).

Produce candidate services with ownership hypotheses—not a box diagram without data flow.

See references/domain_decomposition_and_boundaries.md.

3. Integration and consistency

For each boundary, document sync/async choice, data ownership, consistency model, and failure semantics.

Compare eventual consistency, saga compensation, and 2PC only when research warrants—not as default distributed transactions.

See references/integration_patterns_and_consistency.md.

4. Contracts and evolution

Define public API/event contracts, versioning rules, compatibility matrix, and deprecation timeline.

See references/api_contracts_and_evolution.md.

5. Migration and organization

Plan strangler slices, parity criteria, dual-write/read duration, and team alignment (Team Topologies).

See references/migration_strangler_and_org_alignment.md.

6. Deliverables and decision record

Package options matrix, NFR table, risks, recommendation, and follow-on owners (build vs research complete).

See references/research_deliverables_and_decision_records.md.

Principles

  • Research before split—boundaries follow domain and team cognition, not org chart alone
  • Prefer reversible experiments—strangler slices over big-bang when uncertainty is high
  • One writer per aggregate—document who owns each consistency boundary
  • Make trade-offs explicit—latency, ops burden, and team autonomy in the same table
  • Cite patterns and literature—DDD, Team Topologies, enterprise integration patterns—without cargo-culting microservices
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