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AI Skill Report Card

Architecting Enterprise Systems

A-85·Aug 17, 2026·Source: Web

Quick Start14 / 15

When given a system requirement (e.g., "design an order management system"), immediately produce these outputs together — never partially:

Architecture layers
Module relations
Event flow
API flow
Deployment flow
Folder structure

Example trigger: "Design architecture for a payment processing service." Response: Full architecture package below (see Example 1).

Recommendation▾

Add a second example (e.g., a different domain like inventory or notification system) to demonstrate variability and reduce reliance on a single template output.

Workflow15 / 15

Progress:

Step 1: Clarify domain boundaries (what business capability does this system own?)
Step 2: Define architecture layers (presentation, application, domain, infrastructure)
Step 3: Define modules/services and their relations (dependency direction, shared kernel vs. isolated)
Step 4: Design event-driven flow (producers, consumers, event topics/queues, retry/DLQ strategy)
Step 5: Design API flow (endpoints, request/response contracts, sync vs async, gateway routing)
Step 6: Design deployment flow (CI/CD stages, containers, scaling strategy, environments)
Step 7: Produce folder structure (mirrors architecture layers and module boundaries)
Step 8: Validate scalability (identify bottlenecks, stateless services, horizontal scaling points)

Step Details

Architecture Layers — Always structure as:

Presentation Layer (API Gateway / Controllers)
Application Layer (Use cases / Orchestration / CQRS handlers)
Domain Layer (Entities, Value Objects, Domain Events, Business Rules)
Infrastructure Layer (DB, Message Broker, External Integrations)

Module Relation — Define per module:

Owns which domain entities
Depends on which modules (one-directional where possible)
Exposes which contracts (API/event)
Shared kernel items (if any) kept minimal

Event Flow — Always specify:

Event name (past-tense, domain-driven: OrderPlaced, PaymentConfirmed)
Producer module
Broker/topic (Kafka topic / RabbitMQ exchange)
Consumer module(s)
Failure handling (retry policy, dead-letter queue)

API Flow — Always specify:

Client → API Gateway → Service → Domain → Infra
Sync (REST/gRPC) vs Async (event) decision per endpoint
Versioning strategy (/v1/)
Auth/authorization checkpoint

Deployment Flow — Always specify:

Build → Test → Containerize → Push Registry → Deploy (per env: dev/staging/prod)
Orchestration (Kubernetes namespace/service/deployment)
Scaling policy (HPA, resource limits)
Observability hooks (logging, tracing, metrics)

Folder Structure — Always mirror layers per module (modular monolith or microservice), e.g.:

src/
  modules/
    order/
      api/
      application/
      domain/
      infrastructure/
    payment/
      api/
      application/
      domain/
      infrastructure/
  shared/
    kernel/
    events/
  gateway/

Recommendation▾

Include a 'bad output' contrast example (e.g., tightly coupled monolith design) to sharpen the good-vs-bad distinction expected in top-tier skills.

Examples15 / 20

Example 1: Input: "Design architecture for a payment processing service."

Output:

Architecture Layer

Presentation: REST API Gateway (/v1/payments)
Application: ProcessPaymentUseCase, RefundPaymentUseCase
Domain: Payment entity, PaymentStatus VO, PaymentConfirmed domain event
Infrastructure: Postgres (payment records), Kafka (event bus), Stripe adapter

Module Relation

payment-service owns Payment entity
Depends on order-service (read-only, via event OrderPlaced)
Exposes PaymentConfirmed, PaymentFailed events
No direct DB access from other modules (contract-first)

Event Flow

OrderPlaced (from order-service) → consumed by payment-service → triggers ProcessPaymentUseCase
On success: publish PaymentConfirmed → consumed by order-service & notification-service
On failure: publish PaymentFailed → retry 3x with exponential backoff → DLQ after exhaustion

API Flow

Client → API Gateway (/v1/payments) → Auth middleware → PaymentController → ProcessPaymentUseCase → Domain validation → Stripe adapter → DB persist → Event publish

Deployment Flow

Build (Docker) → Unit/Integration Test → Push to registry → Deploy to payment-svc namespace in K8s → HPA min 2/max 10 pods → Prometheus + Grafana + Jaeger tracing

Folder Structure

payment-service/
  api/
    controllers/
    dto/
  application/
    use-cases/
  domain/
    entities/
    events/
    value-objects/
  infrastructure/
    db/
    kafka/
    stripe-adapter/

Recommendation▾

Add brief guidance on choosing between microservices vs modular monolith with concrete criteria (team size, deploy cadence thresholds) rather than just 'unless scale/team-autonomy justifies'.

Best Practices

Always design for loose coupling, high cohesion — modules communicate via contracts (API/events), never shared database tables.
Prefer async event-driven communication for cross-module workflows; reserve sync API calls for real-time user-facing reads.
Always define idempotency for event consumers (duplicate delivery is expected).
Always include versioning in APIs and schema evolution strategy for events (backward compatible).
Always design stateless services to support horizontal scaling.
Include observability (logs, metrics, traces) as a first-class architecture concern, not an afterthought.
Default to modular monolith structure unless scale/team-autonomy explicitly justifies microservices.

Common Pitfalls

Do NOT skip any of the 6 mandatory outputs (layer, module relation, event flow, API flow, deployment flow, folder structure) — always deliver the full set.
Do NOT allow modules to share a database schema directly — this breaks service boundaries.
Do NOT design synchronous chains across more than 2-3 services — leads to cascading failures; use events instead.
Do NOT ignore failure/retry semantics in event flows — always specify DLQ and backoff.
Do NOT propose toy/prototype-grade design — always assume production-grade: security, scalability, observability included.