feat: Add comprehensive documentation for integration layer, API design, config governance, observability, build/deploy, and testing strategies

- Introduced integration layer design with Resilience4j for external vendor calls.
- Established API design standards with unified response structures and global exception handling.
- Defined configuration and service governance using Kubernetes native solutions.
- Implemented observability practices including trace ID propagation and structured logging.
- Outlined build and multi-environment deployment strategies using Gradle and GitLab CI/CD.
- Specified testing strategies across different layers, utilizing JUnit, MockK, Testcontainers, and WireMock.
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# 03. 持久层方案
## 决策
Spring Data JPA + Hibernate 作为默认 ORMFlyway 做 schema 迁移。
选 JPA 而不是 MyBatis-Plus / jOOQ,主要考虑:
- Kotlin + Spring Boot 生态里 JPA 是最主流、文档和踩坑资料最多的组合,团队上手成本低。
- 大部分 domain 模块(`identity-store``webview-ticket` 等)都是常规 CRUD + 少量关联查询,JPA 默认能力够用;真的遇到复杂查询,用 `Specification` 或原生 SQL`@Query(nativeQuery = true)`)兜底,不需要为了少数复杂查询把整个技术栈换成 jOOQ。
- 如果某个 domain 后续查询复杂度明显上升(比如报表类需求),可以在那个模块单独引入 jOOQ 只处理复杂查询,两者不互斥。
## 结构约定
```
platform-persistence/
BaseEntity # 审计字段:createdAt/updatedAt/createdBy/updatedBy,各 domain entity 继承
PageResult<T> # 统一分页返回封装
JpaAuditingConfig # 开启 Spring Data JPA Auditing
domains/xxx/
src/main/kotlin/.../xxx/infrastructure/persistence/
XxxEntity # JPA entity
XxxJpaRepository # : JpaRepository<XxxEntity, Long>
src/main/resources/db/migration/xxx/
V1__init.sql # Flyway migration,按 domain 分子目录
```
## `BaseEntity` 示例
```kotlin
// platform-persistence/src/main/kotlin/.../BaseEntity.kt
@MappedSuperclass
@EntityListeners(AuditingEntityListener::class)
abstract class BaseEntity {
@CreatedDate
@Column(nullable = false, updatable = false)
var createdAt: Instant = Instant.EPOCH
@LastModifiedDate
@Column(nullable = false)
var updatedAt: Instant = Instant.EPOCH
@CreatedBy
@Column(updatable = false, length = 64)
var createdBy: String? = null
@LastModifiedBy
@Column(length = 64)
var updatedBy: String? = null
}
// platform-persistence/src/main/kotlin/.../JpaAuditingConfig.kt
@Configuration
@EnableJpaAuditing(auditorAwareRef = "auditorAware")
class JpaAuditingConfig {
@Bean
fun auditorAware(): AuditorAware<String> = AuditorAware {
Optional.ofNullable(StoreContextHolder.currentUserIdOrNull()?.toString())
}
}
```
`auditorAware` 直接读 [04-security-auth.md](./04-security-auth.md) 里的 `StoreContextHolder`,避免每个 domain 各写一份"当前操作人是谁"的逻辑。
## Entity + Repository + Migration 示例(`identity-store` 里的门店表)
```kotlin
// infrastructure/persistence/StoreEntity.kt
@Entity
@Table(name = "store", schema = "identity_store")
class StoreEntity(
@Id @GeneratedValue(strategy = GenerationType.IDENTITY)
val id: Long = 0,
@Column(nullable = false, length = 128)
var name: String,
@Column(name = "code", nullable = false, unique = true, length = 32)
var code: String,
@Enumerated(EnumType.STRING)
@Column(nullable = false, length = 16)
var status: StoreStatus,
) : BaseEntity()
@Repository
interface StoreJpaRepository : JpaRepository<StoreEntity, Long> {
fun findByCode(code: String): StoreEntity?
fun findByStatus(status: StoreStatus): List<StoreEntity>
}
```
```sql
-- src/main/resources/db/migration/identity_store/V1__init.sql
create schema if not exists identity_store;
create table identity_store.store (
id bigint generated always as identity primary key,
name varchar(128) not null,
code varchar(32) not null unique,
status varchar(16) not null,
created_at timestamp not null,
updated_at timestamp not null,
created_by varchar(64),
updated_by varchar(64)
);
```
Flyway 版本号(`V1``V2`…)在同一个 schema 目录下按提交顺序递增,不同 domain 目录之间的版本号互相独立,互不干扰。
## 跨 domain 数据访问规则
**每个 domain 独立 schema**:即使同一个数据库实例,各 `domains/*` 的表也归属各自 schema,不允许跨 domain 直接 `join` 表——需要数据时通过对方模块暴露的 `application` 层接口调用,保持模块边界(即使将来要拆分微服务,DB 层面也不用重新拆分)。
```kotlin
// 错误示范:workbench 直接 join identity_store 的表
@Query("""
select w from WorkbenchTileEntity w
join StoreEntity s on s.id = w.storeId -- 跨 schema 直接 join,禁止
""")
fun findTilesWithStoreInfo(): List<WorkbenchTileEntity>
// 正确做法:workbench 通过 identity-store 暴露的接口获取门店信息
@Service
class WorkbenchAppService(
private val storeQueryService: StoreQueryService, // identity-store 模块对外暴露的接口
private val tileRepository: WorkbenchTileRepository,
) {
fun listTiles(userId: Long): List<TileResponse> {
val stores = storeQueryService.listStoresByUserId(userId) // 走 application 层调用,不查表
val tiles = tileRepository.findByUserId(userId)
return buildTiles(tiles, stores)
}
}
```
## 附录:为什么坚持"每个 domain 独立 schema"
模块化单体最容易被破坏的地方就是数据库——代码层面 Gradle 依赖规则挡住了跨 domain import 类,但如果两个 domain 的表都在同一个 schema 下,写 SQL 的时候很容易"顺手 join 一下",这条规则完全不受编译器约束,只能靠约定。所以我们把 schema 拆开:`workbench``DataSource` 配置的默认 schema 是 `workbench`,即使有人手滑写了一条跨 schema 的 join,大概率会因为找不到表或者权限问题直接报错,把"容易被绕开的软约束"变成"大概率会失败的硬约束"。
代价是:如果确实需要跨 domain 做一次性数据修复或报表查询,不能简单写 SQL join,要么走各自暴露的接口拼装,要么走专门的数据同步/报表管道——这是有意为之的摩擦,用来保护长期的模块边界。
## 待补充
- 具体数据库选型(PostgreSQL/MySQL)和实例划分方式(同实例多 schema,还是多实例)。
- 复杂查询是否引入 QueryDSL/jOOQ`Specification` 不够用时再决定)。
- 各 domain 的实际表结构,等开发到对应模块时再补。
## 参考链接
- [Spring Data JPA 官方文档](https://docs.spring.io/spring-data/jpa/reference/)
- [Flyway 官方文档](https://documentation.red-gate.com/fd)
- [Spring Data JPA Auditing](https://docs.spring.io/spring-data/jpa/reference/auditing.html)