- 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.
5.9 KiB
08. 可观测性
决策
统一 Trace ID + 结构化(JSON)日志 + Micrometer 指标,对应架构图 Cross-Cutting 里的 Observability 要求;关键行为单独走审计日志通道,对应 Audit / Security。
结构约定
platform-observability/
TraceIdFilter # 入口生成/透传 traceId,写入 MDC
logback-spring.xml # 结构化日志格式配置
MetricsConfig # Micrometer 基础配置,暴露 /actuator/prometheus
AuditLogAspect # AOP 切面,标注 @Audited 的方法自动记录审计日志
TraceIdFilter 示例
// platform-observability/.../TraceIdFilter.kt
class TraceIdFilter : OncePerRequestFilter() {
override fun doFilterInternal(request: HttpServletRequest, response: HttpServletResponse, chain: FilterChain) {
val traceId = request.getHeader("X-Trace-Id") ?: UUID.randomUUID().toString()
MDC.put("traceId", traceId)
response.setHeader("X-Trace-Id", traceId)
try {
chain.doFilter(request, response)
} finally {
MDC.clear() // 必须清理,否则线程池复用线程会带出上一个请求的 traceId
}
}
}
object TraceIdHolder {
fun current(): String = MDC.get("traceId") ?: "unknown"
}
调用 F6/Mini 域时,把当前 traceId 透传到下游请求头,方便跨系统关联日志:
webClient.get()
.uri("/f6/procurement/list")
.header("X-Trace-Id", TraceIdHolder.current())
.retrieve()
// ...
结构化日志配置示例
<!-- logback-spring.xml -->
<configuration>
<appender name="JSON" class="ch.qos.logback.core.ConsoleAppender">
<encoder class="net.logstash.logback.encoder.LogstashEncoder">
<includeMdcKeyName>traceId</includeMdcKeyName>
<customFields>{"app":"conti-backend"}</customFields>
</encoder>
</appender>
<root level="INFO">
<appender-ref ref="JSON" />
</root>
</configuration>
// build.gradle
implementation 'net.logstash.logback:logstash-logback-encoder:7.4'
输出的每条日志会带上 traceId 字段,直接对接现有 ELK 方案(见 Architecture-Diagram/ODP ELK Logging Solution Project - Overview.pdf)时可以直接按 traceId 过滤出一次请求的完整链路日志。
Micrometer / Actuator 配置
# application.yml
management:
endpoints:
web:
exposure:
include: health, prometheus, info
endpoint:
health:
probes:
enabled: true # 暴露 /actuator/health/liveness、/readiness,供 K8s 探针使用
implementation 'org.springframework.boot:spring-boot-starter-actuator'
implementation 'io.micrometer:micrometer-registry-prometheus'
审计日志示例
// platform-observability/.../Audited.kt
@Target(AnnotationTarget.FUNCTION)
@Retention(AnnotationRetention.RUNTIME)
annotation class Audited(val action: String)
// platform-observability/.../AuditLogAspect.kt
@Aspect
@Component
class AuditLogAspect(private val storeContextHolder: StoreContextHolder) {
private val auditLog = LoggerFactory.getLogger("AUDIT")
@Around("@annotation(audited)")
fun logAudit(joinPoint: ProceedingJoinPoint, audited: Audited): Any? {
val result = runCatching { joinPoint.proceed() }
auditLog.info(
"action={} userId={} storeId={} traceId={} success={}",
audited.action, storeContextHolder.userId, storeContextHolder.storeId,
TraceIdHolder.current(), result.isSuccess,
)
return result.getOrThrow()
}
}
// 使用方式
@Audited(action = "WEBVIEW_TICKET_ISSUE")
fun issueTicket(userId: Long, storeId: Long): WebviewTicket { ... }
审计日志走独立 logger(AUDIT),在 logback-spring.xml 里单独配置一个 appender 写到专门的审计日志文件/索引,不和普通业务日志混在一起,方便设置更长的保留期和更严格的访问权限。
关键规则
traceId从入口 filter 生成,贯穿到f6-integration/mini-clients调用外部系统,失败时把traceId一起返回给前端(已经在 06-api-design.md 的ApiResult里),方便排障(对应架构图 Flow 2 的"失败可支持排障"要求)。- 审计相关的关键行为(登录、换票、供应商调用失败)走单独的审计日志通道,不和普通业务日志混在一起。
- 日志/指标最终对接现有 ELK 方案,具体接入方式(Filebeat 采集 stdout,还是直接推 Logstash)待确认。
附录:为什么要在 MDC 里放 traceId,而不是每条日志手动传参
不用 MDC 的话,每个方法打日志都要显式传 traceId 参数:log.info("traceId={} 门店切换成功", traceId),深层调用链里每一层都要多加一个参数,代码侵入性很强,还容易漏传。MDC(Mapped Diagnostic Context)是日志框架提供的"线程内隐式上下文",在 filter 里设置一次,同一线程内后续所有日志调用(不管调用链多深)都会自动带上这个字段,日志格式配置里声明 includeMdcKeyName 即可,业务代码完全不需要感知 traceId 的传递。
代价和 04-security-auth.md 里提到的 ThreadLocal 类似:MDC 底层也是 ThreadLocal 实现的,异步线程池、协程切换线程的场景需要手动透传(MDC.getCopyOfContextMap() 传给子线程),我们当前同步 Servlet 栈下不需要特殊处理,但如果某个模块引入异步处理要注意这一点。
待补充
- 具体接入现有 ELK / APM 的方式和字段规范。
- 审计日志的存储和保留策略。