🤖 AI Summary
本文提出了一种服务健康工程方法，通过结合遥测、工作流完成情况等手段来检测分布式系统中的静默故障和异步工作停滞问题。
📝 Abstract
Distributed systems support many critical business workflows, but service health is often judged through component dashboards rather than through end-to-end user outcomes. This article presents service health engineering as a practical reliability discipline that connects telemetry, workflow completion, dependency behavior, operational readiness, and recovery validation. Using a document approval workflow as a running example, it describes how service promises, service-level indicators and objectives, watchdogs, incident measures, resiliency testing, and weekly service-health reviews can reveal silent failures and stranded asynchronous work. It also presents a human-reviewed, AI-assisted reporting architecture for assembling service-health evidence without making AI an autonomous decision-maker. The approach brings established reliability practices together around whether user journeys complete as promised.