Why SaaS downtime monitors should track pipeline workflows, not just endpoint uptime

An engineering guide argues that a 200 response from a service does not prove a multi-service SaaS nightly pipeline can read, transform, and publish data. It recommends separating liveness from readiness checks and treating endpoint availability only as a symptom. The proposed approach models the nightly job as a state machine, emitting structured events tied to a run identifier so incidents can be reconstructed in order. Alerts should be based on an SLO measuring whether scheduled runs are verified on time, with component checks explaining breaches. The article also stresses keeping sensitive data such as tokens and customer payloads out of logs.