BetishOpsObservation and period
Every record has a time. Coverage evaluates the expected set for the interval, not just its last reading.
BetishOps. Your SAP operations, explained with evidence. An alert reveals a symptom. Understanding it requires knowing what happened, when it changed, and which observations support it. This walkthrough uses illustrative data.
Observation starts at the source: processes, queues, jobs, sessions, and resources. Each extraction retains its context and observation time. Jobs organize collection, while coverage separates a complete observation from information that is still missing.
History turns those observations into a sequence. In this example, the queue grows from twelve to one hundred and eighty-four pending records. Daily close brings the period's evidence together and shows its coverage, without hiding missing intervals.
Indicators connect a measurement to a question: how much did the queue grow, how long has the oldest record been waiting, and what changed since the previous period? From source to history, and from an indicator to its evidence. BetishOps: fewer isolated signals, clearer decisions.