Ingestion and replication: moving from detection in hours to detection in minutes.

It seems that currently, we only become aware of a problem once there is a visible impact on tracking or on the tables consumed by the business. In many cases, the root cause appears to occur much earlier—for instance, when a package or replication process stops running correctly, starts skipping steps, or begins to accumulate delays.

 Would it make sense to move toward earlier detection? I was thinking of something that periodically monitors data from `replication.package` and similar sources to identify anomalies before tracking alerts are triggered: Packages that haven't run in the last *N* minutes. Failed jobs. Recurring skips. Abnormal increases in the time between executions.

 Growing discrepancies between expected timestamps and actual processed timestamps. It could even evolve into an agent that not only alerts but also provides context: "Package X on server Y hasn't run for 35 minutes. The last execution failed, and the likely impact is on the BayCity tracking tables."

 My impression is that this could help us significantly reduce detection time, since we often end up investigating only after a delay of several hours has already built up. What do you think? Is there already a tool or monitoring system in place that addresses this need—one I might not be aware of? We are working with Azure Databricks; I was planning to implement this using an agent, but I need...