Orchestration Monitoring

DAGs, workflows, and scheduled jobs — the layer that decides when your ETL actually runs
Jobs tracked

164

+9
Runs (24h)

3,428

+184
Failing jobs

27

last run red
Overdue jobs

4

past their usual spacing

Job health

Worst first. A job can be late, slow, or moving a fraction of its usual rows without a single run going red — the schedule is learned from each job's own history, not declared.

JobPlatformScheduleLast runDurationStatus
hourly_customer_sync

3h late

Talend~1h01:00 UTC1m 2sOverdue
gold_build

Py4JJavaError: Job aborted

Databricks~6h02:10 UTC5sFailing
nightly_customer_load

4.0x usual runtime

Control-M (DC1)~24h01:00 UTC40m 8sSlow
customer_extract

900 rows vs 10,000 usual

Informatica PowerCenter~24h00:30 UTC2m 4sVolume drop
invoice_integration
Dell Boomi~2m03:12 UTC11sHealthy

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