PIPELINE HEALTH
Data Pipeline Monitoring for Warehouse and dbt
Data pipeline monitoring that ties warehouse freshness and volume to your orchestration, so a paused sync or a failed dbt run becomes an alert, not a fire drill.
Alerted #data-eng 0.8s ago.
Downstream impact · consumers at risk
What is data pipeline monitoring?
Data pipeline monitoring tracks the health of the jobs and tables that move and transform your data. Dataobservability combines warehouse freshness and volume signals with orchestration context from tools like Airflow and Fivetran, so when a pipeline stalls or runs late you are alerted with the affected tables and downstream impact already identified.
Last updated July 2026
What you get
Built for data pipeline monitoring
Freshness tied to orchestration
Connect a late table to the paused sync or failed job that caused it.
Volume and run-time anomalies
Catch loads that ran but delivered far too few or too many rows.
End-to-end visibility
Source to warehouse to dashboard in one lineage graph, so pipeline issues show their blast radius.
Alerts your on-call acts on
Grouped, routed alerts in Slack and PagerDuty instead of a wall of cron emails.
How it works
From connected to caught
Connect warehouse and tools
Add your warehouse plus orchestration signals from Airflow or your loader.
Monitor every table
Freshness and volume monitors generate automatically across the pipeline.
Correlate failures
A late or thin table is linked to the upstream job that explains it.
Resolve and track
Open an incident, assign an owner, and close the loop with a root cause.
Catch broken data before your stakeholders do
Connect your warehouse and get data pipeline monitoring live in 15 minutes. Transparent pricing, no credit card.