Data Pipeline Monitoring: Start With These 5 Alerts

Most monitoring setups fail for one reason: too many alerts, no clear owner.

Start with a small baseline that catches business-critical breakages quickly.

The first 5 alerts to implement

1. Freshness breach on key dashboard models.
2. Row count anomaly on core fact tables.
3. Null-rate spike on critical business columns.
4. Task failure in orchestration for revenue-impacting DAGs.
5. Late source delivery from external APIs or files.

Add ownership to every alert

Every alert needs:

• an owner
• an escalation path
• a response expectation

Without this, alerts become noise.

Keep thresholds simple and clear

Use static thresholds first. Add advanced logic later.

select
  count(*) as orders_today
from analytics.orders_clean
where created_at >= current_date;

When this number drops outside expected range, alert with context: last good run time, upstream job status, and impacted dashboards.

Weekly reliability review

Run a 20-minute weekly review:

• Which alerts fired?
• Which were actionable?
• Which were noisy?
• What guardrail is still missing?

Pipeline reliability comes from routine, not one-time setup.