For teams
Data Reliability Engineering With Real Observability
Run data reliability engineering like SRE for data: set SLAs, monitor every pillar, track incidents, and measure data downtime over time.
Alerted #data-eng 0.8s ago.
Downstream impact · consumers at risk
In one paragraph
Data reliability engineering applies SRE principles to data: defining SLAs for freshness and quality, monitoring them continuously, and tracking incidents to reduce data downtime. Dataobservability gives you the SLAs, anomaly detection, end-to-end lineage, and incident history to run that practice and prove your data is getting more reliable over time.
Why it fits
Teams formalizing data reliability with SLAs, on-call, and incident review.
Data SLAs you can measure
Set and monitor freshness and quality SLAs per table and report on them.
Incident tracking and MTTR
Every break becomes a tracked incident, so you can measure mean time to resolution.
Reduce data downtime
Lineage and anomaly detection shrink detection and resolution time.
Live in 15 minutes
Connect your warehouse and watch monitors generate across every table. Transparent pricing, no credit card.