Observability for
Advanced
Data Engineering
Proactively prevent bad data and quickly root cause issues, automatically. On-prem or cloud.
When your data operation is…
Inside-out data pipeline observability designed for Spark-heavy teams
Shift observability to post-production and let data developers focus on business value
Stop guessing what’s going on
Holistic Monitoring
Establish full visibility
→ maintain data platform health
Out-of-the-box granular metrics collection & monitoring
Data quality, pipeline runs, infra performance
Stop chasing coverage, writing tests manually
Automated coverage
Reduce manual effort
→ increase data developers velocity
Auto-generated tests in post-production, with no manual coding
Dynamic anomaly detection evolving with data & behavior
Stop pulling teeth when you root-cause
CONTEXTUALIZED RCA
Root-cause issues quickly
→ minimize downstream impact
Rich execution context, with runs, code, schema, & env tracking
Deep column-level data lineage, automatically built
Pinpointed actionable alerts
Stop catching bad data too late
Proactive protection
Detect issues in real-time
→ prevent issue propagation
Real-time testing, in-line with the pipeline runs
Automatic runs preemption, with no code changes
Stop wasted runs & resources
Intelligent savings
Optimize infra performance
→ save costs
Monitoring infra resources, CPU, and pipeline SLAs
Smart auto-recommendations
