Observability for
Data Engineering

Proactively prevent bad data and quickly root cause issues, automatically. On-prem or cloud.

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When your data operation is…

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Inside-out data pipeline observability designed for Spark-heavy teams

Shift observability to post-production and let data developers focus on business value

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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
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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


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
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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
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Single-point one-time installation.
No code changes. Zero-config.
Immediate insights.

Single-point one-time installation.
No code changes.
Immediate insights.

Book a demo