Observe, fix, and optimize
Lakehouse & Spark pipelines — in-motion

Monitor data, jobs, and performance in real time – with zero code changes.

Proactively cut costs, prevent incidents,
and troubleshoot issues

Cost & Performance Optimization

Cut platform costs and ensure SLAs with job-level optimizations and auto-tuning.

Pinpoint CPU & memory overprovisioning, job inefficiencies, and run time bottlenecks.

Profile job execution over time, detect degradations, and identify savings opportunities.

Easily optimize with job-specific recommendations and 1-click auto-tuning.

In-Motion Observability

Prevent incidents in real-time with inline job monitoring and full-stack coverage.

Monitor your entire data stack in one place - data, jobs, usage, infra, and cost.

Detect anomalies out-of-the-box with AI-powered detection.

Prevent issues in real-time with automated run preemptions.

Actionable RCA

Simplify troubleshooting with actionable lineage, context, and insights.

Automated column-level lineage connecting datasets, jobs, and transformations.

Contextualized job execution with transformation, code, and env tracking.

A single pane of glass for actionable alerts, intuitive UI, AI-powered insights.

CI/CD Testing

Accelerate platform upgrades and pipeline code-changes with seamless validation in CI.

Automatically simulate runs in staging without re-routing data or manual setup.

Catch data issues and performance regressions before they reach production.

Pinpoint issues to specific changes in code, inputs, or environment.

Seamless Instrumentation

Central one-time installation
with zero code changes.

Scale observability E2E across all workloads, in <15 minutes

Secure by design - runs 100% in your environment. Data never leaves.

Proven Results, Fast

50%
infra cost reduction
90%
prevented data incidents
25%
increased data engineering velocity
50%
faster deployments & upgrades

Stop firefighting. Standardize proactive observability.

Let data developers focus on business value

Infra cost savings

  • Optimize resource utilization at job-level
  • Proactively detect degradations

Infra cost savings

Prevented data incidents

  • Scale data & pipeline coverage to 100%
  • Detect immediately - zero time to detect

Prevented data incidents

Increased dev velocity

  • Minimize time to root-cause & tune jobs
  • Eliminate manual checks & validation

Increased dev velocity

Faster deployments

  • Accelerate platform upgrades & migrations
  • De-risk ongoing pipeline code-changes

Faster deployments

Regain trust in data

  • Ensure data quality, job SLA, platform health
  • Restore data team’s reputation

Regain trust in data

Establish eng standards

  • Increase consistency and accountability
  • Dynamically enforce standards & contracts

Establish eng standards

Ready to shift to proactive observability?

Easily optimize jobs, prevent incidents in real-time, and root-cause issues with full context.
No code changes. Secure in your environment.