Find where your Databricksmoney and reliability leak.
LakeOps turns Databricks billing, job and compute metadata into prioritized cost, reliability and rightsizing findings — with evidence-first investigation guidance.
Efficiency overview
From raw operational signals to a clear next action.
LakeOps is designed around the questions engineering and FinOps teams actually need answered: what changed, what matters most, and where should we investigate first?
Cost intelligence
Detect workload-level cost spikes, rank cost drivers and quantify optimization opportunities against recent baselines.
Reliability intelligence
Surface failed jobs, retry patterns and runtime regressions so teams know which workload to investigate first.
Rightsizing signals
Use CPU and memory posture to identify low-utilization compute that deserves downsizing or scheduling review.
Evidence-first RCA
Keep deterministic Python/SQL facts separate from hypotheses, with confidence and verification steps attached to findings.
Simple enough for V0. Built to become continuous later.
The first design-partner workflow intentionally avoids complex infrastructure. Once customers validate the value, the same engine becomes a continuous read-only Databricks connector.
Collect metadata
Start with sanitized Databricks billing, job-run and compute metadata. No table contents are required for V0.
Analyze deterministically
LakeOps calculates spend, baselines, failure rates, retries, runtime changes and utilization using Python and SQL.
Prioritize action
Findings are ranked by severity, confidence and estimated impact, then packaged into an engineering-ready audit.
Operational intelligence without asking for your business data.
For early design partners, the collector can run inside the Databricks environment and transfer sanitized operational metadata or findings. LakeOps V0 does not need raw table contents, credentials, SQL text or customer records to calculate its core signals.
Have a Databricks environment? Let LakeOps scan it free.
We’re looking for the first five teams willing to share feedback on the cost, reliability and compute findings. The V0 scan is free while we validate the workflow.