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Your Databricks DBUs hide the waste. Cloudgov.ai finds it.
Read only and agentic. Connect your Databricks workspace once and let Cloudgov.ai turn system tables, cluster patterns, SQL warehouse usage, and DBU consumption into continuous FinOps outcomes.
Waste identified across oversized clusters, idle warehouses, job compute, and Delta storage overhead this quarter.
Every Databricks DBU, continuously optimized
From cluster rightsizing to SQL warehouse tuning, job scheduling to Delta storage cleanup. Cloudgov.ai's agentic AI reads your Databricks workspace, surfaces the wins, and executes with human in the loop guardrails.
Agents analyze cluster utilization, spot fallback, and auto scaling patterns to recommend node types, driver sizing, and auto termination policies. Approve in one click or auto apply in non production workspaces.
Identify oversized warehouses, idle serverless clusters, and query patterns that would run faster and cheaper on a different warehouse tier. Route recurring queries to the right compute automatically.
Detect notebooks running on all purpose compute that should be scheduled jobs instead. Convert workloads to job compute for material savings on repeatable pipelines.
Identify unused tables, stale Vacuum candidates, and unoptimized Delta files. Reclaim DBUs by adjusting retention and running OPTIMIZE where it matters most.
Learns your workspace's normal DBU consumption per job, per user, and per warehouse. Catches runaway queries, mispriced clusters, and forgotten workloads before end of month.
Virtual tagging via cluster policies, job tags, or workspace mapping. Attribute every DBU to a team, product, or downstream customer, without touching underlying data.
Connect once. Optimize continuously.
Under 15 minutes to full read only access across your Databricks workspace. No customer data ever leaves Databricks.
Create a read only service principal in your Databricks workspace with can_view on system tables and audit logs. Cloudgov.ai never reads customer data.
Grant SELECT on system.billing.usage, system.compute, and system.query_history. Cloudgov.ai reads only usage and metadata, never customer content.
Activate BillingShield to route your Databricks invoice, ContainerShield for compute allocation, and MulticloudShield to unify DBUs alongside your cloud spend.
Read only. FOCUS native. Agentic, not just analytical.
Read only, always
Cloudgov.ai never writes to or mutates your AWS accounts. Actions land as tickets, IaC diffs, or approvals in your existing workflow.
FOCUS native
Ingests the FinOps Open Cost & Usage Spec directly. Add Azure, GCP, and OpenAI later without re modeling anything.
Agentic outcomes
Findings flow into policy, approvals, tickets, and chargeback. Not another dashboard. Real actions with real audit trails.
The Databricks integration unlocks four Shields
Each Shield is an autonomous domain of FinOps outcomes. Turn them on independently, or run all four together for full AWS coverage.
Route your Databricks invoices through Cloudgov.ai. Unlock 2 to 5% back on every dollar and 30 day payment terms, no architecture changes.
DBU commitments managed per workspace. Continuous coverage optimization, drawdown forecasting, and expiration alerts before they hurt.
Cluster and warehouse level DBU allocation across teams, jobs, and products. Query attribution, cluster policies, and job compute cost visibility.
Unified visibility, allocation, and optimization across AWS, Azure, and GCP on the FOCUS spec. One view, one policy, one chargeback.
Real numbers, from real Databricks environments
Illustrative, benchmark aligned ranges. Your results will vary by environment.
On rightsizing, commitments, and waste, guaranteed on qualified engagements.
Service principal connects, system tables sync, agents surface top cluster savings automatically.
No writes to your accounts. Every action routed through your existing approval flow.
Ready to see your Databricks spend in a way that finally makes sense?
15 minute demo, real numbers on your environment, no long term commitment.