Budget Burn Control
70% says act. 90% says ask. CloudPi combines threshold alerts, remediation workflows, and forecast-increase requests so every overrun has a remediation, not a retrospective.
The problem
By the 12th, half the budget is gone. The exports back it up: autoscale never dialed down after launch. Azure managed disks stuck around post-sprint. One BigQuery job quietly doubled scans. Finance sees a mid-month blowout and cannot close Variance Review. Engineering fields "who owns this?" Product parks work until a credible number lands.
Same pattern in prod and dev - compute, storage, and egress doing most of the damage.
How CloudPi fixes it
Onboard in 30 minutes. Connect Azure (or AWS, GCP) billing. Create policy rules. Group accounts into projects. Invite owners by email.
Three plan numbers. Budget (Finance ceiling). Forecast (owner-entered dollars, sprint-planned). Projected (CloudPi nightly extrapolation).
Staged threshold alerts. Two emails, not one:
- 70% burn - Review email. FinOps reviews remediation activity. Owner is nudged to approve ADO remediation tickets sitting in the queue.
- 90% burn - Escalation email. Suggests a forecast-increase request.
Remediation runs on the owner's trust. Start with ticket-only (every finding opens an ADO ticket, human approves). Graduate to gated (fix pre-staged, 1-click approval). Arrive at auto-save (CloudPi executes, saving recorded, no ticket needed). The owner controls how fast.
Forecast-increase requests carry their why. Owner submits "+$10K for this year - Feature Y." Under 10% auto-approves. Over 10% routes to FinOps. Standing note: clear outstanding recommendations before asking for more.
Outcomes
| Metric | Before | After |
|---|---|---|
| On-demand compute | Baseline | -12% |
| Total monthly spend | Baseline | -7% |
| Overspend incidents | Baseline | -70% |
| Forecast variance | +/-19% | +/-10% |
Finance closes one day faster. Engineering reclaims ~2 sprint-days per month. Product plans with burn rates they can trust.
Features used
- Budget and forecast management
- Policy-based recommendations (threshold alerts)
- Workflow automation (Review email / Escalation email / Auto-save)
- ADO / Azure / ServiceNow ticket integration
- Cost assignment rules
- Self-service dashboards
Stop chasing. Start closing. Book a Demo