The team was moving fast. A new feature needed testing, so someone spun up a high-memory instance on GCP. They meant to shut it down. They didn't.
Sixteen days later, the finance lead was scanning billing trends. That's when they saw it: a slow, silent spike that added up to $42,000—burned on test data that no one was using.
It wasn't the first time something slipped through. But this one hit hard. For a high-growth startup, that wasn't just money—it was 11% of their quarterly runway, gone without warning.
And what hurt more wasn't just the cost. It was how long it took to trace the why.
Here's where things broke down:
No real-time visibility into cost drift The GCP console only showed cumulative spend. No one noticed the increase day by day because no alerts were set at the granular level. It wasn't a spike—it was a bleed, and no one saw it coming.
Disconnected views between DevOps and Finance Engineering saw the resource but didn't track its spend. Finance saw the invoice but didn't know which team or workload caused it. The delay in connecting usage to cost caused unnecessary tension and rework.
Billing alerts without context The GCP alert triggered after the cost had already crossed the threshold. But it didn't show which role created the instance, or why it wasn't shut down. By the time they got answers, the quarter had already taken a hit.
That's when they brought in Cloudshot—not as a report generator, but as a real-time cost intelligence engine.
Cloudshot connected to their cloud within minutes. It learned the spending baseline, mapped live usage, and—most critically—it brought teams together around the same data.
Here's what changed:
Live Cost Drift Detection with Baseline Intelligence
Cloudshot understood what "normal" spend looked like and monitored deviations in real time. It flagged unusual activity within 3 days—not 16—well before it became a financial problem. The finance team no longer had to find the fire—it was already being watched.
Usage-to-Cost Mapping Across Teams, Services, and Roles
Cloudshot traced the cost anomaly back to a specific instance, linked it to the project, and tied it to the user who deployed it. Now, DevOps and Finance could work with the same view—no translation needed. Blame was replaced by visibility, and resolution happened fast.
Prevented $18K in future waste through continuous optimization
Two more risky patterns—an overprovisioned staging cluster and a forgotten AI training job—were flagged and resolved. No alerts were missed, no meetings were needed. Savings became systematic, not accidental.
The biggest transformation? They stopped living in fear of their own cloud.
They no longer waited for cost spikes to become line items. They saw cost as a signal—not just a spreadsheet.
"Cloudshot didn't just save us money. It gave Finance and DevOps a shared truth."
— Startup CFO