It's 4pm Friday. Your CFO just pinged you.
AWS bill spiked $47K. You have until 6pm to explain it. That's 120 minutes to correlate spend across 5 dashboards and find the culprit.
The Situation
You're the platform engineer on call. Your CFO sends a Slack message: "Why is AWS up $47K this month?" Panic. You don't have a quick answer.
You open 5 dashboards. Cost Explorer shows the spike started Thursday night. You check CloudTrail. Hundreds of logs. You cross-reference tags across AWS accounts — but your tag taxonomy is broken, and it's been updated three different ways.
By 5:50pm, you send: "Pretty sure it's ECS but I'm not 100% confident." That's not an answer your CFO wants at 6pm Friday.
The Company
Series B SaaS growing 3x YoY. Your infrastructure matches: 7 AWS accounts, multiple teams deploying independently, tags that made sense last year but don't now.
Every person with AWS access has "tried" something different. No central cost taxonomy. Finance and Engineering don't talk until the bill arrives.
With Escher
You ask: "Why did our AWS bill spike $47K this week?"
- 0-1 min: Escher connects to all 7 AWS accounts, pulls 30 days of cost and usage data, correlates to CloudTrail and resource tags.
- 1-2 min: Identifies ECS task count tripled Thursday 11:47pm. Correlates to 50 new c5.2xlarge instances.
- 2-3 min: Finds the GitHub commit that triggered the deployment, identifies the responsible team, and surfaces the Terraform plan that changed the desired task count.
- By 4:04pm: You send: "ECS task count tripled due to commit abc123. Revert plan ready. Saves $9,400/month if reverted." With the exact commit, the exact timestamp, and the exact cost impact.
product screenshot · replace with actual
The Outcome
Before
2 hours
of digging
With Escher
4 minutes
exact answer
Ready to see Escher in action?
Get real answers to your cloud questions in minutes.
Get started free