Finout · 2022 to 2023
Turning cloud cost chaos into one clear picture
A cloud cost management platform that helps FinOps, engineering and finance understand spend from the same source of truth.
- Company
- Focus
- Product design, UX research, visual design
- Design scope
- Core product workflowsCustomer and stakeholder researchProduct marketing and visual assetsEarly design-system foundations and Storybook implementation
Research and framing
The problem was not a lack of data. It was the work required to understand it.
Teams moved between provider dashboards, exports and spreadsheets before they could answer a basic cost question.
I mapped that fragmented workflow and connected it to four recurring needs: visibility, alignment, efficiency and accuracy. That reframed the opportunity from another dashboard into one investigation model: understand the spend, detect meaningful change and establish who owns it.
Fragmented visibility
Manual reconciliation
Investigation was complex and slow
No clear cost ownership
Interactive walkthrough. Best viewed on desktop.
MegaBill
One view across every cloud, service and team
Research showed that teams needed one shared overview, but still had to trace every number back to its source.
That made the path into detail as important as the overview itself. I designed MegaBill as a cross-provider starting point with flexible grouping and a consistent route from total spend to the resource behind a change.
Group cloud spend and drill from the total cost to the resources behind it.
Select a highlighted row to open the next configured dimension.
| Service | Total | Previous period | Change | Percentage |
|---|---|---|---|---|
| AWS Services | $72,800 | $70,200 | ▲ 3.7% | 77% |
| Google Cloud Services | $14,600 | $15,100 | ▼ 3.3% | 15% |
| Kubernetes | $4,700 | $4,300 | ▲ 9.3% | 5% |
| Snowflake | $2,700 | $2,500 | ▲ 8.0% | 3% |
Interactive walkthrough. Best viewed on desktop.
Anomaly Detection
A feed for the cost changes that needed attention
A unified bill improved visibility, but teams still had to actively search for the cost changes that deserved attention.
This led to a chronological anomaly feed rather than another dashboard. I gave every item its expected and actual spend, affected cost context and compact trend, with a direct route into MegaBill for investigation.
Hover over the highlighted areas to unpack the design decisions.
$2,700 ▲ 5.9%
- Expected cost
- $45,400
- Actual cost
- $48,100
Cost centerAWS
Service: AmazonEC2Interactive walkthrough. Best viewed on desktop.
Virtual Tags
Turning untagged cost into accountable spend
The research separated visibility from accountability: seeing a cost did not explain which product, environment or owner was responsible for it.
Incomplete provider metadata made that gap unavoidable. I shaped Virtual Tags as an ordered rule model for matched and unmatched costs, then extended it through Split Cost so shared costs could be distributed without making the allocation harder to understand or validate.
Create virtual tag
Set tag rules
Rules are evaluated from top to bottom.
Set default value
Write down free text or choose from a list.
Interactive walkthrough. Best viewed on desktop.
What changed in practice
One path from fragmented cost data to accountable spend
MegaBill, Anomaly Detection and Virtual Tags shipped as core parts of Finout and remain part of the product today.
FinOps, engineering and finance could begin with the same cross-provider view instead of reconciling separate dashboards and exports.
Anomaly Detection surfaced unexpected spend with its context intact, then opened the relevant MegaBill investigation directly.
Virtual Tags let FinOps teams convert existing metadata into business context and define what should happen when that context was missing.
Reflection
Clarity came from preserving the path through the data
Cloud cost data became useful when people could understand how a number was constructed and who was responsible for it.
Across these workflows, I used progressive disclosure as the organizing principle: begin with one clear picture, preserve context through every level, then turn what people discovered into accountable action.