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Tredence · UX Designer · 2022

Helping finance and engineering agree on cloud spend.

Cloud cost clarity for finance, DevOps, and cloud admins acting on the same spend picture.

3primary user roles
AWS · Azure · GCPmulti-cloud scope
Shippedinternal product

Overview

The same cloud bill meant different things to each team.

I shaped research synthesis, information architecture, dashboards, recommendations, alerting, and handoff for an internal AWS cost product used across finance and engineering contexts.

The problem

Visibility was fragmented before action even began.

The solution

One path from cost signal to owned action.

01

See

Give every role a common spend and trend overview.

02

Explain

Connect anomalies to technical resources and causes.

03

Act

Pair recommendations with risk, evidence, and an owner.

Decision 01

Create one shared operating view.

The overview gave finance and engineering the same starting point before offering role-specific depth.

  • Shared language. Use consistent spend, trend, ownership, and risk definitions.
  • Progressive depth. Move from overview into team, cluster, and resource detail.
  • Context travels. Keep the selected period and ownership visible across views.
Cloud cost dashboard with spend trends and ownership
The home dashboard gave finance and engineering one shared view of spend, trend, and ownership.

Decision 02

Make every recommendation explain itself.

The first version buried recommendations below charts. I moved prioritized actions into the main path and attached the evidence needed to judge safety.

  • Cause before action. Explain what produced the cost change.
  • Confidence stays visible. Show the strength of the evidence.
  • Risk and owner. Make operational consequences and responsibility explicit.
Cloud optimization recommendations with supporting evidence
Recommendations paired cause, confidence, impact, and an explicit action.

Decision 03

Connect the anomaly to the resource.

A cost signal became useful when an engineer could trace it to the cluster or resource that required investigation.

  • Signal to detail. Preserve the route from overview into technical evidence.
  • Operational state. Keep runtime and resource health visible.
  • Action in context. Avoid sending users into a separate reporting tool.
Cloud cluster deep dive with cost and resource evidence
The deep dive connected cost anomalies to the technical resource an engineer could investigate.

Outcome

Teams gained a clearer route from cost risk to action.

The shipped internal product created a shared operating view and made recommendations easier to inspect.

Shared cost context

Finance, DevOps, and cloud admins could work from the same underlying view.

Explainable recommendations

Evidence, confidence, risk, and ownership traveled with the suggested action.

Earlier intervention path

The workflow connected spend change to technical cause while action was still possible.

Evidence boundary: stakeholder interviews, cloud-team shadowing, support feedback, usability testing, and shipment of the internal product support this narrative. No savings, adoption, or business-impact percentage is claimed.

Final product

The shared cloud-cost workflow.

The final product screens are grouped here so the visual walkthrough follows the reasoning and outcome.