ACO: AT&T Cloud Optimizer
NDA2021 · AT&T (Chief Data Office)
Internal tool that helps AT&T org leaders see, attribute, and right size their Azure cloud spend.
Built under NDA for AT&T's Chief Data Office, so methodology, research, and iteration details are restricted. The interactive rebuild below reproduces the information architecture and interaction model as a fictional company, with entirely invented data.
ACO is an enterprise Azure cost optimization dashboard built for AT&T's Chief Data Office. It models the org as a 4 level hierarchy (Organizations → Teams → Applications → Resources) so VPs and app owners can drill from a top line cost number to the exact VM/VMSS that's over provisioned.
Live demoClick through a working rebuild of the cost-attribution flow: organisation, team, application, resource, with spend rolling up at every level. Fictional company, generated data.Open the live demoInteractive prototype
The problem
Before ACO, the Chief Data Office had no single, attributable view of Azure spend across the enterprise. Cloud cost was spread over hundreds of applications and dozens of org units, so VPs couldn't see what their teams were spending, app owners had no accountability for over provisioned resources, and right sizing was a manual, one off analysis. Finance could see the total bill but had no model to allocate or reduce it.
Information architecture
All Organizations (executive cards)
└─ Organization
├─ Overview apps · spend · resources · VM/VMSS split
├─ Teams per team lead: 13-month cost trend + savings opportunity
└─ Applications table: app · MOTS ID · type · owner · in-year cost · savings
└─ Application
├─ Overview
└─ Subscriptions
└─ Resource
├─ Details SKU · CPU / RAM / IOPS / Throughput
├─ Recommendations alternative SKUs ranked by savings
├─ Risk Level conservative ↔ aggressive
└─ Metrics allocation vs utilization over time
A parallel Organization Tree mirrors the reporting hierarchy (SVP → VP → team lead → app group → application), searchable by person or MOTS ID.Process & prototyping
- Consistent IA across every entity level: top-line KPI strip + 13-month cost-trend sparkline + savings-opportunity callout.
- Action badges (red / yellow / N/A) surface recommendation counts at every row in the apps table.
- Recommendation engine ranks alternative Azure SKUs by projected savings, with a tooltip explaining the 30-day-percentile basis.
- Organization Tree view (search by user or MOTS ID) supports hierarchical drilldown by SVP → VP → Team Leader → App Group Leader → Application.
- Per-resource detail page exposes a Risk Level slider (High ↔ Low) that biases recommendations toward conservative vs aggressive right-sizing.
Outcome & impact
ACO gave every level of the org a drill down from a top line cost number to the specific over provisioned VM, with ranked right sizing recommendations and a risk dial to balance savings against stability. The platform contributed to an 18% enterprise wide cloud cost reduction at AT&T.
Role & collaboration
Team
About 6 people, same team across both ACO and SUD: 2 frontend engineers (Kshitij plus 1 other; both also did UI design work), 1 tech lead, 1 scrum master, 2 data engineers handling the Oracle to MongoDB ETL pipeline. Kshitij wasn't titled 'lead' but in practice he led the backend, DevOps, and cloud work.
My role
- Owned the majority of the frontend implementation (the other FE contributed UI work too).
- Took over the backend in Node.js with Apollo GraphQL.
- Owned DevOps + Kubernetes, including the Azure Key Vault → K8s secrets integration.
- Owned the entire cloud deployment pipeline.
- Co-designed the UI alongside the other frontend engineer.