SUD: Server Utilization Dashboard
NDA2022 · AT&T (Chief Data Office)
Companion to ACO: maps AT&T's physical and hybrid server fleet across data centers, environments, and lifecycle.
Same NDA stance as ACO: methodology restricted. The interactive rebuild below reproduces the structure and interaction model as a fictional company, with entirely invented data.
SUD is the physical fleet companion to ACO. Where ACO right sizes Azure spend at the application level, SUD inventories AT&T's 372,995 servers across 32 data centers, 81 cities, and 7 environment types (Network Cloud, AT&T Integrated Cloud, Enterprise Cloud, Dedicated, Shared VMware, Bare Metal, Other Non Cloud). It gives capacity planners, FinOps, and infra VPs a single place to drill from a US map view of data centers all the way down to a single server's lifecycle timeline.
Live demoClick through a working rebuild of the utilisation flow: data centers, environments, clusters and servers, with health and lifecycle at every level. Fictional company, generated data.Open the live demoInteractive prototype
The problem
Before SUD, AT&T had no unified view of its physical and hybrid server fleet. Capacity planners reconciled spreadsheets across data centers, SREs had limited visibility into end of service life hardware, and Chief Data Office leadership had no fleet wide picture across 32 data centers and hundreds of thousands of servers. Deciding where to pre provision or retire capacity meant manual data pulls from disconnected systems.
Information architecture
By Data Center
All Data Centers (US map + sortable list, fleet-wide health summary)
└─ State → Data Center
├─ Overview infrastructure counts · server-age histogram · usage donut
├─ Cluster List → Cluster → Server
└─ Applications
By Environment
All Environment Types (7 types: Network Cloud, AIC, Enterprise Cloud, Dedicated,
Shared VMware, Bare Metal, Other)
└─ Environment Type
├─ Overview active servers · supply vs demand by architecture
├─ Details architecture by lifecycle / EOSL / city / model
├─ Cities capacity vs the raw→allocable→allocated→consumed→utilized funnel
└─ Lifecycle
Server detail (shared leaf of both paths)
Details · Location · Ownership · Dates · Lifecycle Timeline · 8 Applications · Health ScoreProcess & prototyping
- Two parallel entry paths: 'View by Data Center' (location first) and 'View by Environment' (architecture first), both terminating at the same server detail leaf.
- Universal Health Score: every entity level (DC, cluster, server, application) carries the same G/Y/R/N/A pill + 13 month composite trend, weighted CPU 25% · RAM 70% · Storage 5%.
- Map ↔ List toggle on every level with geography.
- 5 step consumption funnel surfaces utilization: raw → allocable → allocated → consumed → utilized (in vCPU).
- Lifecycle Timeline visualizes Design → Build → On Network → Out of Network with milestone date stamps and forward EOSL marker.
- Supply vs demand chart by city flags where AT&T should pre provision (example data: Houston showed demand 10,970 vs supply 9,100 in Sep 2019).
- AIC-SSP (AT&T Integrated Cloud Self-Service Platform) broken out as its own sub-product for region-level consumption tracking.
Outcome & impact
SUD unified 372,995 servers across 32 data centers, 81 cities, and 7 environment types into a single drill down, from a US map all the way to one server's lifecycle and composite health score. It boosted executive decision making efficiency by 30% through real time server health and utilization metrics.
Role & collaboration
Team
Same crew as ACO: about 6 people, 2 frontend engineers (Kshitij plus 1 other; both did UI work), 1 tech lead, 1 scrum master, 2 data engineers running the Oracle to MongoDB ETL pipeline.
My role
- Owned the majority of the frontend implementation.
- 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.