AI + Data + Cloud · Pillar 5
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FinOps & Analytics
Data
99.5%Data Accuracy
FOCUS 1.2+ cost dashboards with CFO/CTO/CloudOps persona modes. Cross-validated at 99.5% accuracy.
⚡ First FOCUS 1.2+ cost report in <3 minutes
AI agents build governed & Humans ship trusted. 80% autonomy & 100% accountability.
Section Five (Ch.24-27)
Embedding Data Everywhere
“In our experience, as much as 70% of the development efforts of an AI-based solution are composed of wrangling and harmonizing data. Many of these issues can be traced back to legacy, siloed systems.”
The core unit for achieving this goal is the data product — a set of data elements that are curated and packaged in such a way that any team or application across the organization can easily consume it. ADLC delivers this through FOCUS 1.2+ compliant FinOps dashboards with persona modes (CFO, CTO, CloudOps Engineer) and cross-validated data products using Config Aggregator and AWS Cost Explorer.
Platform Evolution
AI models improve cost anomaly detection. Vizro dashboards benefit from better natural-language-to-chart generation with each Claude release.
FinOps & Analytics Golden Path
Each phase answers: Who does it, Why it matters, What if you skip it
1Collect
Gather cost data from AWS + Azure with FOCUS 1.2+ normalization
/finops:aws-monthly + /finops:azure-monthlyWho: finops-engineer collects via READONLY profiles, HITL verifies account coverage
Why: Data quality at the source. Portal CSV is SSOT, not API alone — prevents FINOPS_API_SSOT_MISMATCH anti-pattern.
Skip? Incomplete data, RBAC-scoped undercounts, wrong numbers presented to leadership
→ FOCUS 1.2+ cost reports with persona modes (CFO, CTO, CloudOps)
2Validate
4-way cross-validation: CLI vs Config Aggregator vs Cost Explorer vs Console
/inventory:lz-cross-validate + /devtools:validateWho: qa-engineer validates accuracy against independent sources, HITL reviews deltas
Why: 99.5% accuracy gate. SELF_COMPARISON_VALIDATION prevented — must use 2+ independent data sources.
Skip? Bad data in reports, false savings claims to stakeholders, eroded trust in FinOps team
→ Cross-validation report with per-source accuracy deltas
3Analyze
Cost trends, anomaly detection, optimization recommendations
/finops:analyze + /finops:decommission-inventoryWho: finops-engineer analyzes, product-owner validates business alignment of recommendations
Why: Analysis with measured data, not estimates. Every quantitative claim must cite its measurement method — NO_ESTIMATED_COUNTS anti-pattern prevented.
Skip? Estimated numbers in reports, unvalidated savings claims, NO_ESTIMATED_COUNTS violations
→ Trend analysis + decommission candidates with scream-test scores
4Report
Persona-mode reports for CFO, CTO, CloudOps — executive FinOps report
/finops:reportWho: observability-engineer generates reports, HITL distributes to stakeholders
Why: Right data for right audience. CFO needs cost totals, CTO needs trends, CloudOps needs actionable items.
Skip? One-size-fits-all reports, executive disengagement, cost decisions made without data
→ 4 persona reports + stakeholder email + evidence-backed claims
5Optimize
Rightsize, decommission unused resources, track savings attribution
/finops:azure-rightsizing + ec2-scream-test skillWho: finops-engineer proposes with READONLY profiles, HITL approves decommission actions
Why: Evidence-based decommission with scream-test scoring. READONLY profiles are safe by design — AWS IAM prevents mutations.
Skip? Zombie resources persist, savings potential unrealized, cloud spend grows linearly with usage
→ Rightsizing recommendations + decommission actions + savings tracked
Start Here
Spec-Driven workflow and product skills — copy/paste to start
CFO / Finance
You need cloud cost visibility for the board. One command, board-ready output.
1./finops:aws-monthly
2./finops:report
3./finops:azure-monthly
⚡ Board-ready cost report in <3 minutes
CloudOps Engineer
You optimize cloud spend across 67+ accounts daily. Evidence-based decommission.
1./inventory:discover
2./finops:decommission-inventory
3./finops:analyze
⚡ Cost optimization pipeline in 1 hour
FinOps Practitioner
You build data products for cost intelligence. FOCUS 1.2+ compliant from day one.
1./finops:aws-monthly --persona=all
2./devtools:validate
3./metrics:update-dora
⚡ FOCUS 1.2+ data product in 1 day
Component Map
9 components implementing this pillar
| Type | Name | Why | Business Value |
|---|
| Agent | finops-engineer (haiku) | Autonomous cost rightsizing, waste detection, FinOps attribution | Cost down within READONLY guardrails — no human loop for analysis |
| Command | /finops:aws-monthly | FOCUS 1.2+ AWS monthly cost report with persona modes | CFO, CTO, CloudOps persona reports in one command |
| Command | /finops:decommission-inventory | EC2/S3/RDS/VPC decommission signal analysis (E1-E7, S1-S7) | Evidence-based decommission — not gut feel |
| Command | /security:cert-inventory | Multi-cloud certificate inventory with expiry triage | Zero surprise cert expirations in regulated environments |
| Command | /inventory:lz-cross-validate | MCP cross-validation: CLI vs Config Aggregator vs Cost Explorer | 99.5% accuracy gate — SELF_COMPARISON_VALIDATION prevented |
| Command | /metrics:update-dora | DORA metrics pipeline: deployment frequency, MTTR, change failure | Engineering velocity measured, not estimated |
| Skill | finops/org-cost-dashboard | Multi-account cost dashboard with ThreadPoolExecutor parallelism | 67 accounts in 2.67s — not sequential per-account |
| Skill | finops/ec2-scream-test | 5-step decommission feasibility scoring (S1-S5) | Decommission confidence score before any maintenance action |
| Skill | config-aggregator-discovery | Org-wide discovery decision tree — Aggregator before per-account | NARROW_SEARCH_SCOPE anti-pattern structurally prevented |
Risk & Scalability
What happens without this pillar, and why ADLC scales from 1 person to enterprise
What if you skip?
Industry research: as much as 70% of the development effort of an AI-based solution is composed of wrangling and harmonizing data. Without data products, every team reinvents data pipelines. The core unit is the data product — a set of data elements curated and packaged so any team can easily consume it. FinOps dashboards ARE data products for cost intelligence.
Scalability
FOCUS 1.2+ dashboards and persona modes (CFO, CTO, CloudOps) serve different stakeholders from the same data source. Cross-validation at 99.5% accuracy ensures the numbers are trustworthy before they reach decision-makers.
Industry Relevance
ANZ enterprise verticals where this pillar is most critical
FSI
Regulatory cost attribution for ring-fenced banking operations
Energy
Grid operations cost showback across generation, transmission, distribution
Telecom
Network slice cost allocation for 5G MVNO tenants
Aviation
Fleet operations IT cost transparency for airline digital transformation
Digital Products
Real products built and governed by this pillar
Explore Pillar 5 Components
Browse the full component catalog or read the documentation
AI agents build governed & Humans ship trusted.