| Stage | Microsoft Fabric | Azure ML / Foundry | Compute / Infra |
|---|---|---|---|
|
1. Data Storage
Clinical notes & structured data
|
Fabric Lakehouse / ADLS Gen2 Notes as files or Delta table rows. Structured data (MRNs, codes) in Warehouse. |
— |
No GPU Fabric F-SKU capacity (existing). West US 3. |
|
2. Cohort Query
Filter patients by coded criteria
|
Fabric Warehouse SQL endpoint Filter by dept, date range, procedure codes. Returns MRN list. |
— |
No GPU CPU-only Fabric compute. |
|
3. Training Data Prep
Format labeled examples for fine-tuning
|
Fabric Spark Notebook Extract notes + gold-standard labels. Format as JSONL (OpenAI chat format). Export to Blob. |
Foundry Upload JSONL to Data + Indexes |
No GPU Fabric Spark cluster (CPU). Egress ~$0.08/GB West US 3 → East US 2. |
|
4. Fine-tuning Job
Supervised fine-tuning on clinical data
|
— |
Foundry Azure ML Fine-tuning Job QLoRA SFT on 100–500 labeled examples per task. One-time or quarterly refresh. Training type: Regional (PHI). |
GPU Required Standard NDAMSv4_A100 (4× A100 80GB). $32/hr. Duration: 2–4 hrs/run. Spot option: ~$6/hr. |
|
5. Model Storage
Fine-tuned checkpoint saved
|
— |
Foundry Azure Blob Storage (East US 2) ~20 GB adapter weights + base model reference. |
Storage ~$0.40/month. Azure Blob LRS East US 2. |
|
6. Inference Endpoint
Deploy fine-tuned model as REST API
|
— |
Foundry Managed Online Endpoint Scale-to-zero when idle. OpenAI-compatible API. Private VNet for PHI. Regional deployment (East US 2). |
GPU Required Standard NCADSA100v4 (1× A100 80GB). $3.67/hr active. $0/hr idle (scale-to-zero). ~2–5 min cold start. |
|
7. Batch Inference
Process notes at scale
|
Fabric Spark Notebook Loop MRN list, retrieve notes, call endpoint, collect structured JSON responses. |
Foundry Fine-tuned Qwen3-32B API |
No Extra Cost Fabric Spark (CPU). Network egress negligible (<$1/run at ~500MB). |
|
8. Results & Reporting
Store outputs, serve dashboards
|
Fabric Lakehouse → Power BI Write extraction results to Delta table. QI dashboard (NICCU CVC). Research exports for retrospective projects. |
— |
No GPU Power BI Premium / Fabric capacity. Existing licensing. |
| Component | Resource | When Active | Unit Cost | Monthly Estimate |
|---|---|---|---|---|
| Fabric platform | Existing F-SKU capacity | Always | Existing license | $0 incremental |
| Inference endpoint | NCADSA100v4 (1× A100 80GB) | Business hours only (~10 hrs/day, weekdays) | $3.67/hr | ~$550 |
| Fine-tuning job | NDAMSv4_A100 (4× A100 80GB) | Once/quarter (~3 hrs/run) | $32/hr (or $6/hr spot) | ~$96 (or ~$18 spot) |
| Model storage | Azure Blob LRS East US 2 | Always | $0.018/GB/month | ~$0.40 |
| Training data storage | Azure Blob (JSONL files ~1 GB) | Always | $0.018/GB/month | ~$0.02 |
| Cross-region data transfer | West US 3 → East US 2 egress | Per batch run (~500 MB) | $0.08/GB | <$1 |
| GPT-4o (Xray project) | Serverless — pay per token | On demand | ~$5/1M tokens | ~$10–50 (volume dep.) |
| Total estimated monthly cost | ~$560–660 / month | |||