Savings estimator
See what you could save across Azure, AI, and Fabric
Estimate your annual savings from one slider, then tune it with your AI token spend and Fabric capacity. Every assumption is on the page, and the result is a range you can defend.
Your Azure spend
Your all-in monthly Azure bill, including any AI and Fabric spend. From Azure Cost Management; a round number is fine.
Scales the published 22% average: a mature practice has less of it left to capture, and the estimate says so.
A few subscriptions and tidy tagging, or sprawling multi-team estates with drift. More sprawl means more idle, orphaned, and mis-sized resources to reclaim.
Roughly how much of your bill is IaaS (VMs, disks) versus managed PaaS (App Service, SQL DB, Cosmos). IaaS-heavy estates carry more right-sizing, reservation, and Azure Hybrid Benefit headroom.
Add your AI & LLM spend Batch, caching, model mix, PTUs
Inference spend only. The estimate deliberately excludes vector databases, embeddings, and egress.
Model mixRight-sizing existing PTUs only. Provisioned capacity is a performance purchase, not automatically a savings one.
Adjust the AI assumptions
Default 20%. Microsoft's Batch API discount applies to this slice.
System prompts, RAG preambles, tool definitions. Default 40%.
Add your Fabric capacity SKU right-size, reservations, pause schedules
We map it to the nearest F-SKU at pay-as-you-go rates.
From the Capacity Metrics app. A guess is fine; CloudMonitor measures the real number.
Adjust the Fabric assumptions
Billing todayBelow ~14.3 hours/day, pause/resume beats a reservation.
Unlock your full Savings Pulse Report
The lever-by-lever breakdown, the formula behind each number, an audit of every assumption, and a PDF you can put in front of your CFO. Rendered right here; nothing is emailed to you.
22%
Average year-one savings
< 90d
Payback period for most customers
5–10×
Annual ROI on the platform fee
Published customer results, not calculator output, like Clinic to Cloud's 46% reduction in two weeks and Transport for NSW's 22% data-lake saving.
Methodology
Every rate, sourced and dated.
The estimate applies each lever sequentially inside its pillar so nothing is counted twice, subtracts your AI and Fabric spend from the Azure base before the 22% anchor applies, and shows a conservative-to-optimistic range instead of a single figure. Reservations and pause schedules are treated as mutually exclusive per capacity: reserved hours are use-it-or-lose-it, and the breakeven sits near 14.3 hours a day.
| Assumption | Value | Source | Verified |
|---|---|---|---|
| Azure savings anchor | 22% average year-one savings | CloudMonitor published average year-one savings (the same figure behind every pricing tier) | 2026-07-11 |
| Optimization-stage multipliers | 100% / 70% / 35% of the anchor | CloudMonitor estimate — owner-approved 2026-07-11; scales the published average, not a new claim | 2026-07-11 |
| Estate-complexity multipliers | 85% / 100% / 115% of the anchor (low / moderate / high) | CloudMonitor estimate — owner-approved 2026-07-11; scales the published 22% average around a moderate estate, not a new claim | 2026-07-11 |
| Infrastructure-mix multipliers | 85% all-PaaS → 115% all-IaaS (linear; 100% at a 50/50 split) | CloudMonitor estimate — owner-approved 2026-07-11; IaaS carries more right-sizing, reservation, and Hybrid Benefit headroom than managed PaaS; 50/50 holds the anchor at the published average | 2026-07-11 |
| Model right-sizing headroom | 25% frontier / 15% balanced / 5% mini | CloudMonitor estimate — owner-approved 2026-07-11; based on published inter-tier per-token price spreads | 2026-07-11 |
| Batch API discount | 50% on batchable workload | Microsoft-documented Azure OpenAI Batch API discount (Global-Batch, 24-hour turnaround) | 2026-07-11 |
| Prompt-caching discount | 75% on cached input tokens | Azure OpenAI prompt-caching discount on cached input tokens, blended across current models (per-model range roughly 50–90%) | 2026-07-11 |
| Cache realization factor | 70% of the theoretical cacheable share | CloudMonitor estimate — real cache hit rates undershoot the theoretical cacheable share (1,024-token minimum prefix, limited cache lifetime) | 2026-07-11 |
| Input-token share of AI spend | 40% | Typical input-token share of inference spend given 2:1–4:1 input:output volume and 3–8× output pricing | 2026-07-11 |
| PTU right-sizing headroom | 0% / 30% / 10% of the PTU slice by utilization | Reclaim unallocated PTUs, size to average load with spillover, move non-prod to pay-as-you-go, and buy reservations on the retained base | 2026-07-11 |
| Fabric pay-as-you-go rate | $0.18 per CU-hour | Azure Retail Prices API — Microsoft Fabric pay-as-you-go compute, US regions ($/CU-hour) | 2026-07-11 |
| Fabric 1-year reservation | $938 per CU per year (40.5% below 24/7 pay-as-you-go) | Azure Retail Prices API — Microsoft Fabric 1-year reserved capacity, US regions ($/CU/year) | 2026-07-11 |
| Right-sizing target utilization | 70% | CloudMonitor right-sizing target — leaves headroom for smoothing spikes and the 10-minute overage protection window | 2026-07-11 |
| Non-prod pause schedule | 12 hours × 5 days (64% of non-prod compute saved) | Default pause/resume schedule for non-production capacity: 12 hours × 5 days (savings = 1 − 60/168 ≈ 64%) | 2026-07-11 |
| Global estimate ceiling | 40% of total entered spend | Hard ceiling — the optimistic estimate never exceeds 40% of total entered spend | 2026-07-11 |
| Conservative bound | 60% of the optimistic estimate | Conservative bound shown as 60% of the optimistic estimate — a range, not false precision | 2026-07-11 |
What the estimate does not cover
- AI harness costs (vector databases, embeddings, egress, observability), typically another 40–60% of an AI feature's total cost.
- OneLake storage, capacity overage billing, and Spark autoscale: real levers, deliberately excluded to keep the headline conservative.
- Rate changes: Microsoft reprices these services; each rate above carries the date we last verified it.
Estimates vary with your actual usage. Industry benchmarks, where cited, come from the State of FinOps 2026 Report.
Questions
About this estimate.
Is there a minimum Azure spend to get value from CloudMonitor?
For the cost-optimization side, CloudMonitor is aimed at teams spending more than about $10,000 a month on Azure. That's the point where reservation coverage, right-sizing, and idle-resource savings comfortably outrun the license fee. Below it, the recommendation engine still runs, but the recoverable dollars get thinner. The savings calculator shows where your numbers land. The governance and visibility side helps any size customer: cost allocation and chargeback, budgets and forecasts, anomaly alerts, tagging coverage, and board-ready reporting all deliver value whether you spend $2,000 a month or $2 million.
How does the savings calculator work out its estimate?
The estimate combines three pillars. Your core Azure spend is anchored to the 22% average year-one saving CloudMonitor customers see, scaled down by how optimized you already are. Your Azure OpenAI token spend applies Microsoft-documented levers: Batch API routing, prompt caching, model right-sizing, and provisioned-throughput right-sizing. Your Microsoft Fabric capacity uses current Azure prices for pay-as-you-go compute, one-year reservations, SKU right-sizing, and pause schedules. Every rate appears in the methodology section with its source and the date we last verified it, and the result is always a range.
Do I have to enter my details to see a savings number?
No. The headline savings range, the pillar breakdown, and the license comparison are free to use with no form. Your work email and company name unlock the full report: the lever-by-lever breakdown with the formula behind each number, an audit of every assumption you kept or changed, and a PDF you can share internally.
How accurate is the savings estimate?
It's an estimate built from your inputs and published rates, not from your billing data, so treat it as a range, not a promise. Mature FinOps teams see smaller numbers by design, because less of the average saving is still on the table. For a real figure, join the beta: CloudMonitor reads your billing export in place, no second copy, and replaces every assumption with your actual usage.
Does the estimate cover AI and Microsoft Fabric costs?
Yes — those are the two costs most savings calculators skip. The AI section models Azure OpenAI token spend (batch routing, caching, model mix, provisioned throughput) and the Fabric section models capacity cost (SKU right-sizing, reservations, pause schedules). It deliberately excludes AI harness costs such as vector databases, embeddings, and egress (typically another 40–60% of an AI feature's cost) and OneLake storage; the exclusions are listed alongside the methodology.
Get your real number.
CloudMonitor reads your billing export in place, no second copy, and replaces every estimate on this page with your actual usage.
