e2e-fabric-cost-estimation

Estimates Microsoft Fabric capacity costs and recommends SKU sizing for workload migrations.

Updated Aug 19, 2026
One-click install
npx skills add https://github.com/paulasilvatech/Fabric-Agentic-SDLC --skill e2e-fabric-cost-estimation-paulasilvatech
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: e2e-fabric-cost-estimation
Source: https://github.com/paulasilvatech/Fabric-Agentic-SDLC/tree/main/.github/skills/e2e-fabric-cost-estimation
Command: npx skills add https://github.com/paulasilvatech/Fabric-Agentic-SDLC --skill e2e-fabric-cost-estimation-paulasilvatech

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Migrating workloads like Spark, SQL, Power BI, and Real-Time Intelligence to Microsoft Fabric makes cost forecasting difficult because pricing is region-specific, meter-based, and split across compute, storage, and network dimensions. This Skill produces live, API-grounded cost estimates and SKU recommendations instead of stale hardcoded figures. ## Core Features & Use Cases - Live Pricing Retrieval: Fetches current per-CU-hour PAYG rates, Reserved Instance term totals, and Autoscale Spark rates from the Azure Retail Prices API before quoting any dollar figure. - Workload-to-CU Mapping: Converts Databricks clusters, Synapse pools, Power BI P-SKUs, and multi-cloud sources (AWS, GCP, Snowflake) into Fabric Capacity Unit demand with documented conversion heuristics. - Billing Mode Strategy: Computes Reserved vs. Pay-As-You-Go vs. Autoscale break-even points and builds a complete migration cost worksheet including storage and egress. - Use Case: A team migrating from Databricks and Synapse asks for a Fabric cost estimate; the Skill detects the target region, profiles current spend via the Cost Management API, maps workloads to CU demand, and outputs a monthly cost breakdown comparing F-SKU tiers. ## Quick Start Ask the assistant to estimate the monthly Microsoft Fabric cost for migrating your Databricks and Power BI workloads, specifying your Azure region and current cluster or SKU configuration.

Frequently Asked Questions about e2e-fabric-cost-estimation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I estimate Microsoft Fabric costs before a migration?▼

Profile your source workloads (cluster hours, DWU-hours, P-SKU utilization), map them to Fabric Capacity Units, then fetch live per-CU rates from the Azure Retail Prices API for your region. The Skill aggregates concurrent CU demand, applies a safety factor, and produces a monthly cost breakdown.

How to choose between Fabric Reserved Instance and Pay-As-You-Go?▼

Compute the break-even point from live pricing: divide the amortized monthly reservation cost by the SKU's PAYG hourly cost. If your expected billed hours per month exceed that break-even figure, the Reserved Instance wins; otherwise use PAYG or pause/resume for intermittent workloads.

What is Autoscale Billing for Spark in Microsoft Fabric?▼

Autoscale Billing for Spark is an opt-in serverless model where Spark jobs are offloaded from the capacity and billed per Spark CU-hour on a separate meter. Bursting and smoothing are disabled for Spark, and the autoscale rate is a distinct price that must be fetched separately from the base PAYG rate.

How do Databricks clusters map to Fabric capacity units?▼

The documented conversion is 1 Fabric CU equals 2 Spark vCores, so a node's CU equivalent is its vCores divided by 2. These Databricks mappings are unvalidated heuristics, so always confirm sizing with a pilot workload before committing to a capacity SKU.

Why must pricing be fetched live instead of using known rates?▼

Fabric pricing is region-specific and changes over time, so hardcoded rates go stale and produce wrong estimates. The Skill mandates calling the Azure Retail Prices API before presenting any dollar figure and surfaces an error rather than falling back to memorized rates.

Can I estimate Fabric costs when migrating from AWS or Snowflake?▼

Yes, but source-side costs must also be live: use the AWS Price List API or Cost Explorer, GCP Cloud Billing Catalog, or Snowflake metering history tables. Where no public price API exists, use the official pricing page or invoice and state the source and date.