Explore the Azure Pricing Calculator: estimating costs before you deploy
Slide deck explaining how to use the Azure Pricing Calculator to estimate costs before deployment: adding services, configuring inputs (region, tier, SKU, size), setting usage assumptions, and understanding why estimates differ from actual invoices.
Explore the Azure Pricing Calculator: estimating costs before you deploy
Introduction to the Azure Pricing Calculator: a tool for estimating Azure costs before deployment based on service configuration and usage assumptions.
Explore the Azure Pricing Calculator: estimating costs before you deploy
Introduction to the Azure Pricing Calculator: a tool for estimating Azure costs before deployment based on service configuration and usage assumptions.
Azure Pricing Calculator (what it is)
Use it to estimate costs before deployment, based on your inputs. Web-based cost estimation tool (pre-deployment). You add services plus configure assumptions. Great for budgeting and comparing designs. Not an exact invoice or guaranteed quote.
An estimate equals services plus configuration plus usage
The total changes when you change region, size, or monthly usage. Add services (e.g., Virtual Machine (VM), Storage, Database). Set configuration inputs per service. Set monthly usage (hours, GB, operations, throughput). Total updates as you tweak inputs.
Region affects price
Pick the real deployment region to avoid misleading totals. Region equals where the resource runs in Azure. Prices can vary between regions. Don't leave region on a default 'just because'. When comparing: change only region, keep the rest fixed.
Tier / SKU / size equals performance level
Higher performance usually means higher cost. Tier / Stock Keeping Unit (SKU) / size controls capability. VM size impacts CPU and memory assumptions. Storage/database tiers affect performance and features. Use comparisons to find a good fit.
Usage inputs drive the total
Defaults may assume maximum usage, like 24/7 VM runtime. Set hours per month for Virtual Machine (VM) runtime. Set storage size in gigabytes (GB) realistically. Include operations/throughput where relevant. If totals look odd: check usage assumptions first.
Model the full solution, not just the headline service
Compute, storage, and networking are often separate cost components. Compute: service runtime (e.g., VM hours). Storage: disks, backups, database storage. Networking: outbound data transfer (data leaving Azure). 'VM line item' often doesn't include everything.
Clean comparisons: one change per test
Isolate the cause by changing only one input at a time. Keep most inputs constant. Change one lever: region OR size OR usage. Record results per scenario. Easier to explain 'what caused the difference.'
Why estimates and invoices don't match
Estimates use assumptions; actual spend uses real usage. Estimate (before deployment) equals assumptions plus configuration. Actual spend (after deployment) equals real usage plus real meters. Common drifts: hours, traffic, storage growth, config changes. Use Cost Analysis (Azure Cost Management) after deployment.
Pitfalls to avoid
Most bad estimates come from defaults, missing components, or wrong expectations. Don't expect an exact invoice from the calculator. Adjust defaults (especially monthly usage). Include supporting costs: compute, storage, networking. Compare pricing options (pay-as-you-go vs reservations/savings plans).