Review Azure Files provisioned capacity and snapshot storage
Compare share-level utilization with snapshot storage in Azure Monitor before reviewing provisioned capacity. Keep account totals out of share-level decisions.
Steps3 min read
Cloud cost guides
Find answers to common questions about cloud and AI costs.
29 guides
Check Blob lifecycle rules before changing access tiers
Check lifecycle rules before moving an individual Azure Block Blob out of Archive, and account for retrieval and early-deletion meters before approval.
Steps3 min read
Separate transfer costs before blaming compute or storage
Review AWS transfer usage types, Azure bandwidth categories, and Google Cloud network tiers before assigning a compute, storage, or network cost cause.
Steps4 min read
Review Blob Storage versions and soft-delete costs
Check whether an existing Azure Blob Inventory report covers retained versions and deleted objects, then compare its scope with Blob Capacity before planning storage changes.
Steps4 min read
Separate AI requests from retries and evaluation work
Review AWS and Azure telemetry to separate application requests, model calls, retries, and evaluation activity before allocating AI spend.
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Measure AI cost per successful business outcome
Compare scoped AI spending with accepted business outcomes using a read-only worksheet that keeps retries, failed attempts and attribution gaps visible.
Steps4 min read
Review Azure Machine Learning capacity floors
Check managed online deployment minimums and training-cluster node floors against workload needs, then use endpoint cost tags to prioritize owner reviews.
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Compare Azure OpenAI token costs with provisioned capacity
Compare Azure OpenAI token charges with hourly PTU capacity costs, including idle hours, model-specific sizing, reservation coverage and unused commitments.
Steps4 min read
Check who can use your Azure commitments
Compare Azure reservation and savings plan scopes with eligible usage before widening access across an EA enrollment or MCA billing profile.
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Choose models by cost per usable answer, not token price
Compare model candidates on shared tasks, quality limits and response times. Use a read-only worksheet to estimate cost per accepted result from evaluation records.
Steps3 min read
Check Cosmos DB hot partitions before reducing throughput
Compare Cosmos DB partition utilization and 429 responses before a throughput cut, then use existing logs to identify keys with concentrated demand.
KQL3 min read
Check Azure Front Door request and transfer costs
Review Standard and Premium profile fees, request counts, and transfer charges separately to identify which costs caching can reduce and which remain.
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Budget AI search and tool usage separately
Separate model tokens, search grounding, and tool-resource measurements so an AI workflow budget does not hide charges behind prompt counts or monitoring data.
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Review Azure inter-region data transfer costs
Separate bandwidth, peering and Front Door charges before estimating Azure cross-region costs. Use a read-only register to match network paths to billed meters.
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Check GPU commitment cost against useful work
Separate reservation use from GPU activity, then compare period cost with accepted workload output before deciding whether to renew capacity.
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Keep shared Azure cost allocation separate from billing
Review shared-service allocation rules, target percentages and cost records so internal chargeback stays separate from Azure invoice reconciliation.
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Find costly Azure Data Factory activity patterns
Compare factory-level Azure Data Factory costs with per-run meter consumption to choose a workload for review without treating duration or usage as the charged price.
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Compare AI prices without mixing token types or capacity
Use a read-only worksheet to compare Azure OpenAI, Amazon Bedrock, and Vertex AI costs, separating token categories, cache charges, and provisioned capacity.
Steps4 min read
Avoid double-counting cloud network charges
Separate repeated imports from valid charges on one traffic path. Reconcile a closed invoice period while keeping credits, corrections, adjustments and distinct service fees visible.
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Check Azure Backup charges before changing retention
Review backup charge types, stopped protection and Archive eligibility before proposing retention changes that could remove needed recovery points.
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Avoid buying cloud commitments from a single busy week
Before approving a cloud commitment, compare historical recommendations with lasting demand and check whether recent purchases have been reflected.
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Review Azure SQL capacity before downsizing
Identify provisioned Azure SQL databases and pools worth a sizing review using workload peaks, storage limits and purchasing-model checks, not low CPU alone.
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Explain a cloud bill increase before changing resources
Use a read-only worksheet to compare monthly cloud costs and separate usage changes from prices, discounts, credits, and invoice adjustments.
Steps4 min read
Keep currencies separate in multi-cloud cost reports
Check cost denominations before combining cloud exports, choose billed or effective cost, and record a conversion policy that keeps totals traceable.
Steps3 min read