Check whether resource-based CUD sharing fits your billing setup
Match Compute Engine resource-based CUD scope to intended project coverage and verify shared reservation projects use the same Cloud Billing account before a move.
Steps3 min read
Cloud cost guides
Find answers to common questions about cloud and AI costs.
28 guides
Review Compute Engine recommendations before resizing VMs
Review VM size suggestions against peak demand, compatibility and restart needs. Learn why estimated savings and empty recommendation lists need care.
BASH3 min read
Match Cloud Run functions to the right pricing model
Classify Cloud Run functions by documented version and console area before comparing costs. Keep pricing-family labels separate from API history and billed-SKU confirmation.
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 BigQuery long-term storage billing
Check BigQuery partition tiers and last-write timestamps before forecasting storage costs. Separate logical and billable bytes without treating metadata as a full bill.
SQL3 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.
Steps3 min read
Check Cloud SQL compute, storage, backup and network charges
Separate Cloud SQL charges from usage charts before choosing a cost change. Review one invoice month and include any separate MySQL enhanced-backup project.
Steps3 min read
Check BigQuery autoscale charges by reservation minute
Review BigQuery autoscale slot-seconds from the last day and compare reservation limits and slot sharing before asking an owner to change capacity.
SQL3 min read
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
Check Cloud Storage protections before counting deletion savings
Review Cloud Storage versioning, soft delete, and locked retention settings before treating deletion as storage savings.
Steps3 min read
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
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.
Steps3 min read
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.
Steps4 min read
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.
Steps4 min read
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.
Steps4 min read
Check discount sharing before comparing project costs
Review Compute Engine discount sharing and fee allocation before treating a lower project cost as lower usage. Include commitment costs outside project totals.
Steps3 min read
Check transfer charges before moving Google Cloud workloads
Review Google Cloud network charges after credits, confirm billing units, and link the largest items to traffic a proposed regional move would actually change.
SQL3 min read
Separate Cloud NAT charges from network transfer costs
Break down Cloud NAT costs by gateway hours, external IP hours, processed GiB, and related services. Use existing logs to explain traffic, not to reconstruct the bill.
Steps3 min read
Separate job trouble from Dataflow cost
Compare Dataflow job estimates with billed costs, then use Dataflow and Managed Service for Apache Spark metrics to assign performance follow-up without mistaking errors for spend.
Steps3 min read
Reduce BigQuery scans without changing the answer
Review one BigQuery SELECT for unnecessary partition scans. Compare dry-run bytes without dropping required rows or treating clustered-table estimates as final costs.
Steps3 min read
Check your BigQuery target before enabling billing export
Review the dataset and project requirements for Cloud Billing export, including location limits, encryption constraints, project links, and available usage-cost history.
Steps3 min read
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