Day 14 : Understanding Multi-Cloud Billing - What Every FinOps Team Must Know

#ibbus #100daysoffinops #cloudbilling #finopssi

AWS Cost and Usage Reports (CUR) provide the most detailed billing data in AWS.

AWS CUR can reach terabytes due to highly granular, per-resource usage data.

Because CUR captures every resource, every usage type, every hour, and often for multiple linked accounts, the dataset becomes extremely large.

For organizations with heavy workloads (multi-account, enterprise scale), the CUR files can easily grow to hundreds of gigabytes or even terabytes per month.

Azure Cost Management + Billing exports usage data into storage accounts or Log Analytics.

Unlike AWS CUR or GCP BigQuery export, Azure’s level of detail is not uniform across all services.

Azure Cost Management exports vary by service, as each resource reports usage at different granularity levels.

Some Azure services export very granular usage records, while others provide only summarised or daily cost data.

Google Cloud exports billing data directly into BigQuery, making it immediately queryable.

Each service—like Compute Engine, BigQuery, Cloud Storage, etc.—logs detailed consumption metrics.

GCP billing exports stream into BigQuery with thousands of detailed line items for every SKU.

Because GCP logs each SKU’s usage as a separate entry, a billing period can include thousands to millions of rows depending on the project size.

Cloud providers reduce your bill through Reservations, Savings Plans, Credits, Commitments, and Discounts, and applying those reductions correctly to each usage line.

AWS → RI, Savings Plans, EDP credits
Azure → Reservations, Savings Plans, EA
GCP → CUDs, Sustained Use Discounts, Credits

Enterprise Discount Program credits (EDU)
Committed Use Discounts (CUD)
Sustained Use Discounts (SUD)

Cloud costs are usually tracked using tags or labels (like project, team, environment).

When tags are missing, incorrect, or not enforced, a big portion of the spend cannot be mapped to any owner.

AWS → Tags
Azure → Tags
GCP → Labels

Data Timeliness refers to how quickly cloud billing and usage data becomes available after the resources are used.

It affects:

Cost monitoring
Forecasting
Anomaly detection
Budget alerts

AWS usage and cost data can be delayed by 24+ hours.

Azure may take 48–72 hours to finalize.

The standard or detailed usage cost export to BigQuery does not guarantee real-time updates usage and cost data from GCP services are reported at varying intervals.

AWS: 24 hours
Azure: 48–72 hours
GCP: 24 hours

Some billing items like credits, discounts, enterprise agreements, or commitments can take weeks to show up.

Hidden costs in cloud computing are expenses that don’t appear obvious during planning but show up later in your bill.