Workload Setup & Estimates
Role: Product Owner Location: Spaces → Add Workload wizard
Before your AI workload's spend appears in your Spaces dashboard or in weekly Spend Cards, you need to register it as an AI workload and claim the IAM role your application uses to call Bedrock. This connects your application's CUR spend to your budget in the FinOps Center hierarchy.
Prerequisites
Before you can complete workload setup, the following must already be true:
The model your workload uses must be Approved and Implemented by the FinOps Lead and Cloud Engineer for the account and region your workload runs in.
You must have the IAM role ARN that your application assumes when calling Bedrock. This is provided in the Developer Handoff block from the Cloud Engineer.
Your workload must be registered in Spaces at the Product (E4) level. If it is not, create the workload in Spaces first before adding AI configuration.
Adding an AI Workload
Open Spaces and navigate to your Product.
Click Add Workload.
In the workload type selector, choose AI Workload.
Complete the Business Request fields:
Use Case Type — Select the category that best describes what the workload does (e.g., customer-facing chat, internal tooling, document processing, code generation).
Workload Type — Select the underlying infrastructure type (Lambda, ECS, EC2, or other).
Details — Free-text description of what the workload does and why it needs this model. This is stored on the Business Request record.
Select your Availability Requirement:
Standard — Single-region inference, standard pricing.
Production / High Availability — Cross-region inference profile, approximately 10% pricing premium. Choose this if your workload requires high availability or low-latency fallback across regions. This is a business decision about your SLA requirements, not a technical one.
Click Submit Request.
The Business Request goes to the FinOps Lead for review and configuration. You will be notified when the request is approved and the IAM configuration is ready to claim.
If the model is not available in the dropdown: The model has not been Implemented for your workload's account and region. Contact your FinOps Lead to check the approval status and ask your Cloud Engineer to complete the enablement task.
Claiming the IAM Role
After your Business Request is approved and the Cloud Engineer marks the task Implemented, the workload appears in your Spaces dashboard with a Claim Role prompt.
Open the workload in Spaces.
Click Claim Role.
Enter the IAM role ARN provided in the Developer Handoff block. This is the role your application assumes when calling
bedrock:InvokeModel.Click Confirm Claim.
Once claimed, every Bedrock API call that role makes will be attributed to this workload in CUR via line_item_iam_principal. This is what connects your application's spend to your budget in the FinOps Center hierarchy.
Note on shared accounts: If your workload runs in an account that is shared with other budgets, claiming the IAM role causes that role's spend to exit the shared cost pool and flow 100% to your workload. This is the intended behavior — it replaces averaged approximations with accurate attribution. Release the claim only if the workload is decommissioned or the role changes.
Setting Token Estimates
After claiming the role, set a token estimate for the period. This estimate is what your weekly Spend Cards will measure actuals against.
Open the workload in Spaces.
Click Set Estimate.
Choose your input method:
Token volume — Enter expected input tokens, output tokens, and cache-read tokens separately per period.
Dollar budget — Enter a dollar amount. FinOps Center back-calculates the token equivalent using current Bedrock pricing for the approved model and region.
Select the estimate period (weekly, monthly).
Click Save Estimate.
Estimates can be updated mid-period. Each change creates an audit record. If you revise an estimate, the Spend Card for the current period will show both the original and revised estimate.
Prompt caching: If your workload uses prompt caching, enter cache-read tokens separately from input tokens. Cache-read tokens are billed at a lower rate than input tokens — combining them will overstate your expected cost.
Allocation Mode
Each AI workload can be set to one of two allocation modes:
BI-only — Spend is visible in your Spaces dashboard and in Spend Cards, but does not move budget. Use this during initial rollout or for workloads where chargeback is not yet agreed.
Chargeback — Spend is debited against your workload's allocated budget. Use this once the estimate is confirmed and the chargeback model is agreed with Finance.
To change the allocation mode, open the workload in Spaces and click Edit Allocation Mode. The FinOps Lead must confirm chargeback mode changes.
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