The wizard is part of the Cost Allocation setup flow. For an overview of the canvas, manual mapping, and toolbar controls, see Cloud Resource Mapping.
Step 1 — Categorize your accounts
The wizard auto-categorizes each cloud account based on its name using keyword matching. Each account is assigned to one of these categories:| Category | Cost Layer | Production? | Example account names |
|---|---|---|---|
| Production | Production (COGS) | Yes | prod-api, workload-us-east, live-services |
| Development | Development (Non-Prod) | No | dev-team-alpha, sandbox-experiments |
| Testing | Testing (Non-Prod) | No | qa-regression, uat-environment |
| Staging | Staging (Non-Prod) | No | staging-v2, pre-prod-us-west |
| Security & Operations | Security & Operations (Non-Prod) | No | audit-logs, security-hub, infra-management |
| Support | Support (Non-Prod) | No | support-services |
| Not Sure | Production (COGS) | Yes (default) | Accounts that don’t match any pattern |
“Not Sure” defaults to Production. This is a deliberate conservative choice — it’s better to over-allocate to COGS (which you’ll refine) than to hide production costs in a non-production bucket.
preprod match Staging (not Production) and devops matches Security & Operations (not Development).
Review before proceeding — the wizard shows a summary of how many accounts fall into each category. Pay special attention to “shared services” or “infrastructure” accounts — these default to Security & Operations but may contain production workloads. Accounts with ambiguous names (numeric IDs, single words) default to Production; renaming those in AWS improves auto-detection accuracy in future runs.
Step 2 — Organize production accounts
This step only appears when 2 or more accounts are categorised as Production (or “Not Sure”). With a single production account, the wizard skips it.
- Core Product — main customer-facing application
- Data Pipeline — ETL, analytics, ML infrastructure
- Internal Tools — admin dashboards, internal APIs
Step 3 — Service cost breakdown
Choose whether to split production accounts by AWS service and auto-group them into service categories. Production service categories (under Production / COGS):| Category | What it covers | Example services |
|---|---|---|
| Compute | Runtimes, containers, workflow engines | EC2, ECS, Lambda, EKS, Fargate |
| Database & Storage | Databases, warehouses, object storage | RDS, S3, DynamoDB, Redshift, ElastiCache |
| Networking & Delivery | Network, CDN, DNS, messaging, APIs | CloudFront, ELB, Route 53, API Gateway, SNS |
| AI & Analytics | ML/AI, BI, data processing, streaming | SageMaker, Bedrock, Kinesis, Glue, MSK |
| Category | What it covers | Example services |
|---|---|---|
| Security & Operations | Monitoring, security, compliance, CI/CD | CloudWatch, GuardDuty, Config, CodeBuild |
| Support | AWS support plans | Business Support, Enterprise Support |
Why do Security & Operations and Support go under Non-Production? Even when these services run in a production account, they represent operational overhead — not direct cost of delivering your product. Keeping them under OpEx produces cleaner COGS metrics and more accurate gross margin calculations.
- Yes, group by service — best for organisations that want visibility into what infrastructure types drive costs. Useful for engineering leaders optimising specific areas.
- No, keep it simple — best if you just need the Production vs. Non-Production split. Sufficient for high-level financial reporting and easier to manage.
What happens when you apply
When you click Apply mapping, the wizard:- Creates service category cost layers (Compute, Database & Storage, etc.) under the selected parent layers
- Creates any production sub-layers you defined in Step 2
- Assigns non-production accounts to their category layer; production accounts go to their sub-layer or the production pool
- Splits production accounts by service (if enabled) and auto-assigns each to its category
- Reports what percentage of services were successfully auto-mapped
Auto-mapping individual nodes
Even after the wizard completes, you can apply service auto-mapping to any assigned leaf node in the Sankey diagram by clicking the tree icon on that node. A preview panel opens showing which service categories will be created, how much spend falls into each, and a breakdown preview before you commit. This is useful for:- Accounts that were mapped manually rather than through the wizard
- Applying service breakdowns to new accounts added after the initial setup
- Refining specific sub-layers with more granular service visibility
Best practices
- Start with Help me map — even if you plan to customise heavily, the wizard creates a solid foundation in minutes
- Review before saving — verify account categorisations match your organisational structure before clicking Save
- Default “Not Sure” to Production — this is intentional; review and reclassify rather than risk missing production costs
- Use sub-layers for multi-product organisations — if you have distinct product lines with independent P&Ls, sub-layers make cost tracking far more useful
- Enable service grouping — the extra visibility into Compute vs. Database vs. Networking costs is valuable for both engineering optimisation and finance reporting
- Iterate — auto-mapping gets you 80–90% of the way; use the Sankey diagram to refine the rest
- Name your accounts well — following AWS Control Tower or Landing Zone naming conventions significantly improves auto-categorisation accuracy
Cloud Resource Mapping
Canvas overview, manual mapping, and toolbar reference.
Cost Layers
Add sub-layers, reassign services, and manage your structure over time.

