Configure Datadog Cloud Cost Management to ingest AWS, Azure, and GCP billing data and allocate costs by tag

Steps

1. Ensure the relevant cloud integration (AWS, Azure, or GCP) is installed in Datadog first, since Cloud Cost Management builds on top of it.
2. For AWS, generate a Cost and Usage Report (CUR) — for manual setup this must be a Legacy CUR export with resource IDs and split cost allocation data enabled — then in Datadog go to Cost > Setup & Configuration (app.datadoghq.com/cost/setup) and configure it via the guided CloudFormation flow, the Terraform flow (datadog_integration_aws_cur_config / equivalent Cloud Cost Management API), or manually by entering Bucket Name, Bucket Region, Export Path Prefix, and Export Name.
3. Attach an IAM policy to the Datadog integration role (default name DatadogIntegrationRole) granting s3:ListBucket / s3:GetObject on the CUR bucket, plus ce:Get*, cur:DescribeReportDefinitions, and organizations:Describe*/List* so Datadog can read and reconcile the report.
4. For Azure and GCP, follow the equivalent per-cloud setup pages under docs.datadoghq.com/cloud_cost_management/setup/ to grant Datadog billing-export read access (Azure Cost Management export to storage, GCP BigQuery billing export).
5. Allocate costs by tag using the automatically ingested tag sources (CUR columns, cloud resource tags, account/organization tags, integration tags, and out-of-the-box tags like aws_product), and layer on Tag Pipelines for resources that cannot be tagged directly in the cloud provider.
6. Verify data completeness in Cost Explorer once ingestion finishes; historical data (up to 15 months) backfills automatically if the CUR/export already has history.