For Databricks non-serverless compute, total cost of ownership (TCO) information is fragmented between cloud cost reports (e.g., AWS CUR, Azure Cost Mgmt) & Databricks system tables (richer granularity & metadata). While many users are becoming increasingly familiar with Databricks system tables, joining with Azure & AWS cost reports can be cumbersome.
This solution helps automate and simplify this process - with it, users can report on the total infra (VM, networking, storage) and Databricks costs (DBUs) of their classic compute, in unified dashboards.
The FOCUS v1.3 query in focus/ is listed on the FinOps Foundation site as a FOCUS v1.3 data generator.
These three pieces can be used independently or in combination:
- Azure — unifies Azure Cost Management exports (Actuals, Amortized, FOCUS) with Databricks system tables.
- AWS — unifies AWS CUR with Databricks system tables.
- FOCUS v1.3 — vendor-neutral FinOps Open Cost and Usage Specification output from Databricks system tables. Recommended if you want a single, standardized schema across cloud providers.
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© 2025 Databricks, Inc. All rights reserved. The source in this notebook is provided subject to the Databricks License [https://databricks.com/db-license-source]. All included or referenced third party libraries are subject to the licenses set forth below.
| library | description | license | source |
|---|---|---|---|
| HashiCorp Terraform | Infrastructure as code tool | BUSL 1.1 | https://github.com/hashicorp/terraform |
| hashicorp/azurerm Terraform provider | Azure Resource Manager provider for Terraform | MPL 2.0 | https://github.com/hashicorp/terraform-provider-azurerm |
| databricks/databricks Terraform provider | Databricks provider for Terraform | Apache 2.0 | https://github.com/databricks/terraform-provider-databricks |
| Apache Spark (PySpark) | Distributed data processing engine (runtime dependency) | Apache 2.0 | https://github.com/apache/spark |