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Administration & Architecture
Explore discussions on Databricks administration, deployment strategies, and architectural best practices. Connect with administrators and architects to optimize your Databricks environment for performance, scalability, and security.
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Need the cost explorer

littlewat
New Contributor II

We would like each workspace admin to be able to easily check the cost of their own workspace for free.

Currently, we have a Usage dashboard, but it shows account-level costs and requires a SQL Warehouse to view. This means that additional costs are incurred just to check the costs, which is not ideal.

On the other hand, AWS Cost Explorer allows us to view costs easily and for free.

Could you consider providing a similar feature in Databricks, like AWS Cost Explorer, that allows workspace admins to easily and freely monitor their workspace costs?

2 REPLIES 2

Raman_Unifeye
Contributor III

@littlewat - Unfortunately, there is no Warehouse level 'Absolute' Free cost explorer.

Nearest to this - you could build Dashboard queriying system.billing.usage & system.access.audit tables which can be accessed by workspace admin.

Suggest to raise a Feture request to Databricks!!

 


RG #Driving Business Outcomes with Data Intelligence

nayan_wylde
Esteemed Contributor

Databricks currently does not provide a free, workspace‑level cost viewer—all usage/cost dashboards are account‑level and require a SQL Warehouse, which does create cost.
So your request is valid and aligns with what many customers want.


Here are few options you can try:

Option 1 — Use AWS Cost Explorer with Workspace Tags (Best free solution)
If your Databricks workspace has a workspace tag (e.g., WorkspaceName, Environment, Owner), then AWS Cost Explorer can break down costs per workspace successfully.
--Free
--No SQL warehouse
--Workspace admins only see their workspace if IAM permissions are scoped


Option 2 — Use the Databricks Billable Usage API directly (No SQL warehouse)

https://docs.databricks.com/api/account/billableusage/download

You can run this on a jobs compute with a tiny cluster → cost is extremely low, and you avoid the SQL Warehouse.

Option 3 — Use System Tables (if enabled)

Solution that @Raman_Unifeye provided above.