Cloud environment cost estimates

How Workbench calculates cost estimates for cloud environments

Prior reading: Overview of Cloud Environments

Purpose: This document provides details on how cloud environment cost estimates are calculated.


Verily Workbench dynamically generates cost estimates for your new and existing cloud environments.

You can find the cost estimates for your existing cloud environments on each environment card:

Screenshot of cloud environment detail card, zoomed in on current cost.
Viewing an existing cloud environment's cost estimate.

To view the cost estimates for a new cloud environment, create a new cloud environment and proceed to the Choose configuration step. You’ll see the cost estimate for the default configuration.

Screenshot of Choose configuration dialog, showing cost estimate breakdown for a default configuration.
Viewing a new cloud environment's cost estimate.

Proceed to the Customize step to configure the environment image type and cloud compute profile. The cost estimate will dynamically change based on the number of CPUs and GPUs selected.

Screencast showing dyanmic cost calculator tool on Customize dialog when creating a cloud environment.
Viewing the dynamic estimated cost of a new cloud environment.

Cost estimations on Google Cloud

Google Cloud cost estimations are internally computed directly from the pricing SKUs listed from the Cloud Billing API. This means that calculated costs reflect the on-demand pricing of cloud resources and does not factor in billing account-specific discounts including committed use discounts and negotiated pricing contracts.

There are several broad cost categories for cloud environments on Google Cloud. These include compute costs, disk costs, network costs, and managed services fees. For detailed information on these costs, see Cost management on Google Cloud.

Workbench cloud environments on Google Cloud are based on Compute Engine instances. Cost estimations depend on the following factors:

  1. Cloud compute profile
  2. Workspace region
  3. Managed service fees

Cloud compute profile

The number of CPUs and GPUs and the amount of memory all incur cost when the cloud environment is running.


For Vertex AI notebooks and custom applications, you can set compute configurations directly in the UI. If you’re creating an environment using the CLI, you can configure the machine type via the
--machine-type option. The machine type determines the number of CPUs and the amount of memory configured for each node. For example, the n2-standard-4 machine type is configured with 4 vCPUs and 16 GB of memory.

Note: To learn more about Compute Engine machine types, see Machine families resource and comparison guide. Cloud environments incur vCPU and memory costs when they are running.

For Dataproc clusters, you can configure the machine type for the master and worker nodes. The machine type determines the number of CPUs and the amount of memory for each node.

If a worker node is configured as a spot instance, then a spot discount is applied.


Persistent disks attached to cloud environments also incur cost based on the disk size and disk type. For more information, see persistent disk pricing. Note that persistent disks incur cost even when the cloud environment is stopped.

By default, Vertex AI and custom application cloud environments are configured with two standard persistent disks: a 100 GB boot disk and a 150 GB data disk.

For Dataproc clusters, persistent disks are attached and provisioned per VM, so two disks are provisioned for the master node and each worker node.

Note that the number of disks, disk type, and disk size can be changed via the CLI.


The workspace default region determines the region-specific pricing of the compute profile and disk costs.

For example, the cost of a Vertex AI cloud environment created in us-west2 can cost almost 20% more than the same notebook created in us-central1.

Screenshot of cost estimate for a cloud environment in the us-central1 region. Screenshot of cost estimate for a cloud environment in the us-west2 region.
Cost estimate for a Vertex AI notebook created in us-central1 (left) versus us-west2 (right).

Managed service fees

Vertex AI and Dataproc cluster cloud environments incur additional managed service fees. Google Cloud adds a fixed cost per CPU core. For more information, see Management in “Cloud cost management.”

Unaccounted costs and discounts


Cost estimates are calculated from the hourly on-demand pricing of individual cloud resource SKUs. Billing account-specific pricing including committed use discounts and negotiated contract pricing is not accounted for. Further, sustained use discounts accrued from running VMs for an extended duration of time are not accounted for. For more information on committed use discounts, see Resource-based committed use discounts. For more information on sustained use discounts, see Sustained use discounts for Compute Engine.

Networking Costs

Cost incurred from user actions such as copying or transferring data across cloud regions are not factored into cost estimations. This includes the estimated hourly and monthly costs displayed during environment creation and the hourly cost displayed on each environment card. See Networking costs for more information on data copying, download, and transfer costs.


You will see an Unknown cost estimate on the environment card if a cloud environment was created using the Workbench CLI with an unsupported configuration for cost estimation. You can submit feedback in this form to request cost estimation support for your cloud environment configuration.

A cloud environment with an unsupported configuration for cost estimation.

Last Modified: 21 May 2024