Locations

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Google Cloud uses regions, subdivided into zones, to define the geographic location of physical computing resources. Google stores and processes your data only in the region you specify for all features of Vertex AI except for data labeling tasks and any feature in experimental or preview launch status.

Choosing your location

You can choose any supported location when you create a dataset, train a custom-trained model that does not use a managed dataset, or when you import an existing model. You should typically use the region closest to your physical location or the physical location of your intended users, but check that the Vertex AI feature you want to use is supported in your region. There is no global location.

For operations other than creating a dataset or importing a model, you must use the location of the resources you are operating on. For example, when you create a training pipeline that uses a managed dataset, you must use the region where the dataset is located.

Specifying the location using Google Cloud console

When you use Google Cloud console, you specify the location by using the location dropdown menu:

locations dropdown menu

Specifying the location using the Vertex AI API

You specify the location for a Vertex AI API request by using the appropriate regional endpoint.

For example, to make a request in the europe-west4 region, use the following endpoint:

https://europe-west4-aiplatform.googleapis.com

To make a request in the us-central1 region, use the following endpoint:

https://us-central1-aiplatform.googleapis.com

When you specify a resource, you use the name of the resource's region as the location. For example, a dataset in the us-central1 region would be specified using the following path:

projects/PROJECT/locations/us-central1/datasets/DATASET_ID

See the list of supported service endpoints.

Available locations

Vertex AI regions

Vertex AI is available in the following regions. See also Vertex AI Workbench locations.

Americas

  • Oregon (us-west1)
  • Los Angeles (us-west2)
  • Salt Lake City (us-west3)
  • Las Vegas (us-west4)
  • Iowa (us-central1)
  • South Carolina (us-east1)
  • N. Virginia (us-east4)
  • Dallas (us-south1)
  • Montréal (northamerica-northeast1)
  • Toronto (northamerica-northeast2)
  • São Paulo (southamerica-east1)

Europe

  • London (europe-west2)
  • Belgium (europe-west1)
  • Netherlands (europe-west4)
  • Zurich (europe-west6)
  • Frankfurt (europe-west3)
  • Warsaw (europe-central2)
  • Paris (europe-west9)

Asia Pacific

  • Mumbai (asia-south1)
  • Singapore (asia-southeast1)
  • Jakarta (asia-southeast2)
  • Hong Kong (asia-east2)
  • Taiwan (asia-east1)
  • Tokyo (asia-northeast1)
  • Sydney (australia-southeast1)
  • Seoul (asia-northeast3)

Middle East

  • Tel Aviv (me-west1)

Google Cloud also provides additional regions for products other than Vertex AI.

Feature availability

Some Vertex AI features are not available in all regions. The following table lists the features that are available in each region.

Americas

Region Oregon
us-west1		 Los Angeles
us-west2		 Salt Lake City
us-west3		 Las Vegas
us-west4		 Iowa
us-central1		 South Carolina
us-east1		 N. Virginia
us-east4		 Dallas
us-south1		 Montréal
northamerica-northeast1		 Toronto
northamerica-northeast2		 São Paulo
southamerica-east1
AutoML for image data (training, online predictions, and batch predictions)
AutoML for tabular data, classification and regression objectives (training, online and batch predictions, and explanations)
AutoML for tabular data, forecasting objective (training, online and batch predictions, and explanations)
AutoML for text data (training, online predictions, and batch predictions)
AutoML for video data (training and batch predictions)
Custom model training
Interactive shell for custom training
Custom model online predictions and explanations
Custom model batch predictions and explanations
Data Labeling
Vertex AI Vizier
Vertex AI Pipelines
Vertex ML Metadata
Vertex AI Experiments
Vertex AI Feature Store
Vertex AI Model Monitoring
Vertex AI Matching Engine
Vertex AI TensorBoard

Europe

Region London
europe-west2		 Belgium
europe-west1		 Netherlands
europe-west4		 Zurich
europe-west6		 Frankfurt
europe-west3		 Warsaw
europe-central2		 Paris
europe-west9
AutoML for image data (training, online predictions, and batch predictions)
AutoML for tabular data, classification and regression objectives (training, online and batch predictions, and explanations)
AutoML for tabular data, forecasting objective (training, online and batch predictions, and explanations)
AutoML for text data (training, online predictions, and batch predictions)
AutoML for video data (training and batch predictions)
Custom model training
Interactive shell for custom training
Custom model online predictions and explanations
Custom model batch predictions and explanations
Data Labeling
Vertex AI Vizier
Vertex AI Pipelines
Vertex ML Metadata
Vertex AI Experiments
Vertex AI Feature Store
Vertex AI Model Monitoring
Vertex AI Matching Engine
Vertex AI TensorBoard

Asia Pacific

Region Mumbai
asia-south1		 Singapore
asia-southeast1		 Jakarta
asia-southeast2		 Hong Kong
asia-east2		 Taiwan
asia-east1		 Tokyo
asia-northeast1		 Sydney
australia-southeast1		 Seoul
asia-northeast3
AutoML for image data (training, online predictions, and batch predictions)
AutoML for tabular data, classification and regression objectives (training, online and batch predictions, and explanations)
AutoML for tabular data, forecasting objective (training, online and batch predictions, and explanations)
AutoML for text data (training, online predictions, and batch predictions)
AutoML for video data (training and batch predictions)
Custom model training
Interactive shell for custom training
Custom model online predictions and explanations
Custom model batch predictions and explanations
Data Labeling
Vertex AI Vizier
Vertex AI Pipelines
Vertex ML Metadata
Vertex AI Experiments
Vertex AI Feature Store
Vertex AI Model Monitoring
Vertex AI Matching Engine
Vertex AI TensorBoard

Middle East

Region Tel Aviv
me-west1
AutoML for image data (training, online predictions, and batch predictions)
AutoML for tabular data, classification and regression objectives (training, online and batch predictions, and explanations)
AutoML for tabular data, forecasting objective (training, online and batch predictions, and explanations)
AutoML for text data (training, online predictions, and batch predictions)
AutoML for video data (training and batch predictions)
Custom model training
Interactive shell for custom training
Custom model online predictions and explanations
Custom model batch predictions and explanations
Data Labeling
Vertex AI Vizier
Vertex AI Pipelines
Vertex ML Metadata
Vertex AI Experiments
Vertex AI Feature Store
Vertex AI Model Monitoring
Vertex AI Matching Engine
Vertex AI TensorBoard

Vertex AI Workbench locations

Managed notebooks regions

Managed notebooks are available in the following regions.

Region description Zone name
Americas
Oregon us-west1
Las Vegas us-west4
Iowa us-central1
Montréal northamerica-northeast1
São Paulo southamerica-east1
Europe
Belgium europe-west1
Netherlands europe-west4
Asia Pacific
Mumbai asia-south1
Singapore asia-southeast1
Hong Kong asia-east2
Tokyo asia-northeast1
Sydney australia-southeast1
Seoul asia-northeast3

User-managed notebooks locations

User-managed notebooks are available in the following zones.

Region description Zone name
Americas
Oregon us-west1-a
us-west1-b
us-west1-c
Los Angeles us-west2-a
us-west2-b
us-west2-c
Las Vegas us-west4-a
us-west4-b
us-west4-c
Iowa us-central1-a
us-central1-b
us-central1-c
South Carolina us-east1-b
us-east1-c
us-east1-d
Northern Virginia us-east4-a
us-east4-b
us-east4-c
Montréal northamerica-northeast1-a
northamerica-northeast1-b
northamerica-northeast1-c
São Paulo southamerica-east1-a
southamerica-east1-b
southamerica-east1-c
Europe
London europe-west2-a
europe-west2-b
europe-west2-c
Belgium europe-west1-b
europe-west1-c
europe-west1-d
Netherlands europe-west4-a
europe-west4-b
europe-west4-c
Zürich europe-west6-a
europe-west6-b
europe-west6-c
Frankfurt europe-west3-a
europe-west3-b
europe-west3-c
Asia Pacific
Mumbai asia-south1-a
asia-south1-b
asia-south1-c
Singapore asia-southeast1-a
asia-southeast1-b
asia-southeast1-c
Jakarta asia-southeast2-a
asia-southeast2-b
asia-southeast2-c
Hong Kong asia-east2-a
asia-east2-b
asia-east2-c
Taiwan asia-east1-a
asia-east1-b
asia-east1-c
Tokyo asia-northeast1-a
asia-northeast1-b
asia-northeast1-c
Sydney australia-southeast1-a
australia-southeast1-b
australia-southeast1-c
Seoul asia-northeast3-a
asia-northeast3-b
asia-northeast3-c

Region considerations

Using accelerators

Accelerators are available on a region basis. The following table lists all the available accelerators for each region:

Americas

Region Oregon
us-west1		 Los Angeles
us-west2		 Salt Lake City
us-west3		 Las Vegas
us-west4		 Iowa
us-central1		 South Carolina
us-east1		 N. Virginia
us-east4		 Dallas
us-south1		 Montréal
northamerica-northeast1		 Toronto
northamerica-northeast2		 São Paulo
southamerica-east1
NVIDIA A100
NVIDIA Tesla K80
NVIDIA Tesla P4
NVIDIA Tesla P100
NVIDIA Tesla T4
NVIDIA Tesla V100 *
TPU V2 *
TPU V2 Pod *
TPU V3 * *
TPU V3 Pod

Europe

Region London
europe-west2		 Belgium
europe-west1		 Netherlands
europe-west4		 Zurich
europe-west6		 Frankfurt
europe-west3		 Warsaw
europe-central2		 Paris
europe-west9
NVIDIA A100
NVIDIA Tesla K80
NVIDIA Tesla P4
NVIDIA Tesla P100
NVIDIA Tesla T4 *
NVIDIA Tesla V100 *
TPU V2 *
TPU V2 Pod *
TPU V3 *
TPU V3 Pod *

Asia Pacific

Region Mumbai
asia-south1		 Singapore
asia-southeast1		 Jakarta
asia-southeast2		 Hong Kong
asia-east2		 Taiwan
asia-east1		 Tokyo
asia-northeast1		 Sydney
australia-southeast1		 Seoul
asia-northeast3
NVIDIA A100 †
NVIDIA Tesla K80
NVIDIA Tesla P4
NVIDIA Tesla P100
NVIDIA Tesla T4
NVIDIA Tesla V100 * * * *
TPU V2 *
TPU V2 Pod
TPU V3
TPU V3 Pod

Middle East

Region Tel Aviv
me-west1
NVIDIA A100
NVIDIA Tesla K80
NVIDIA Tesla P4
NVIDIA Tesla P100
NVIDIA Tesla T4
NVIDIA Tesla V100
TPU V2
TPU V2 Pod
TPU V3
TPU V3 Pod

* Cells marked with asterisks represent regions where the specified accelerator is available for training but not for serving batch or online predictions.

† Cells marked with daggers represent regions where the specified accelerator is available for serving batch or online predictions but not for training.

If your job uses multiple types of GPUs, they must all be available in a single zone in your region. For example, you can't run a job in us-central1 using NVIDIA Tesla T4 GPUs, NVIDIA Tesla K80 GPUs, and NVIDIA Tesla P100 GPUs. While all of these GPUs are available for jobs in us-central1, no single zone in that region provides all three types of GPU. To learn more about the zone availability of GPUs, see the comparison of GPUs for compute workloads.

BigQuery location requirements

When you use a BigQuery table as a source for a managed tabular dataset or tabular prediction data, it must conform to the following location requirements:

Americas

  • BigQuery tables can be either multi-regional (US) or regional (us-central1).

  • BigQuery views must be regional (us-central1).

  • If the table or view is not in the same project that the Vertex AI job is running in, make sure that Vertex AI has the correct roles.

Europe

  • BigQuery tables and views must be regional (europe-west4).

  • Location: The region that your Vertex AI job runs in, such as us-central1, europe-west4, or asia-east1.

  • If the table or view is not in the same project that the Vertex AI job is running in, make sure that Vertex AI has the correct roles.

Cloud Storage bucket requirements

Some Vertex AI tasks, such as importing data, use a Cloud Storage bucket.

  • We recommend that you use the following settings when creating a Cloud Storage bucket to use with Vertex AI:

    • Location type: Region.
    • Location: The region where you are using Vertex AI; for example, us-central1, europe-west4, or asia-east1.
    • Storage class: Standard.

    These settings are not strict requirements, but using these settings often improves performance. For example, it's possible to use a bucket in a multi-region with Vertex AI, but loading data from a bucket in the same region as your Vertex AI resource might reduce latency.

  • If the bucket is not in the same project that the Vertex AI job is running in, make sure Vertex AI has the correct roles.

Restricting resource locations

Organization policy administrators can restrict the regions available where you can use Vertex AI by creating a resource locations constraint. Read about how a resource locations constraint applies to Vertex AI

Resource locations constraints don't apply to DataLabelingJob resources.