Locations

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 AI Platform (Unified) except for data labeling tasks and any feature in experimental 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 AI Platform service 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 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 AI Platform (Unified) API

You specify the location for an AI Platform 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

For a full list of supported endpoints, see the API reference documentation.

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

Available regions

AI Platform is available in the following regions:

Americas

  • Iowa (us-central1)

Europe

  • Netherlands (europe-west4)

Asia Pacific

  • Taiwan (asia-east1)

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

Service availability

Some AI Platform services are not available in all regions. The following table lists the services that are available in each region:

Americas

Region Iowa
us-central1
AutoML for image data (training, online predictions, and batch predictions)
AutoML for tabular data (training, online predictions, and batch predictions)
AutoML for text data (training, online predictions, and batch predictions)
AutoML for video data (training and batch predictions)
Custom model training
Custom model online predictions
Custom model batch predictions
Data Labeling

Europe

Region Netherlands
europe-west4
AutoML for image data (training, online predictions, and batch predictions)
AutoML for tabular data (training, online predictions, and batch predictions)
AutoML for text data (training, online predictions, and batch predictions)
AutoML for video data (training and batch predictions)
Custom model training
Custom model online predictions
Custom model batch predictions
Data Labeling

Asia Pacific

Region Taiwan
asia-east1
AutoML for image data (training, online predictions, and batch predictions)
AutoML for tabular data (training, online predictions, and batch predictions)
AutoML for text data (training, online predictions, and batch predictions)
AutoML for video data (training and batch predictions)
Custom model training
Custom model online predictions
Custom model batch predictions
Data Labeling

Region considerations

Training with accelerators

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

Americas

Region Iowa
us-central1
NVIDIA Tesla K80
NVIDIA Tesla P4
NVIDIA Tesla P100
NVIDIA Tesla T4
NVIDIA Tesla V100

Europe

Region Netherlands
europe-west4
NVIDIA Tesla K80
NVIDIA Tesla P4
NVIDIA Tesla P100
NVIDIA Tesla T4
NVIDIA Tesla V100

Asia Pacific

Region Taiwan
asia-east1
NVIDIA Tesla K80
NVIDIA Tesla P4
NVIDIA Tesla P100
NVIDIA Tesla T4
NVIDIA Tesla V100

If your job uses multiple types of GPUs, they must all be available in a single zone in your region. For example, you cannot 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.

Insufficient resources

Demand is high for GPUs and for compute resources in the us-central1 region. You may get an error message in your job logs that says: Resources are insufficient in region: <region>. Please try a different region..

To resolve this issue, try using a different region or try again later.

Cloud Storage bucket requirements

Some AI Platform tasks, such as importing data from your local computer, use a Cloud Storage bucket.

  • Create your Cloud Storage buckets in the same region that your AI Platform job runs in.

  • Use the following settings when creating Cloud Storage a bucket to read and write data for your AI Platform job.

    • Location type: Region.
    • Location: The region that your AI Platform (Unified) job runs in, such as us-central1, europe-west4, or asia-east1.
    • Storage class: Standard (sometimes displayed in the Cloud Storage browser as Regional).

Restricting resource locations

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

Resource locations constraints don't apply to DataLabelingJob resources.