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Version: 22.4.0



Tower's Google Cloud Batch support is in Beta — more features will be added as Nextflow GCB support is enhanced over time.

This guide assumes you have an existing Google Cloud Account. Sign-up for a free account here.

Tower provides integration to Google Cloud via the Batch API.

The guide is split into two parts:

  1. How to configure your Google Cloud account to use the Batch API.

  2. How to create a Google Cloud Batch compute environment in Tower.

Configure Google Cloud

Create a project

Navigate to the Google Project Selector page and either select an existing project or select Create project.

Enter a name for your new project, e.g "tower-nf".

If you are part of an organization, the location will default to your organization.

Enable billing

In the navigation menu (), select Billing. You can follow these instructions to enable billing.

Enable APIs

Use this link to enable the following APIs for your project:

  • Batch API
  • Compute Engine API
  • Cloud Storage API

Select your project from the dropdown menu and select Enable.

Alternatively, you can enable each API manually by selecting your project in the nav bar and visiting each API page:

Create a service account key

  1. In the navigation menu, select IAM & Admin and then Service Accounts.

  2. Select the email address of the Compute Engine default service account.

  3. Select Keys, then Add key, then Create new key.

  4. Select JSON as the key type.

  5. Select Create.

A JSON file will be downloaded to your computer. This file contains the credential that will be used by Tower. You will need it to configure the compute environment in Tower.

You can manage your key from the Service Accounts page.

Create a Cloud Storage bucket

  1. In the navigation menu (), select Cloud Storage and then Create bucket.

  2. Enter a name for your bucket. You will reference this name when creating the compute environment in Tower.

    Do not use underscores (_) in your bucket name. Use hyphens (-) instead.

  3. Select Region for the Location type and select the Location for your bucket. You will reference this location when creating the compute environment in Tower.

  4. Select Standard for the default storage class.

  5. Select Uniform for the Access control.

    The Batch API is available in a limited number of locations. However, these locations are only used to store metadata about the pipeline operations. The storage bucket and compute resources can be in any region.

  6. Select Create.

  7. Once the bucket is created, you will be redirected to the Bucket details page.

  8. Select Permissions, then + Add.

  9. Copy the email address of the Compute Engine default service account into New principals.

  10. Select the following roles:

  • Storage Admin
  • Storage Legacy Bucket Owner
  • Storage Legacy Object Owner
  • Storage Object Creator

You have created a project, enabled the necessary Google APIs, created a bucket, and created a JSON file with the required credentials. You are now ready to set up a new compute environment in Tower.

Configure Tower

The following guide to configure Tower assumes you have (1) a service account key for a Google Cloud account and (2) the name and location of a Cloud Storage bucket.

To create a new compute environment for Google Cloud in Tower:

  1. In a workspace, select Compute Environments and then New Environment.

  2. Enter a descriptive name for this environment, e.g. "Google Cloud Batch (europe-north1)".

  3. Select Google Cloud Batch as the target platform.

  4. Add new credentials by selecting the + button.

  5. Enter a name for the credentials, e.g. "Google Cloud Credentials".

  6. Enter the Service account key for your Google Cloud account. This key was created in the previous section.

  7. Select the Location where you'd like to execute pipelines.

  8. Enter your bucket URL for the Pipeline work directory. The URL is the name of your bucket with the gs:// prefix, e.g. gs://my-bucket. This bucket should be accessible in the region selected in the previous step.

  9. You can enable Spot to use spot instances, which have significantly reduced cost compared to on-demand instances.

  10. You can use the Environment variables option to specify custom environment variables for the Head job and/or Compute jobs.

  11. Configure any advanced options described below, as needed.

  12. Select Create to finalize the compute environment setup.

Jump to the documentation for Launching Pipelines.

Advanced options

  • You can enable Use Private Address to ensure that your Google Cloud VMs aren't accessible to the public internet.

  • You can use Boot disk size to control the boot disk size of VMs.

  • You can use Head Job CPUs and Head Job Memory to specify the CPUs and memory allocated for head jobs.