Cloud Life Sciences#
Tower provides integration to Google Cloud via the Cloud Life Sciences API.
The guide is split into two parts, namely how to configure your Google Cloud account and enable the Google Life Sciences Application Programming Interface (API), followed by a guide on how to create a new Google Cloud compute environment in Tower.
Configuration of Google Cloud#
Create a new Google Cloud project or select an existing one.#
Navigate to the Google Project Selector page and select an existing project or click CREATE PROJECT.
Enter a name for your new project e.g: "tower-nf".
If you are part of an organization the location will be set by default to match your organization parameters.
Make sure Billing is enabled for the project.#
At the top left of the page, in the navigation menu (≡) click Billing. You can follow the enable billing instructions here.
Enable the Google Life Sciences, the Compute Engine , and the Google Cloud Storage APIs.#
Open this link to enable all three APIs on for your project.
Select your project from the drop down menu and click Enable.
Alternatively enable these APIs manually by selecting the project on the top bar and visiting the API pages:
Retrieve the Compute Engine Service account for your project#
Click Go to credentials or visit this link
1. Select the Cloud Life Sciences API from the dropdown menu and select the radio button Yes, I'm using one or both to indicate we will use the Compute Engine API.
2. Then click What credentials do I need?
3. A second screen appears to say you do not need any further credentials. Click Done.
You will be redirected to the API & Services page and the Credentials section.
Note a Compute Engine default service account has been created.
4. Copy the email address as you will need this to configure Google Storage.
Create a new key for the compute service account#
1. Copy and click the Email of the service account.
2. Click "Manage Service accounts.
3. Select Add key and Create new key.
4. Select JSON as the key type. Then, press Create.
A JSON key will be downloaded to your computer.
This is the credential that is being used by Tower. You you will need it to configure the Tower compute environment. In the Service accounts page, you can see your key is now active and you can manage it from there.
Create a Google Storage bucket.#
In the top left of the page, there is a navigation menu (≡). Open it and then, proceed to click on Storage and Create Bucket.
Configure your Bucket#
Bucket Naming - No underscores _ !
Do not use underscores in your bucket name. Use hyphens instead.
1. Name your bucket, you will need this name to configure the Tower environment.
2. Select Region as the Location type and the Location for your bucket. You will need the Location to configure the Tower environment.
3. Select Standard as the default storage class.
4. Select Uniform as the Access control.
The Google Cloud Life Sciences API is available in limited number of locations, however, these locations are only used to store metadata about the pipeline operations. The location of the storage bucket and compute resources can be in any region.
Set Bucket permissions#
1. In the Storage page, on the Browser section, click on the newly created storage.
2. Navigate to the Permissions tab.
3. Click on + Add,
4. Copy-paste the service account email created above into the
new members box and add the following roles:
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 a JSON file containing required credentials. You are now ready to set up a new compute environment in Tower.
The following guide to configure Tower assumes you have JSON keys for a configured Google Cloud account. You will also need the name and location of the Google storage bucket.
The sections above shows how to configure Google Cloud.
To create a new compute environment for Google Cloud in Tower follow these steps:
1. In a workspace choose "Compute environments" and then, click on the New Environment button.
2. Enter a name for this environment, e.g. "Google Cloud Life Sciences (europe-west2)".
3. Select Google Life Sciences as the target platform.
4. Select the + sign to add new credentials.
5. Name your credentials.
6. Copy & paste the contents from the Google JSON key.
If you do not have a JSON key follow this guide.
7. Select the Region and Zones where you'd like to deploy the workload.
The Google Storage bucket created earlier should be accessible in the region.
8. You can leave the Location empty and Google will run the Life Sciences API Service in the closest available location.
9. Enter the bucket URL in the Pipeline work directory e.g. gs://my-google-bucket-name.
This is the name of your Google Storage bucket with the
10. You can also opt-in to execute the workflow on the Preemptible instances to save further cost.
11. If you'd like to integrate an existing Google FileStore volume to your compute environment, you can make use of the Filestore file system option.
12. You can specify certain environment variables on the Head job or the Compute job using the Environment variables option.
1. Optionally, settings such as Use Private Address, Boot disk size, Head Job CPUs and Head Job memory could be optimized as per the requirements of the workflow as well.
2. Select Create to finalise the creation of the compute environment.
Jump to the documentation section for Launching Pipelines.