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add new permissions from the IAM Admin panel
create GCS bucket
Labels
Labels are key-value pairs meant to better organize the projects.
Lets imagine the scenario when the client has multiple Data Scientists working on different projects. Labeling them will allow better structure.
| Code Block |
|---|
team:data-science
component:<main-application-name>
environment:production
|
More information on labels: https://cloud.google.com/resource-manager/docs/creating-managing-labels
Permissions
The permissions are added when the project is created.
By default, the requestor`s email has the project editor role
Once the project is released, the requestor can add more emails / users to the IAM policies of the project.
Here is a sample of provided permissions (optional):
| Code Block |
|---|
user:dana@boxalino.com:roles/editor
user:dana@boxalino.com:roles/resourcemanager.projectIamAdmin
user:dana@boxalino.com:roles/compute.osLogin
user:dana@boxalino.com:roles/compute.osAdminLogin
user:dana@boxalino.com:roles/bigquery.dataOwner
serviceAccount:service-account-from-other-projects:roles/iam.serviceAccountUser
serviceAccount:service-account-from-other-projects:roles/bigquery.dataOwner
serviceAccount:service-account-from-other-projects:roles/bigquery.dataEditor |
More information on permissions: https://cloud.google.com/iam/docs/understanding-roles
Required Files
| 1 | instance.txt | properties for the VM machine (name, size, root path, etc) (see Instance) |
| 2 | env.yml | anaconda environment file |
| 3 | requirements.txt | environment requirements (for pip/anaconda install) (see Requirements) |
| 4 | commands.txt | a list of commands to be executed as part of your application run process |
| 5 | your jupyter files | the jupyter notebook |
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