How resources are organized in a GCP project

In Google Cloud Platform (GCP), resources are organized hierarchically within a project, and projects are the main way to group related resources. Here’s a detailed breakdown of how resources are managed in GCP:

GCP Resource Hierarchy

1. Organization: The top level of the hierarchy. It represents a company, institution, or another group. All projects and resources belong to an organization.

2. Folders: Optional and used to organize projects. Folders can contain other folders and projects.

3. Projects: The fundamental entity that organizes all your GCP resources. Every resource belongs to exactly one project.

4. Resources: Individual services and instances like Compute Engine VMs, Cloud Storage buckets, BigQuery datasets, etc.

Projects

• Identity and Access Management (IAM): Permissions and access control are managed at the project level (though permissions can be more granularly managed for specific resources within a project).
• Billing: All resources within a project are billed to the same account.
• Quota Management: Quotas are applied at the project level.
• APIs and Services: Enabling APIs is done at the project level.

Resource Management

Resources within GCP projects can be managed per project but can also be scoped or managed by users within a project. Here's a detailed look at how this works:

Per Project

• APIs and Services: APIs are enabled at the project level.
• Billing: Billing is handled at the project level.
• IAM Policies: Access control policies can be set at the project level to manage who has access to which resources.

Per User

• IAM Roles and Permissions: IAM can assign roles and permissions to individual users or service accounts at a more granular level.
  • For example, you might give a user read-only access to a Cloud Storage bucket but full access to a BigQuery dataset.
• Resource Ownership: While resources belong to a project, specific resources can be created and managed by individual users. For instance:
  • A specific VM instance might be managed by a particular user with the necessary IAM permissions.
  • Cloud Functions or App Engine services can be deployed and managed by users within the project with appropriate roles.

Example Scenarios

1. Project Level:

   • Example: A project called my-data-project that contains BigQuery datasets, Cloud Storage buckets, and Compute Engine instances.
   • Management: Project administrators can manage APIs, billing, and overall permissions for the entire project.

2. User Level:

   • Example: Within my-data-project, a user named Alice is given the role of BigQuery Data Editor, allowing her to create and manage datasets and tables within BigQuery.
   • Management: Alice can manage the datasets and tables she has permissions for, but she might not have access to other resources like Compute Engine instances unless explicitly granted.

Resource Example

IAM Policies

• Project Level:

  {
    "bindings": [
      {
        "role": "roles/owner",
        "members": [
          "user:[email protected]"
        ]
      }
    ]
  }
  

• Resource Level:

  {
    "bindings": [
      {
        "role": "roles/storage.objectViewer",
        "members": [
          "user:[email protected]"
        ]
      }
    ]
  }
  

Resource Scoping

• Compute Engine: A VM instance can be created within a project but assigned to a specific service account that manages it.
• Cloud Storage: Buckets and objects can have ACLs (Access Control Lists) that define which users or groups can access them.