Associate-Cloud-Engineer Exam Dumps - Google Cloud Certified - Associate Cloud Engineer

The correct answer is A because the policy must apply across projects that are already spread across different folders. Setting the resource location constraint at the organization level gives consistent inheritance across the whole resource hierarchy instead of requiring repeated folder-level configuration. Since the business requirement is to permit only EEA locations, an allow-list model is safer than a deny-list model. A deny list can miss future or unexpected locations, while allowed values define the permitted geographic boundary. Google Cloud’s resource locations constraint supports allowed_values and denied_values, and Google recommends using allowed values or value groups to define the geographic boundary for resources.

Explanation

Run gcloud builds submit tag gcr.io/img-278322/acme_track_n_trace:v1. is the right answer.

This command correctly tags the image as acme_track_n_trace:v1 and uploads the image to the img-278322 project.

Ref: https://cloud.google.com/sdk/gcloud/reference/builds/submit

https://cloud.google.com/iam/docs/best-practices-for-using-and-managing-service-accounts

If an application uses third-party or custom identities and needs to access a resource, such as a BigQuery dataset or a Cloud Storage bucket, it must perform a transition between principals. Because Google Cloud APIs don ' t recognize third-party or custom identities, the application can ' t propagate the end-user ' s identity to BigQuery or Cloud Storage. Instead, the application has to perform the access by using a different Google identity.

https://cloud.google.com/logging/docs/audit

Data Access audit logs Data Access audit logs contain API calls that read the configuration or metadata of resources, as well as user-driven API calls that create, modify, or read user-provided resource data.

https://cloud.google.com/logging/docs/audit#data-access

The most secure method and Google-recommended practice for local testing of service account permissions is Service Account Impersonation , as it avoids the security risk of managing physical key files.

Option A (Impersonation): This method allows your user credentials to temporarily act as the service account. It is keyless , meaning no service account key needs to be created, downloaded, or stored, which is the cornerstone of secure credential management on Google Cloud.

Read the dataset ' s metadata and to list tables in the dataset. Read data and metadata from the dataset ' s tables. When applied at the project or organization level, this role can also enumerate all datasets in the project. Additional roles, however, are necessary to allow the running of jobs.

BigQuery Data Viewer

(roles/bigquery.dataViewer)

When applied to a table or view, this role provides permissions to:

Read data and metadata from the table or view.

This role cannot be applied to individual models or routines.

When applied to a dataset, this role provides permissions to:

Read the dataset ' s metadata and list tables in the dataset.

Read data and metadata from the dataset ' s tables.

When applied at the project or organization level, this role can also enumerate all datasets in the project. Additional roles, however, are necessary to allow the running of jobs.

Lowest-level resources where you can grant this role:

Table

View

BigQuery Job User

(roles/bigquery.jobUser)

Provides permissions to run jobs, including queries, within the project.

Lowest-level resources where you can grant this role:

Project

to run jobs https://cloud.google.com/bigquery/docs/access-control#bigquery.jobUser databaseUser needs additional role permission to run jobshttps://cloud.google.com/spanner/docs/iam#spanner.databaseUser

https://cloud.google.com/compute/docs/disks/local-ssd