Pass the Google Cloud Certified Associate-Cloud-Engineer Questions and answers with ValidTests

"...we recommend that you enable Cloud Billing data export to BigQuery at the same time that you create a Cloud Billing account. "https://cloud.google.com/billing/docs/how-to/export-data-bigquery

https://medium.com/google-cloud/analyzing-google-cloud-billing-data-with-big-query-30bae1c2aae4

Billing Administrators can not create a new billing account, and the project is presumably already created. Project Billing Manager allows you to link the created billing account to the project. It is vague on how the billing account gets created but by process of elimination

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

Granting more permissions than necessary violates the principle of least privilege, a fundamental security best practice. While option A grants the necessary permissions (as subsets exist in two predefined roles), it might also grant more permissions than the Operations team strictly requires for their tasks on GKE and Cloud SQL. Option D is too broad; 'Admin' roles grant extensive permissions that likely exceed the specific needs.

Google Cloud's best practices strongly recommend adhering to the principle of least privilege. Creating a custom role allows you to precisely define the set of permissions the Operations team needs for their specific tasks on the GKE cluster and the Cloud SQL instance, without granting any unnecessary permissions. This minimizes the potential blast radius in case of accidental or malicious actions.

Google Cloud Documentation References:

IAM best practices: https://cloud.google.com/iam/docs/best-practices - This document explicitly recommends granting the minimum necessary permissions.

Creating and managing custom roles: https://cloud.google.com/iam/docs/creating-managing-custom-roles - This explains how to create roles tailored to specific job functions.

Understanding roles: https://cloud.google.com/iam/docs/understanding-roles - This outlines the concepts of predefined and custom roles and their use cases.

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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

If your apps are fault-tolerant and can withstand possible instance preemptions, then preemptible instances can reduce your Compute Engine costs significantly. For example, batch processing jobs can run on preemptible instances. If some of those instances stop during processing, the job slows but does not completely stop. Preemptible instances complete your batch processing tasks without placing additional workload on your existing instances and without requiring you to pay full price for additional normal instances.

https://cloud.google.com/compute/docs/instances/preemptible

As mentioned in Schema and data model, you should be careful when choosing a primary key to not accidentally create hotspots in your database. One cause of hotspots is having a column whose value monotonically increases as the first key part, because this results in all inserts occurring at the end of your key space. This pattern is undesirable because Cloud Spanner divides data among servers by key ranges, which means all your inserts will be directed at a single server that will end up doing all the work.https://cloud.google.com/spanner/docs/schema-design#primary-key-prevent-hotspots

Preventing Accidental VM Deletion This document describes how to protect specific VM instances from deletion by setting the deletionProtection property on an Instance resource. To learn more about VM instances, read the Instances documentation. As part of your workload, there might be certain VM instances that are critical to running your application or services, such as an instance running a SQL server, a server used as a license manager, and so on. These VM instances might need to stay running indefinitely so you need a way to protect these VMs from being deleted. By setting the deletionProtection flag, a VM instance can be protected from accidental deletion. If a user attempts to delete a VM instance for which you have set the deletionProtection flag, the request fails. Only a user that has been granted a role with compute.instances.create permission can reset the flag to allow the resource to be deleted.https://cloud.google.com/compute/docs/instances/preventing-accidental-vm-deletion