Most Recent Google Professional-Cloud-DevOps-Engineer Exam Questions & Answers

The best option for selecting the machine type for the application to use that optimizes CPU utilization by using the fewest number of steps is to use the Recommender API and apply the suggested recommendations. The Recommender API is a service that provides recommendations for optimizing your Google Cloud resources, such as Compute Engine instances, disks, and firewalls. You can use the Recommender API to get recommendations for changing the machine type of your Compute Engine instances based on historical system metrics, such as CPU utilization. You can also apply the suggested recommendations by using the Recommender API or Cloud Console. This way, you can optimize CPU utilization by using the most suitable machine type for your application with minimal effort.

For a postmortem to be truly blameless, it must focus on identifying the contributing causes of the incident without indicting any individual or team for bad or inappropriate behavior.

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

The correct answer is D. Grant the roles/storage.objectAdmin Identity and Access Management (IAM) role to the Cloud Build service account on the state file bucket.

According to the Google Cloud documentation, Cloud Build is a service that executes your builds on Google Cloud Platform infrastructure1. Cloud Build uses a service account to execute your build steps and access resources, such as Cloud Storage buckets2. Terraform is an open-source tool that allows you to define and provision infrastructure as code3. Terraform uses a state file to store and track the state of your infrastructure4. You can configure Terraform to use a Cloud Storage bucket as a backend to store and share the state file across multiple users or environments5.

The error message indicates that Cloud Build failed to access the Cloud Storage bucket that contains the Terraform state file. This is likely because the Cloud Build service account does not have the necessary permissions to read and write objects in the bucket. To resolve this issue, you need to grant the roles/storage.objectAdmin IAM role to the Cloud Build service account on the state file bucket. This role allows the service account to create, delete, and manage objects in the bucket6. You can use the gcloud command-line tool or the Google Cloud Console to grant this role.

The other options are incorrect because they do not follow Google-recommended practices. Option A is incorrect because it changes the Terraform code to use local state, which is not recommended for production or collaborative environments, as it can cause conflicts, data loss, or inconsistency. Option B is incorrect because it creates a new storage bucket with the name specified in the Terraform configuration, but it does not grant any permissions to the Cloud Build service account on the new bucket. Option C is incorrect because it grants the roles/owner IAM role to the Cloud Build service account on the project, which is too broad and violates the principle of least privilege. The roles/owner role grants full access to all resources in the project, which can pose a security risk if misused or compromised.

Cloud Build Documentation, Overview. Service accounts, Service accounts. Terraform by HashiCorp, Terraform by HashiCorp. State, State. Google Cloud Storage Backend, Google Cloud Storage Backend. Predefined roles, Predefined roles. [Granting roles to service accounts for specific resources], Granting roles to service accounts for specific resources. [Local Backend], Local Backend. [Understanding roles], Understanding roles.

The best option to give developers the ability to manage infrastructure as code, while ensuring that you follow Google-recommended practices, is to install and configure Config Connector in Google Kubernetes Engine (GKE).

Config Connector is a Kubernetes add-on that allows you to manage Google Cloud resources through Kubernetes. You can use Config Connector to create, update, and delete Google Cloud resources using Kubernetes manifests. Config Connector also reconciles the state of the Google Cloud resources with the desired state defined in the manifests, ensuring that there is no configuration drift1.

Config Connector follows the GitOps methodology, as it allows you to store your infrastructure configuration in a Git repository, and use tools such as Anthos Config Management or Cloud Source Repositories to sync the configuration to your GKE cluster. This way, you can use Git as the source of truth for your infrastructure, and enable reviewable and version-controlled workflows2.

Config Connector can be installed and configured in GKE using either the Google Cloud Console or the gcloud command-line tool. You need to enable the Config Connector add-on for your GKE cluster, and create a Google Cloud service account with the necessary permissions to manage the Google Cloud resources. You also need to create a Kubernetes namespace for each Google Cloud project that you want to manage with Config Connector3.

By using Config Connector in GKE, you can give developers the ability to manage infrastructure as code, while ensuring that you follow Google-recommended practices. You can also benefit from the features and advantages of Kubernetes, such as declarative configuration, observability, and portability4.

1: Overview | Artifact Registry Documentation | Google Cloud

2: Deploy Anthos on GKE with Terraform part 1: GitOps with Config Sync | Google Cloud Blog

3: Installing Config Connector | Config Connector Documentation | Google Cloud

4: Why use Config Connector? | Config Connector Documentation | Google Cloud