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Free Google Associate Cloud Engineer Exam Braindumps (page: 19)

Page 18 of 74
PDF with 290 Questions

You are using Deployment Manager to create a Google Kubernetes Engine cluster. Using the same Deployment Manager deployment, you also want to create a DaemonSet in the kube-system namespace of the cluster. You want a solution that uses the fewest possible services.
What should you do?

  1. Add the cluster's API as a new Type Provider in Deployment Manager, and use the new type to create the DaemonSet.
  2. Use the Deployment Manager Runtime Configurator to create a new Config resource that contains the DaemonSet definition.
  3. With Deployment Manager, create a Compute Engine instance with a startup script that uses kubectl to create the DaemonSet.
  4. In the cluster's definition in Deployment Manager, add a metadata that has kube-system as key and the DaemonSet manifest as value.

Answer(s): A

Explanation:

Adding an API as a type provider
This page describes how to add an API to Google Cloud Deployment Manager as a type provider. To learn more about types and type providers, read the Types overview documentation.

A type provider exposes all of the resources of a third-party API to Deployment Manager as base types that you can use in your configurations. These types must be directly served by a RESTful API that supports Create, Read, Update, and Delete (CRUD).

If you want to use an API that is not automatically provided by Google with Deployment Manager, you must add the API as a type provider.

https://cloud.google.com/deployment-manager/docs/configuration/type-providers/creating-type- provider



You are building an application that will run in your data center. The application will use Google Cloud Platform (GCP) services like AutoML. You created a service account that has appropriate access to AutoML. You need to enable authentication to the APIs from your on-premises environment.
What should you do?

  1. Use service account credentials in your on-premises application.
  2. Use gcloud to create a key file for the service account that has appropriate permissions.
  3. Set up direct interconnect between your data center and Google Cloud Platform to enable authentication for your on-premises applications.
  4. Go to the IAM & admin console, grant a user account permissions similar to the service account permissions, and use this user account for authentication from your data center.

Answer(s): B


Reference:

https://cloud.google.com/vision/automl/docs/before-you-begin

To use a service account outside of Google Cloud, such as on other platforms or on-premises, you must first establish the identity of the service account. Public/private key pairs provide a secure way of accomplishing this goal. You can create a service account key using the Cloud Console, the gcloud tool, the serviceAccounts.keys.create() method, or one of the client libraries.

Ref: https://cloud.google.com/iam/docs/creating-managing-service-account-keys



You are using Container Registry to centrally store your company's container images in a separate project. In another project, you want to create a Google Kubernetes Engine (GKE) cluster. You want to ensure that Kubernetes can download images from Container Registry.
What should you do?

  1. In the project where the images are stored, grant the Storage Object Viewer IAM role to the service account used by the Kubernetes nodes.
  2. When you create the GKE cluster, choose the Allow full access to all Cloud APIs option under `Access scopes'.
  3. Create a service account, and give it access to Cloud Storage. Create a P12 key for this service account and use it as an imagePullSecrets in Kubernetes.
  4. Configure the ACLs on each image in Cloud Storage to give read-only access to the default Compute Engine service account.

Answer(s): A

Explanation:

Configure the ACLs on each image in Cloud Storage to give read-only access to the default Compute Engine service account. is not right.
As mentioned above, Container Registry ignores permissions set on individual objects within the storage bucket so this isnt going to work.

Ref: https://cloud.google.com/container-registry/docs/access-control



You deployed a new application inside your Google Kubernetes Engine cluster using the YAML file specified below.



You check the status of the deployed pods and notice that one of them is still in PENDING status:



You want to find out why the pod is stuck in pending status.
What should you do?

  1. Review details of the myapp-service Service object and check for error messages.
  2. Review details of the myapp-deployment Deployment object and check for error messages.
  3. Review details of myapp-deployment-58ddbbb995-lp86m Pod and check for warning messages.
  4. View logs of the container in myapp-deployment-58ddbbb995-lp86m pod and check for warning messages.

Answer(s): C

Explanation:

https://kubernetes.io/docs/tasks/debug-application-cluster/debug-application/#debugging-pods






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