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Free Google Cloud Architect Professional Exam Braindumps (page: 25)

Page 24 of 68
PDF with 278 Questions

You want to enable your running Google Kubernetes Engine cluster to scale as demand for your application changes.

What should you do?

  1. Add additional nodes to your Kubernetes Engine cluster using the following command:gcloud container clusters resizeCLUSTER_Name ­ -size 10
  2. Add a tag to the instances in the cluster with the following command:gcloud compute instances add-tagsINSTANCE - -tags enable-autoscaling max-nodes-10
  3. Update the existing Kubernetes Engine cluster with the following command:gcloud alpha container clustersupdate mycluster - -enable-autoscaling - -min-nodes=1 - -max-nodes=10
  4. Create a new Kubernetes Engine cluster with the following command:gcloud alpha container clusterscreate mycluster - -enable-autoscaling - -min-nodes=1 - -max-nodes=10and redeploy your application

Answer(s): C

Explanation:

https://cloud.google.com/kubernetes-engine/docs/concepts/cluster-autoscaler To enable autoscaling for an existing node pool, run the following command:
gcloud container clusters update [CLUSTER_NAME] --enable-autoscaling \ --min-nodes 1 --max-nodes 10 --zone [COMPUTE_ZONE] --node-pool default-pool



A lead engineer wrote a custom tool that deploys virtual machines in the legacy data center. He wants to migrate the custom tool to the new cloud environment You want to advocate for the adoption of Google Cloud Deployment Manager What are two business risks of migrating to Cloud

Deployment Manager? Choose 2 answers

  1. Cloud Deployment Manager uses Python.
  2. Cloud Deployment Manager APIs could be deprecated in the future.
  3. Cloud Deployment Manager is unfamiliar to the company's engineers.
  4. Cloud Deployment Manager requires a Google APIs service account to run.
  5. Cloud Deployment Manager can be used to permanently delete cloud resources.
  6. Cloud Deployment Manager only supports automation of Google Cloud resources.

Answer(s): C,F

Explanation:

https://cloud.google.com/deployment-manager/docs/deployments/deleting-deployments



You write a Python script to connect to Google BigQuery from a Google Compute Engine virtual machine. The script is printing errors that it cannot connect to BigQuery.
What should you do to fix the script?

  1. Install the latest BigQuery API client library for Python
  2. Run your script on a new virtual machine with the BigQuery access scope enabled
  3. Create a new service account with BigQuery access and execute your script with that user
  4. Install the bq component for gccloud with the command gcloud components install bq.

Answer(s): B

Explanation:

The error is most like caused by the access scope issue.
When create new instance, you have the default Compute engine default service account but most serves access including BigQuery is not enable. Create an instance Most access are not enabled by default You have default service account but don't have the permission (scope) you can stop the instance, edit, change scope and restart it to enable the scope access. Of course, if you Run your script on a new virtual machine with the BigQuery access scope enabled, it also works https://cloud.google.com/compute/docs/access/service-accounts



Your company just finished a rapid lift and shift to Google Compute Engine for your compute needs. You have another 9 months to design and deploy a more cloud-native solution. Specifically, you want a system that is no-ops and auto-scaling.
Which two compute products should you choose? Choose 2 answers

  1. Compute Engine with containers
  2. Google Kubernetes Engine with containers
  3. Google App Engine Standard Environment
  4. Compute Engine with custom instance types
  5. Compute Engine with managed instance groups

Answer(s): B,C

Explanation:

B: With Container Engine, Google will automatically deploy your cluster for you, update, patch, secure the nodes.
Kubernetes Engine's cluster autoscaler automatically resizes clusters based on the demands of the workloads you want to run.
C: Solutions like Datastore, BigQuery, AppEngine, etc are truly NoOps. App Engine by default scales the number of instances running up and down to match the load, thus providing consistent performance for your app at all times while minimizing idle instances and thus reducing cost.
Note: At a high level, NoOps means that there is no infrastructure to build out and manage during usage of the platform. Typically, the compromise you make with NoOps is that you lose control of the underlying infrastructure.


Reference:

https://www.quora.com/How-well-does-Google-Container-Engine-support-Google- Cloud-Platform%E2%80%99s-NoOps-claim






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