Associate-Cloud-Engineer Valid Test Objectives & Valid Associate-Cloud-Engineer Test Guide
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Google Associate Cloud Engineer Exam Sample Questions (Q299-Q304):
NEW QUESTION # 299
You have designed a solution on Google Cloud Platform (GCP) that uses multiple GCP products.
Your company has asked you to estimate the costs of the solution.
You need to provide estimates for the monthly total cost. What should you do?
- A. Provision the solution on GCP. Leave the solution provisioned for 1 week.
Navigate to the Billing Report page in the Google Cloud Platform Console.
Multiply the 1 week cost to determine the monthly costs. - B. For each GCP product in the solution, review the pricing details on the products pricing page.
Use the pricing calculator to total the monthly costs for each GCP product. - C. Provision the solution on GCP. Leave the solution provisioned for 1 week.
Use Stackdriver to determine the provisioned and used resource amounts.
Multiply the 1 week cost to determine the monthly costs. - D. For each GCP product in the solution, review the pricing details on the products pricing page.
Create a Google Sheet that summarizes the expected monthly costs for each product.
Answer: B
NEW QUESTION # 300
You are hosting an application on bare-metal servers in your own data center. The application needs access to Cloud Storage. However, security policies prevent the servers hosting the application from having public IP addresses or access to the internet. You want to follow Google-recommended practices to provide the application with access to Cloud Storage. What should you do?
- A. 1. Use Migrate for Compute Engine (formerly known as Velostrata) to migrate those servers to Compute Engine.2. Create an internal load balancer (ILB) that uses storage.googleapis.com as backend.
3. Configure your new instances to use this ILB as proxy. - B. 1. Using Cloud VPN or Interconnect, create a tunnel to a VPC in GCP.2. Use Cloud Router to create a custom route advertisement for 199.36.153.4/30. Announce that network to your on-premises network through the VPN tunnel.3. In your on-premises network, configure your DNS server to resolve *.googleapis.com as a CNAME to restricted.googleapis.com.
- C. 1. Use nslookup to get the IP address for storage.googleapis.com.2. Negotiate with the security team to be able to give a public IP address to the servers.3. Only allow egress traffic from those servers to the IP addresses for storage.googleapis.com.
- D. 1. Using Cloud VPN, create a VPN tunnel to a Virtual Private Cloud (VPC) in Google Cloud Platform (GCP).2. In this VPC, create a Compute Engine instance and install the Squid proxy server on this instance.3. Configure your servers to use that instance as a proxy to access Cloud Storage.
Answer: B
Explanation:
Our requirement is to follow Google recommended practices to achieve the end result. Configuring Private Google Access for On-Premises Hosts is best achieved by VPN/Interconnect + Advertise Routes + Use restricted Google IP Range.
* Using Cloud VPN or Interconnect, create a tunnel to a VPC in GCP
* Using Cloud Router to create a custom route advertisement for 199.36.153.4/30. Announce that network to your on-premises network through the VPN tunnel.
* In your on-premises network, configure your DNS server to resolve *.googleapis.com as a CNAME to restricted.googleapis.com is the right answer right, and it is what Google recommends.
Ref: https://cloud.google.com/vpc/docs/configure-private-google-access-hybrid
* You must configure routes so that Google API traffic is forwarded through your Cloud VPN or Cloud Interconnect connection, firewall rules on your on-premises firewall to allow the outgoing traffic, and DNS so that traffic to Google APIs resolves to the IP range youve added to your routes.
* You can use Cloud Router Custom Route Advertisement to announce the Restricted Google APIs IP addresses through Cloud Router to your on-premises network. The Restricted Google APIs IP range is
199.36.153.4/30. While this is technically a public IP range, Google does not announce it publicly. This IP range is only accessible to hosts that can reach your Google Cloud projects through internal IP ranges, such as through a Cloud VPN or Cloud Interconnect connection. Without having a public IP address or access to the internet, the only way you could connect to cloud storage is if you have an internal route to it.
* So Negotiate with the security team to be able to give public IP addresses to the servers is not right.
Following Google recommended practices is synonymous with using Googles services (Not quite, but it is at least for the exam !!).
* So In this VPC, create a Compute Engine instance and install the Squid proxy server on this instance is not right.
* Migrating the VM to Compute Engine is a bit drastic when Google says it is perfectly fine to have Hybrid Connectivity architectures https://cloud.google.com/hybrid-connectivity.
So,
* Use Migrate for Compute Engine (formerly known as Velostrata) to migrate these servers to Compute Engine is not right.
NEW QUESTION # 301
You created a Kubernetes deployment by running kubectl run nginx image=nginx replicas=1. After a few days, you decided you no longer want this deployment. You identified the pod and deleted it by running kubectl delete pod. You noticed the pod got recreated.
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
nginx-84748895c4-nqqmt 1/1 Running 0 9m41s
$ kubectl delete pod nginx-84748895c4-nqqmt
pod nginx-84748895c4-nqqmt deleted
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
nginx-84748895c4-k6bzl 1/1 Running 0 25s
What should you do to delete the deployment and avoid pod getting recreated?
- A. kubectl delete pod nginx-84748895c4-k6bzl -no-restart 2
- B. kubectl delete deployment nginx
- C. kubectl delete inginx
- D. kubectl delete -deployment=nginx
Answer: B
Explanation:
Explanation
This command correctly deletes the deployment. Pods are managed by kubernetes workloads (deployments).
When a pod is deleted, the deployment detects the pod is unavailable and brings up another pod to maintain the replica count. The only way to delete the workload is by deleting the deployment itself using the kubectl delete deployment command.
$ kubectl delete deployment nginx
deployment.apps nginx deleted
Ref: https://kubernetes.io/docs/reference/kubectl/cheatsheet/#deleting-resources
NEW QUESTION # 302
(You are deploying an application to Google Kubernetes Engine (GKE). The application needs to make API calls to a private Cloud Storage bucket. You need to configure your application Pods to authenticate to the Cloud Storage API, but your organization policy prevents the usage of service account keys. You want to follow Google-recommended practices. What should you do?)
- A. Create the GKE cluster with Workload Identity Federation. Configure the default node service account to access the bucket. Deploy the application into the cluster so the application can use the node service account permissions. Use Identity and Access Management (IAM) to grant the service account access to the bucket.
- B. Create the GKE cluster and deploy the application. Request a security exception to create a Google service account key. Set the constraints/iam.serviceAccountKeyExpiryHours organization policy to 24 hours.
- C. Create the GKE cluster with Workload Identity Federation. Create a Google service account and a Kubernetes ServiceAccount, and configure both service accounts to use Workload Identity Federation.
Attach the Kubernetes ServiceAccount to the application Pods and configure the Google service account to access the bucket with Identity and Access Management (IAM). - D. Create the GKE cluster and deploy the application. Request a security exception to create a Google service account key. Set the constraints/iam.serviceAccountKeyExpiryHours organization policy to 8 hours.
Answer: C
Explanation:
The organization policy explicitly prevents the use of service account keys, so options A and B, which involve requesting exceptions to create them, are not in line with the policy and Google's recommended practices for secure authentication.
NEW QUESTION # 303
You significantly changed a complex Deployment Manager template and want to confirm that the dependencies of all defined resources are properly met before committing it to the project. You want the most rapid feedback on your changes. What should you do?
- A. Monitor activity of the Deployment Manager execution on the Stackdriver Logging page of the GCP Console.
- B. Use granular logging statements within a Deployment Manager template authored in Python.
- C. Execute the Deployment Manager template using the --previewoption in the same project, and observe the state of interdependent resources.
- D. Execute the Deployment Manager template against a separate project with the same configuration, and monitor for failures.
Answer: C
Explanation:
Explanation/Reference: https://cloud.google.com/deployment-manager/docs/deployments/updating-deployments
NEW QUESTION # 304
......
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