Google edusum google Cloud Certified Changed Associate-cloud-engineer Questions by Tessa q65 vce pdf

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Google Associate-Cloud-Engineer Exam Overview :

Exam Name:	Google Cloud Certified - Associate Cloud Engineer
Exam Code:	Associate-Cloud-Engineer Dumps
Vendor:	Google	Certification:	Google Cloud Certified
Questions:	363 Q&A's	Shared By:	tessa

Question 104

You are the Google Cloud systems administrator for your organization. User A reports that they received an error when attempting to access the Cloud SQL database in their Google Cloud project, while User B can access the database. You need to troubleshoot the issue for User A, while following Google-recommended practices.

What should you do first?

Options:

Confirm that network firewall rules are not blocking traffic for User A.

Review recent configuration changes that may have caused unintended modifications to permissions.

Verify that User A has the Identity and Access Management (IAM) Project Owner role assigned.

Review the error message that User A received.

Discussion

Question 105

You have an application that reads data from a Pub/Sub topic. During local development, you authenticated using your personal credentials to test the application. You now want to deploy the application to Vertex AI and have created a new service account to be used as the application ' s identity. You need to ensure that the deployed application can still access the Pub/Sub topic. What should you do?

Options:

Extract your access token by using the gcloud auth print-access-token command, and store it with the application.

Grant the relevant IAM roles to the service account used as your agent identity.

Create a secret in Secret Manager to store your personal credentials, and configure the application ' s authentication code to use this secret.

Generate a JSON private key for the service account, and upload the key as Vertex AI metadata.

Discussion

Billy

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Question 106

You are deploying an application to Cloud Run. Your application requires the use of an API that runs on Google Kubernetes Engine (GKE). You need to ensure that your Cloud Run service can privately reach the API on GKE, and you want to follow Google-recommended practices. What should you do?

Options:

Deploy an ingress resource on the GKE cluster to expose the API to the internet. Use Cloud Armor to filter for IP addresses that can connect to the API. On the Cloud Run service, configure the application to fetch its public IP address and update the Cloud Armor policy on startup to allow this IP address to call the API on ports 80 and 443.

Create an egress firewall rule on the VPC to allow connections to 0.0.0.0/0 on ports 80 and 443.

Create an ingress firewall rule on the VPC to allow connections from 0.0.0.0/0 on ports 80 and 443.

Deploy an internal Application Load Balancer to expose the API on GKE to the VPC. Configure Cloud DNS with the IP address of the internal Application Load Balancer. Deploy a Serverless VPC Access connector to allow the Cloud Run service to call the API through the FQDN on Cloud DNS.

Discussion

Answer:

Explanation:

The requirement is for private communication between a Cloud Run service and a GKE API, following best practices.

Option A exposes the GKE API to the public internet, which violates the " privately reach " requirement. Relying on dynamic IP allowlisting with Cloud Armor is complex and less secure than private networking.

Options B and C configure overly permissive firewall rules (allowing all egress or ingress) and do not establish the necessary private network path between Cloud Run (which normally runs outside your VPC) and the GKE cluster within your VPC.

Option D describes the standard Google-recommended pattern for this scenario:

Internal Application Load Balancer (ILB): Expose the GKE service (API) using an ILB. This gives the service a private IP address accessible only within the VPC network (or connected networks).

Cloud DNS: Create a private DNS zone and record pointing a fully qualified domain name (FQDN) to the ILB ' s private IP address. This allows services to reach the API via a stable name instead of an IP.

Serverless VPC Access Connector: This connector creates a bridge allowing serverless services like Cloud Run to send traffic into your VPC network.

Cloud Run Configuration: Configure the Cloud Run service to use the VPC Access connector. The application code can then call the GKE API using its private FQDN registered in Cloud DNS.

This setup ensures traffic flows entirely over private networks (within the VPC via the ILB and through the VPC Access connector), meeting the private communication requirement securely and reliably.

[References:, Serverless VPC Access: "Serverless VPC Access lets your serverless environment send requests to your VPC network..." - https://cloud.google.com/vpc/docs/serverless-vpc-access, Internal Application Load Balancer Overview: "Google Cloud internal Application Load Balancers are regional, proxy-based Layer 7 load balancers that enable you to run and scale your services behind an internal IP address..." - https://cloud.google.com/load-balancing/docs/internal, Connecting from Cloud Run to a VPC network: Documentation often outlines patterns using VPC Access Connectors and Internal Load Balancers or Private Service Connect. - https://cloud.google.com/run/docs/configuring/connecting-vpc, GKE Internal Load Balancing: How to expose GKE services internally. - https://cloud.google.com/kubernetes-engine/docs/how-to/internal-load-balancing, , , ]

Question 107

After a recent security incident, your startup company wants better insight into what is happening in the Google Cloud environment. You need to monitor unexpected firewall changes and instance creation. Your company prefers simple solutions. What should you do?

Options:

Use Cloud Logging filters to create log-based metrics for firewall and instance actions. Monitor the changes and set up reasonable alerts.

Install Kibana on a compute Instance. Create a log sink to forward Cloud Audit Logs filtered for firewalls andcompute instances to Pub/Sub. Target the Pub/Sub topic to push messages to the Kibana instance. Analyze the logs on Kibana in real time.

Turn on Google Cloud firewall rules logging, and set up alerts for any insert, update, or delete events.

Create a log sink to forward Cloud Audit Logs filtered for firewalls and compute instances to Cloud Storage.Use BigQuery to periodically analyze log events in the storage bucket.

Discussion

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