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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Objectives
Topic 1: Building and testing applications	- Unit and integration testing strategies - Debugging and troubleshooting applications - Application development on Google Cloud
Topic 2: Ensuring application performance and reliability	- Monitoring and logging (Cloud Monitoring, Cloud Logging) - Fault tolerance and incident response - Performance optimization
Topic 3: Designing cloud-native applications	- Application architecture design - Scalability and resiliency patterns - Microservices design principles
Topic 4: Integrating Google Cloud services	- API integration and service-to-service communication - Using managed services (Pub/Sub, Firestore, Cloud SQL)
Topic 5: Deploying applications	- CI/CD pipelines - Release management strategies - Containerization and deployment (Cloud Run, GKE)

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Google Professional-Cloud-Developer Exam Questions are Available in 3 Easy-to-Understand Formats

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Google Certified Professional - Cloud Developer Sample Questions (Q248-Q253):

NEW QUESTION # 248
You are deploying your applications on Compute Engine. One of your Compute Engine instances failed to launch. What should you do? (Choose two.)

A. Check whether network traffic to or from your instance is being dropped.
B. Check whether your instance boot disk is completely full.
C. Determine whether your file system is corrupted.
D. Access Compute Engine as a different SSH user.
E. Troubleshoot firewall rules or routes on an instance.

Answer: B,C

Explanation:
Explanation
https://cloud.google.com/compute/docs/troubleshooting/vm-startup

NEW QUESTION # 249
There are three teams developing an ecommerce application in the same Google Cloud project.
Team A will build a set of RESTful APIs that exposes some core functionalities for the application.
Team B and Team C will make requests to those APIs in their downstream processes running on Cloud Run services. You need to propose a solution for exposing the APIs in a way that maximizes security and minimizes management overhead for the three teams. How should you design this solution?

A. 1. Team A uses an API key to authorize Cloud API Gateway and shares the key with Team B and Team C.
2. Team B and Team C store the API key in a secret in Secret Manager, and use this API key to access the API endpoint.
B. 1. Team A uses service accounts to authorize Cloud API Gateway. Team B and Team C each create a service account, export their service account's key, and store each key in a separate secret in Secret Manager.
2. Team B and Team C use this service account key to create an OAuth token to access the APIs.
C. 1. Team A uses Apigee hybrid to create an API key and shares that key with Team B and Team
2. Team B and Team C store the API key in a secret in Secret Manager, and use this API key to access the API endpoint.
D. 1. Team A uses service accounts to authorize Cloud API Gateway. Team B and Team C each create a service account that has access to the APIs.
2. Team B and Team C access the APIs in the Cloud Run service running their processes by using the service accounts attached to their service.

Answer: D

Explanation:
This solution maximizes security by using service accounts for authentication and authorization, avoiding the need to manage and distribute API keys or secrets, which can be insecure and cumbersome. By configuring Cloud API Gateway to use service accounts, you ensure that only authorized services can access the APIs securely. Attaching the service accounts directly to Team B and Team C's Cloud Run services enables seamless and secure access without requiring manual handling of credentials.
Using service accounts also aligns with Google Cloud's best practices for identity and access management, minimizing management overhead while providing a scalable and secure way to control access across teams and services.

NEW QUESTION # 250
You have deployed an HTTP(s) Load Balancer with the gcloud commands shown below.

Health checks to port 80 on the Compute Engine virtual machine instance are failing and no traffic is sent to your instances. You want to resolve the problem.
Which commands should you run?

A. gcloud compute instances add-access-config ${NAME}-backend-instance-1
B. gcloud compute firewall-rules create allow-lb --network load-balancer --allow tcp --destination-ranges 130.211.0.0/22,35.191.0.0/16 --direction EGRESS
C. gcloud compute instances add-tags ${NAME}-backend-instance-1 --tags http-server
D. gcloud compute firewall-rules create allow-lb --network load-balancer --allow tcp --source-ranges 130.211.0.0/22,35.191.0.0/16 --direction INGRESS

Answer: D

Explanation:
Reference: https://cloud.google.com/vpc/docs/special-configurations

NEW QUESTION # 251
Your application is running in multiple Google Kubernetes Engine clusters. It is managed by a Deployment in each cluster. The Deployment has created multiple replicas of your Pod in each cluster. You want to view the logs sent to stdout for all of the replicas in your Deployment in all clusters.
Which command should you use?

A. kubectl exec -it [PARAM] journalctl
B. gcloud compute ssh [PARAM] --command= "sudo journalctl"
C. kubectl logs [PARAM]
D. gcloud logging read [PARAM]

Answer: D

Explanation:
https://cloud.google.com/blog/products/management-tools/using-logging-your-apps-running- kubernetes-engine gcloud command line tool - Using the gcloud logging read command, select the appropriate cluster, node, pod and container logs.

NEW QUESTION # 252
Your team develops services that run on Google Kubernetes Engine. Your team's code is stored in Cloud Source Repositories. You need to quickly identify bugs in the code before it is deployed to production. You want to invest in automation to improve developer feedback and make the process as efficient as possible. What should you do?

A. Use Cloud Build to automate building container images from code based on Git tags.
B. Use Spinnaker to automate deploying container images to the production environment.
C. Use Cloud Build to automate building container images from code based on forked versions.
D. Use Spinnaker to automate building container images from code based on Git tags.

Answer: D

NEW QUESTION # 253
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