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Google Professional-Cloud-Developer, also known as Google Certified Professional - Cloud Developer, is a certification exam offered by Google. Professional-Cloud-Developer exam is designed to test the candidate's knowledge and skills in developing, designing, and managing applications using Google Cloud Platform. Professional-Cloud-Developer exam is intended for developers who have experience in developing and deploying applications on Google Cloud Platform.

The Professional-Cloud-Developer Exam is intended for developers who have experience in building applications on Google Cloud, and who are looking to demonstrate their expertise to potential employers and clients. Professional-Cloud-Developer exam covers a wide range of topics, including cloud computing concepts, Google Cloud services, application development, and deployment.

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Google Professional-Cloud-Developer Certification Exam is intended for developers who have experience with Google Cloud Platform, as well as those who are familiar with at least one programming language such as Java, Python, or Node.js. Candidates are expected to have knowledge of cloud application development principles, containerization technologies, and best practices for building scalable and secure applications.

Google Certified Professional - Cloud Developer Sample Questions (Q119-Q124):

NEW QUESTION # 119
You are designing a resource-sharing policy for applications used by different teams in a Google Kubernetes Engine cluster. You need to ensure that all applications can access the resources needed to run. What should you do? (Choose two.)

A. Create a LimitRange to specify the default compute resource requirements for each namespace.
B. Specify the resource limits and requests in the object specifications.
C. Create a Kubernetes service account (KSA) for each application, and assign each KSA to the namespace.
D. Create a namespace for each team, and attach resource quotas to each namespace.
E. Use the Anthos Policy Controller to enforce label annotations on all namespaces. Use taints and tolerations to allow resource sharing for namespaces.

Answer: A,D

Explanation:
Explanation
https://kubernetes.io/docs/concepts/policy/resource-quotas/
https://kubernetes.io/docs/concepts/policy/limit-range/
https://cloud.google.com/blog/products/containers-kubernetes/kubernetes-best-practices-resource-requests-and-li

NEW QUESTION # 120
Which of the following statements is true about an actively swelling embedded battery?

A. Actively swelling batteries are unlikely to lead to thermal runaway.
B. Actively swelling batteries are more likely to rupture and release gasses.
C. Actively swelling batteries are likely caused by large amounts of liquid inside the batteries.
D. Actively swelling batteries are not considered a safety concern.

Answer: B

Explanation:
Explanation/Reference: https://www.ifixit.com/News/11211/what-to-do-with-a-swollen-iphone-battery

NEW QUESTION # 121
Your team develops stateless services that run on Google Kubernetes Engine (GKE). You need to deploy a new service that will only be accessed by other services running in the GKE cluster.
The service will need to scale as quickly as possible to respond to changing load. What should you do?

A. Use a Vertical Pod Autoscaler to scale the containers, and expose them via a NodePort Service.
B. Use a Horizontal Pod Autoscaler to scale the containers, and expose them via a NodePort Service.
C. Use a Vertical Pod Autoscaler to scale the containers, and expose them via a ClusterIP Service.
D. Use a Horizontal Pod Autoscaler to scale the containers, and expose them via a ClusterIP Service.

Answer: D

Explanation:
https://cloud.google.com/kubernetes-engine/docs/concepts/service#services_of_type_clusterip When you create a Service of type ClusterIP, Kubernetes creates a stable IP address that is accessible from nodes in the cluster.
https://cloud.google.com/kubernetes-engine/docs/concepts/horizontalpodautoscaler The Horizontal Pod Autoscaler changes the shape of your Kubernetes workload by automatically increasing or decreasing the number of Pods in response to the workload's CPU or memory consumption, or in response to custom metrics reported from within Kubernetes or external metrics from sources outside of your cluster.

NEW QUESTION # 122
You are developing a new Python 3 API that needs to be deployed to Cloud Run. Your Cloud Run service sits behind an Apigee proxy. You need to ensure that the Cloud Run service is running with the already deployed Apigee proxy. You want to conduct this testing as quickly as possible. What should you do?

A. Store the service code as a zip file in a Cloud Storage bucket. Deploy your application by using the gcloud run deploy --source command, and test the integration by pointing Apigee to Cloud Run.
B. Use the Cloud Run emulator to test your application locally. Test the integration by pointing Apigee to your local Cloud Run emulator.
C. Deploy your application directly from the current directory by using the gcloud run deploy --source command, and test the integration by pointing Apigee to Cloud Run.
D. Build a container image locally, and push the image to Artifact Registry. Deploy the Image to Cloud Run, and test the integration by pointing Apigee to Cloud Run.

Answer: C

Explanation:
Deploying directly from the current directory with gcloud run deploy --source enables rapid deployment and immediate integration testing with the Apigee proxy, minimizing setup time and complexity.

NEW QUESTION # 123
You are developing a microservice-based application that will be deployed on a Google Kubernetes Engine cluster. The application needs to read and write to a Spanner database. You want to follow security best practices while minimizing code changes. How should you configure your application to retrieve Spanner credentials?

A. Store the application credentials using Cloud Key Management Service, and retrieve them whenever a database connection is made.
B. Store the application credentials as Kubernetes Secrets, and expose them as environment variables.
C. Configure the appropriate service accounts, and use Workload Identity to run the pods.
D. Configure the appropriate routing rules, and use a VPC-native cluster to directly connect to the database.

Answer: C

Explanation:
https://cloud.google.com/blog/products/containers-kubernetes/introducing-workload-identity- better-authentication-for-your-gke-applications A Cloud IAM service account is an identity that an application can use to make requests to Google APIs. As an application developer, you could generate individual IAM service accounts for each application, and then download and store the keys as a Kubernetes secret that you manually rotate. Not only is this process burdensome, but service account keys only expire every
10 years (or until you manually rotate them). In the case of a breach or compromise, an unaccounted-for key could mean prolonged access for an attacker. This potential blind spot, plus the management overhead of key inventory and rotation, makes using service account keys as secrets a less than ideal method for authenticating GKE workloads.

NEW QUESTION # 124
......

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