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Google Professional-Cloud-Developer certification exam is designed to test the knowledge and skills of individuals who develop and deploy applications in the Google Cloud Platform (GCP) environment. Professional-Cloud-Developer exam is a part of the Google Cloud Certification Program, which offers certifications for different roles in the cloud computing industry. The Professional-Cloud-Developer certification exam is intended for developers who have experience working with GCP and are proficient in at least one programming language.

To pass the Google Professional-Cloud-Developer examination, individuals must be proficient in different programming languages such as Python, Java, and Node.js as well as have a solid understanding of cloud technologies including Google's App Engine, Kubernetes, and BigQuery. You will also need to have a solid understanding of Google Cloud's API and services. Professional-Cloud-Developer exam is designed to check these skills and more, making it essential to have practical experience with Google Cloud technology.

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To obtain the Google Professional-Cloud-Developer Certification, applicants are required to pass a rigorous exam that covers a broad range of topics, including Google Cloud Platform architecture, application development, storage, security, and deployment. Professional-Cloud-Developer exam is composed of multiple-choice questions and simulations, and it is designed to test the practical knowledge and experience of the developer. Passing the exam requires a comprehensive understanding of Google Cloud technologies and the ability to apply this knowledge to real-world scenarios. Successful candidates receive a Google Certified Professional - Cloud Developer certification, which is recognized globally as a symbol of expertise and proficiency in cloud development.

Google Certified Professional - Cloud Developer Sample Questions (Q27-Q32):

NEW QUESTION # 27
You are a SaaS provider deploying dedicated blogging software to customers in your Google Kubernetes Engine (GKE) cluster. You want to configure a secure multi-tenant platform to ensure that each customer has access to only their own blog and can't affect the workloads of other customers. What should you do?

A. Build a custom image of the blogging software and use Binary Authorization to prevent untrusted image deployments.
B. Use GKE Audit Logging to identify malicious containers and delete them on discovery.
C. Enable Application-layer Secrets on the GKE cluster to protect the cluster.
D. Deploy a namespace per tenant and use Network Policies in each blog deployment.

Answer: D

Explanation:
https://cloud.google.com/kubernetes-engine/docs/concepts/multitenancy-overview

NEW QUESTION # 28
You are a developer at a large organization. Your team uses Git for source code management (SCM). You want to ensure that your team follows Google-recommended best practices to manage code to drive higher rates of software delivery. Which SCM process should your team use?

A. Each developer creates a branch for their own work, commits their changes to their branch, and merges their code into the main branch daily.
B. Each group of developers creates a feature branch from the main branch for their work, commits their changes to their branch, and merges their code into the main branch after the change advisory board approves it.
C. Each group of developers copies the repository, commits their changes to their repository, and merges their code into the main repository before each product release.
D. Each developer commits their code to the main branch before each product release, conducts testing, and rolls back if integration issues are detected.

Answer: B

Explanation:
Use a centralized repository. A centralized repository is a single location where all of your team's code is stored. This makes it easy for everyone to access the latest code, and it also helps to prevent conflicts.
Use branches. Branches are a way to create a separate version of the code for development purposes. This allows developers to work on new features or bug fixes without affecting the main branch of the code.

NEW QUESTION # 29
You are a developer at a large organization. You are deploying a web application to Google Kubernetes Engine (GKE). The DevOps team has built a CI/CD pipeline that uses Cloud Deploy to deploy the application to Dev Test, and Prod clusters in GKE. After Cloud Deploy successfully deploys the application to the Dev cluster you want to automatically promote it to the Test Cluster. How should you configure this process following Google-recommended best practices?

A. 1 Create a Cloud Function that calls the Google Cloud Deploy API to promote the application to the Test cluster
2 Configure this function to be triggered by SUCCEEDED Pub/Sub messages from the cloud-builds topic
B. 1 Create a Cloud Function that calls the Google Cloud Deploy API to promote the application to the Test cluster
2 Configure this function to be triggered by SUCCEEDED Pub/Sub messages from the clouddeploy operations topic
C. 1 Create a Cloud Build trigger that listens for SUCCEEDED Pub/Sub messages from the clouddeploy-operations topic.
2 Configure Cloud Build to include a step that promotes the application to the Test cluster
D. 1 Create a Cloud Build pipeline that uses the gke-deploy builder
2 Create a Cloud Build trigger that listens to SUCCEEDED Pub/Sub messages from the cloud-builds topic

Answer: A

Explanation:
3 Configure this pipeline to run a deployment step to the Test cluster

NEW QUESTION # 30
The new version of your containerized application has been tested and is ready to deploy to production on Google Kubernetes Engine. You were not able to fully load-test the new version in pre-production environments, and you need to make sure that it does not have performance problems once deployed. Your deployment must be automated. What should you do?

A. Deploy the application using kubectl and set the spec.updateStrategv.type to RollingUpdate. Use Cloud Monitoring to look for performance issues, and run the kubectl rollback command if there are any issues.
B. Deploy the application via a continuous delivery pipeline using blue/green deployments. Use Cloud Monitoring to look for performance issues, and launch fully when the metrics support it.
C. Deploy the application via a continuous delivery pipeline using canary deployments. Use Cloud Monitoring to look for performance issues. and ramp up traffic as the metrics support it.
D. Use Cloud Load Balancing to slowly ramp up traffic between versions. Use Cloud Monitoring to look for performance issues.

Answer: B

Explanation:
https://cloud.google.com/architecture/implementing-deployment-and-testing-strategies-on-gke#perform_a_blueg

NEW QUESTION # 31
You are working on a new application that is deployed on Cloud Run and uses Cloud Functions Each time new features are added, new Cloud Functions and Cloud Run services are deployed You use ENV variables to keep track of the services and enable interservice communication but the maintenance of the ENV variables has become difficult. You want to implement dynamic discovery in a scalable way. What should you do?

A. Rename the Cloud Functions and Cloud Run services endpoints using a well-documented naming convention
B. Configure your microservices to use the Cloud Run Admin and Cloud Functions APIs to query for deployed Cloud Run services and Cloud Functions in the Google Cloud project.
C. Create a Service Directory Namespace Use API calls to register the services during deployment, and query during runtime.
D. Deploy Hashicorp Consul on a single Compute Engine Instance Register the services with Consul during deployment and query during runtime

Answer: B

NEW QUESTION # 32
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