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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Integrating applications with Google Cloud services	21%	- Consuming Google Cloud APIs and services 1. Integrating with AI/ML and generative AI services 2. Enabling and managing APIs 3. Using client libraries, REST, and gRPC - Implementing application performance monitoring 1. Using operations suite tools 2. Instrumenting code for metrics and traces - Integrating with data and storage services 1. Working with relational, NoSQL, and in-memory databases 2. Implementing messaging and event streaming 3. Using object storage and file storage solutions
Topic 2: Configuring cloud-native applications for deployment	24%	- Deploying applications to Cloud Run 1. Integrating with event-driven services 2. Configuring scaling, networking, and security 3. Deploying from source code or containers - Deploying applications to Google Kubernetes Engine 1. Managing configurations and secrets 2. Creating and managing workloads and services 3. Configuring scaling, auto-scaling, and updates - Deploying to App Engine or Cloud Functions 1. Configuring serverless deployments 2. Managing versions and traffic splitting
Topic 3: Building and testing applications	23%	- Building applications and containers 1. Using Cloud Build and Artifact Registry 2. Configuring build pipelines and provenance 3. Implementing containerization best practices - Setting up development environments 1. Emulating Google Cloud services locally 2. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations - Testing applications 1. Automating testing in CI/CD workflows 2. Writing unit, integration, and end-to-end tests 3. Using AI-assisted development tools
Topic 4: Designing highly scalable, secure, and reliable cloud-native applications	32%	- Designing secure applications 1. Implementing authentication and authorization mechanisms 2. Applying security best practices and compliance requirements 3. Securing data in transit and at rest - Designing high-performing applications and APIs 1. Selecting appropriate compute and deployment platforms 2. Designing for high availability and fault tolerance 3. Optimizing for latency and throughput - Designing for observability and monitoring 1. Designing for debugging and troubleshooting 2. Planning logging, metrics, and tracing strategies

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Google Certified Professional - Cloud Developer Sample Questions (Q128-Q133):

NEW QUESTION # 128
You are using Cloud Build to build and test application source code stored in Cloud Source Repositories. The build process requires a build tool not available in the Cloud Build environment.
What should you do?

A. Build a custom cloud builder image and reference the image in your build steps.
B. Ask to have the binary added to the Cloud Build environment by filing a feature request against the Cloud Build public Issue Tracker.
C. Include the binary in your Cloud Source Repositories repository and reference it in your build scripts.
D. Download the binary from the internet during the build process.

Answer: A

NEW QUESTION # 129
You plan to make a simple HTML application available on the internet. This site keeps information about FAQs for your application. The application is static and contains images, HTML, CSS, and Javascript. You want to make this application available on the internet with as few steps as possible.
What should you do?

A. Containerize your application first. Deploy this container to Google Kubernetes Engine (GKE) and assign an external IP address to the GKE pod hosting the application.
B. Upload your application to Cloud Storage.
C. Upload your application to an App Engine environment.
D. Create a Compute Engine instance with Apache web server installed. Configure Apache web server to host the application.

Answer: B

Explanation:
Explanation/Reference: https://cloud.google.com/storage/docs/hosting-static-website

NEW QUESTION # 130
You are building an API that will be used by Android and iOS apps The API must:
* Support HTTPs
* Minimize bandwidth cost
* Integrate easily with mobile apps
Which API architecture should you use?

A. SOAP-based APIs
B. gRPC-based APIs
C. MQTT for APIs
D. RESTful APIs

Answer: D

Explanation:
Explanation
Explanation/Reference: https://www.devteam.space/blog/how-to-build-restful-api-for-your-mobile-app/

NEW QUESTION # 131
You are deploying your application to a Compute Engine virtual machine instance with the Stackdriver Monitoring Agent installed. Your application is a unix process on the instance. You want to be alerted if the unix process has not run for at least 5 minutes. You are not able to change the application to generate metrics or logs.
Which alert condition should you configure?

A. Metric threshold
B. Metric absence
C. Uptime check
D. Process health

Answer: D

Explanation:
Reference: https://cloud.google.com/monitoring/alerts/concepts-indepth

NEW QUESTION # 132
You are building a CI/CD pipeline that consists of a version control system, Cloud Build, and Container Registry. Each time a new tag is pushed to the repository, a Cloud Build job is triggered, which runs unit tests on the new code builds a new Docker container image, and pushes it into Container Registry. The last step of your pipeline should deploy the new container to your production Google Kubernetes Engine (GKE) cluster.
You need to select a tool and deployment strategy that meets the following requirements:
* Zero downtime is incurred
* Testing is fully automated
* Allows for testing before being rolled out to users
* Can quickly rollback if needed
What should you do?

A. Trigger a Spinnaker pipeline configured as an A/B test of your new code and, if it is successful, deploy the container to production.
B. Trigger a Spinnaker pipeline configured as a canary test of your new code and, if it is successful, deploy the container to production.
C. Trigger another Cloud Build job that uses the Kubernetes CLI tools to deploy your new container to your GKE cluster, where you can perform a canary test.
D. Trigger another Cloud Build job that uses the Kubernetes CLI tools to deploy your new container to your GKE cluster, where you can perform a shadow test.

Answer: D

Explanation:
https://cloud.google.com/architecture/implementing-deployment-and-testing-strategies-on-gke#perform_a_shado With a shadow test, you test the new version of your application by mirroring user traffic from the current application version without impacting the user requests.

NEW QUESTION # 133
......

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