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Google Professional-Cloud-Developer Exam Syllabus Topics:

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

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Google Certified Professional - Cloud Developer Sample Questions (Q335-Q340):

NEW QUESTION # 335
How do you access Control Center from the home screen on an iPhone 8?

A. Swipe up from the bottom of the screen.
B. Swipe down from the top of the screen.
C. Swipe from left to right.
D. Swipe from right to left.

Answer: A

Explanation:
Explanation/Reference: https://www.imore.com/control-center

NEW QUESTION # 336
Your company has a data warehouse that keeps your application information in BigQuery. The BigQuery data warehouse keeps 2 PBs of user data. Recently, your company expanded your user base to include EU users and needs to comply with these requirements:
Your company must be able to delete all user account information upon user request.
All EU user data must be stored in a single region specifically for EU users.
Which two actions should you take? (Choose two.)

A. Create a Cloud Storage bucket in the EU region to store information for EU users only.
B. Create a dataset in the EU region that will keep information about EU users only.
C. Use BigQuery federated queries to query data from Cloud Storage.
D. Re-upload your data using to a Cloud Dataflow pipeline by filtering your user records out.
E. Use DML statements in BigQuery to update/delete user records based on their requests.

Answer: A,E

Explanation:
Reference:
https://cloud.google.com/solutions/bigquery-data-warehouse

NEW QUESTION # 337
Your website is deployed on Compute Engine. Your marketing team wants to test conversion rates between 3 different website designs.
Which approach should you use?

A. Deploy the website on App Engine as three separate services.
B. Deploy the website on Cloud Functions and use traffic splitting.
C. Deploy the website on App Engine and use traffic splitting.
D. Deploy the website on Cloud Functions as three separate functions.

Answer: C

Explanation:
Reference:
https://cloud.google.com/appengine/docs/standard/python/splitting-traffic

NEW QUESTION # 338
You want to view the memory usage of your application deployed on Compute Engine. What should you do?

A. Use the Stackdriver Metrics Explorer.
B. Use the Google Cloud Platform Console.
C. Install the Stackdriver Client Library.
D. Install the Stackdriver Monitoring Agent.

Answer: A

Explanation:
Explanation/Reference: https://stackoverflow.com/questions/43991246/google-cloud-platform-how-to-monitor-memory- usage-of-vm-instances

NEW QUESTION # 339
You have containerized a legacy application that stores its configuration on an NFS share. You need to deploy this application to Google Kubernetes Engine (GKE) and do not want the application serving traffic until after the configuration has been retrieved. What should you do?

A. Add a startup script to the GKE instance group to mount the NFS share at node startup. Copy the configuration files into the container, and start the service using an ENTRYPOINT script.
B. Use the gsutil utility to copy files from within the Docker container at startup, and start the service using an ENTRYPOINT script.
C. Use the COPY statement in the Dockerfile to load the configuration into the container image. Verify that the configuration is available, and start the service using an ENTRYPOINT script.
D. Create a PersistentVolumeClaim on the GKE cluster. Access the configuration files from the volume, and start the service using an ENTRYPOINT script.

Answer: D

Explanation:
Reference: https://cloud.google.com/compute/docs/instances/startup-scripts/linux

NEW QUESTION # 340
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