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Google Professional-Cloud-Developer Exam Syllabus Topics:

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

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Google Certified Professional - Cloud Developer Sample Questions (Q234-Q239):

NEW QUESTION # 234
You configured your Compute Engine instance group to scale automatically according to overall CPU usage.
However, your application's response latency increases sharply before the cluster has finished adding up instances. You want to provide a more consistent latency experience for your end users by changing the configuration of the instance group autoscaler.
Which two configuration changes should you make? (Choose two.)

A. Decrease the cool-down period for instances added to the group.
B. Increase the target CPU usage for the instance group autoscaler.
C. Add the label "AUTOSCALE" to the instance group template.
D. Remove the health-check for individual VMs in the instance group.
E. Decrease the target CPU usage for the instance group autoscaler.

Answer: B,C

Explanation:
Explanation

NEW QUESTION # 235
You want to re-architect a monolithic application so that it follows a microservices model. You want to accomplish this efficiently while minimizing the impact of this change to the business.
Which approach should you take?

A. Build a new application with the appropriate microservices separate from the monolith and replace it when it is complete.
B. Replace the application's features with appropriate microservices in phases.
C. Refactor the monolithic application with appropriate microservices in a single effort and deploy it.
D. Deploy the application to Compute Engine and turn on autoscaling.

Answer: C

Explanation:
Explanation/Reference: https://cloud.google.com/solutions/migrating-a-monolithic-app-to-microservices-gke

NEW QUESTION # 236
You are writing a single-page web application with a user-interface that communicates with a third-party API for content using XMLHttpRequest. The data displayed on the UI by the API results is less critical than other data displayed on the same web page, so it is acceptable for some requests to not have the API data displayed in the UI. However, calls made to the API should not delay rendering of other parts of the user interface. You want your application to perform well when the API response is an error or a timeout.
What should you do?

A. Catch timeout or error exceptions from the API call and display the error response in the UI widget.
B. Catch timeout or error exceptions from the API call and keep trying with exponential backoff until the API response is successful.
C. Set the asynchronous option for your requests to the API to false and omit the widget displaying the API results when a timeout or error is encountered.
D. Set the asynchronous option for your request to the API to true and omit the widget displaying the API results when a timeout or error is encountered.

Answer: C

NEW QUESTION # 237
HipLocal wants to improve the resilience of their MySQL deployment, while also meeting their business and technical requirements.
Which configuration should they choose?

A. Replace the current single instance MySQL instance with Cloud SQL, and Google provides redundancy without further configuration.
B. Use the current single instance MySQL on Compute Engine, and replicate the data to Cloud SQL in an external master configuration.
C. Use the current single instance MySQL on Compute Engine and several read-only MySQL servers on Compute Engine.
D. Replace the current single instance MySQL instance with Cloud SQL, and configure high availability.

Answer: B

NEW QUESTION # 238
You are developing an application hosted on Google Cloud that uses a MySQL relational database schema.
The application will have a large volume of reads and writes to the database and will require backups and ongoing capacity planning. Your team does not have time to fully manage the database but can take on small administrative tasks. How should you host the database?

A. Configure Cloud SQL to host the database, and import the schema into Cloud SQL.
B. Configure Firestore to host the database, and import the data into Firestore.
C. Configure Bigtable to host the database, and import the data into Bigtable.
D. Deploy MySQL from the Google Cloud Marketplace to the database using a client, and import the schema.
E. Configure Cloud Spanner to host the database, and import the schema into Cloud Spanner.

Answer: A

Explanation:
Explanation
https://cloud.google.com/spanner/docs/migrating-mysql-to-spanner#migration-process Cloud SQL: Cloud SQL is a web service that allows you to create, configure, and use relational databases that live in Google's cloud. It is a fully-managed service that maintains, manages, and administers your databases, allowing you to focus on your applications and services.
https://cloud.google.com/sql/docs/mysql Cloud SQL for MySQL is a fully-managed database service that helps you set up, maintain, manage, and administer your MySQL relational databases on Google Cloud Platform.

NEW QUESTION # 239
......

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