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Google Professional-Cloud-Developer Exam Syllabus Topics:

SectionWeightObjectives
Integrating applications with Google Cloud services21%- Implementing application performance monitoring
  • 1. Using operations suite tools
  • 2. Instrumenting code for metrics and traces
- 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
- 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
Configuring cloud-native applications for deployment24%- Deploying applications to Google Kubernetes Engine
  • 1. Creating and managing workloads and services
  • 2. Configuring scaling, auto-scaling, and updates
  • 3. Managing configurations and secrets
- Deploying applications to Cloud Run
  • 1. Deploying from source code or containers
  • 2. Configuring scaling, networking, and security
  • 3. Integrating with event-driven services
- Deploying to App Engine or Cloud Functions
  • 1. Configuring serverless deployments
  • 2. Managing versions and traffic splitting
Building and testing applications23%- Setting up development environments
  • 1. Emulating Google Cloud services locally
  • 2. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations
- Building applications and containers
  • 1. Configuring build pipelines and provenance
  • 2. Using Cloud Build and Artifact Registry
  • 3. Implementing containerization best practices
- Testing applications
  • 1. Using AI-assisted development tools
  • 2. Automating testing in CI/CD workflows
  • 3. Writing unit, integration, and end-to-end tests
Designing highly scalable, secure, and reliable cloud-native applications32%- Designing high-performing applications and APIs
  • 1. Selecting appropriate compute and deployment platforms
  • 2. Optimizing for latency and throughput
  • 3. Designing for high availability and fault tolerance
- Designing secure applications
  • 1. Applying security best practices and compliance requirements
  • 2. Securing data in transit and at rest
  • 3. Implementing authentication and authorization mechanisms
- 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 (Q192-Q197):

NEW QUESTION # 192
You are running an application on App Engine that you inherited. You want to find out whether the application is using insecure binaries or is vulnerable to XSS attacks. Which service should you use?

Answer: C

Explanation:
Reference:
https://cloud.google.com/security-scanner


NEW QUESTION # 193
Your application is logging to Stackdriver. You want to get the count of all requests on all /api/alpha/* endpoints.
What should you do?

Answer: D

Explanation:
Explanation/Reference:


NEW QUESTION # 194

Answer: E


NEW QUESTION # 195
You are building a Workflow to process complex data analytics for your application. You plan to use the Workflow to execute a Cloud Run job while following Google-recommended practices.
What should you do?

Answer: D

Explanation:
Using the Cloud Run Admin API connector within Workflows is the Google-recommended way to directly execute a Cloud Run job from a Workflow, providing secure and managed integration.


NEW QUESTION # 196
You want to create "fully baked" or "golden" Compute Engine images for your application. You need to bootstrap your application to connect to the appropriate database according to the environment the application is running on (test, staging, production). What should you do?

Answer: D


NEW QUESTION # 197
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