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Google Professional-Cloud-Developer Exam Syllabus Topics:

SectionWeightObjectives
Configuring cloud-native applications for deployment24%- Deploying to App Engine or Cloud Functions
  • 1. Configuring serverless deployments
  • 2. Managing versions and traffic splitting
- 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. Deploying from source code or containers
  • 2. Integrating with event-driven services
  • 3. Configuring scaling, networking, and security
Building and testing applications23%- Testing applications
  • 1. Writing unit, integration, and end-to-end tests
  • 2. Automating testing in CI/CD workflows
  • 3. Using AI-assisted development tools
- Building applications and containers
  • 1. Using Cloud Build and Artifact Registry
  • 2. Implementing containerization best practices
  • 3. Configuring build pipelines and provenance
- Setting up development environments
  • 1. Emulating Google Cloud services locally
  • 2. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations
Integrating applications with Google Cloud services21%- Integrating with data and storage services
  • 1. Using object storage and file storage solutions
  • 2. Implementing messaging and event streaming
  • 3. Working with relational, NoSQL, and in-memory databases
- Consuming Google Cloud APIs and services
  • 1. Integrating with AI/ML and generative AI services
  • 2. Using client libraries, REST, and gRPC
  • 3. Enabling and managing APIs
- Implementing application performance monitoring
  • 1. Using operations suite tools
  • 2. Instrumenting code for metrics and traces
Designing highly scalable, secure, and reliable cloud-native applications32%- Designing high-performing applications and APIs
  • 1. Designing for high availability and fault tolerance
  • 2. Selecting appropriate compute and deployment platforms
  • 3. Optimizing for latency and throughput
- 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

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Google Certified Professional - Cloud Developer Sample Questions (Q65-Q70):

NEW QUESTION # 65
You are working on a social media application. You plan to add a feature that allows users to upload images.
These images will be 2 MB - 1 GB in size. You want to minimize their infrastructure operations overhead for this feature. What should you do?

Answer: B

Explanation:
Explanation/Reference: https://cloud.google.com/blog/products/storage-data-transfer/uploading-images-directly-to-cloud- storage-by-using-signed-url


NEW QUESTION # 66
You are developing a scalable web application for internal users. Your organization uses Google Workspace. You need to set up authentication to the application for the users, and then deploy the application on Google Cloud. You plan to use cloud-native features, and you want to minimize infrastructure management effort. What should you do? (Choose two.)

Answer: D,E

Explanation:
https://support.google.com/a/answer/7281227?hl=en


NEW QUESTION # 67
Your application requires service accounts to be authenticated to GCP products via credentials stored on its host Compute Engine virtual machine instances. You want to distribute these credentials to the host instances as securely as possible.
What should you do?

Answer: D

Explanation:
Explanation/Reference: https://cloud.google.com/compute/docs/api/how-tos/authorization


NEW QUESTION # 68
Your application is running in multiple Google Kubernetes Engine clusters. It is managed by a Deployment in each cluster. The Deployment has created multiple replicas of your Pod in each cluster. You want to view the logs sent to stdout for all of the replicas in your Deployment in all clusters.
Which command should you use?

Answer: A

Explanation:
https://cloud.google.com/blog/products/management-tools/using-logging-your-apps-running- kubernetes-engine gcloud command line tool - Using the gcloud logging read command, select the appropriate cluster, node, pod and container logs.


NEW QUESTION # 69
Your development team has built several Cloud Functions using Java along with corresponding integration and service tests. You are building and deploying the functions and launching the tests using Cloud Build.
Your Cloud Build job is reporting deployment failures immediately after successfully validating the code.
What should you do?

Answer: A

Explanation:
Explanation
https://cloud.google.com/build/docs/securing-builds/configure-access-for-cloud-build-service-account


NEW QUESTION # 70
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