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Google Professional-Cloud-Developer Exam Syllabus Topics:

SectionWeightObjectives
Configuring cloud-native applications for deployment24%- Deploying applications to Cloud Run
  • 1. Configuring scaling, networking, and security
  • 2. Integrating with event-driven services
  • 3. Deploying from source code or containers
- Deploying to App Engine or Cloud Functions
  • 1. Configuring serverless deployments
  • 2. Managing versions and traffic splitting
- Deploying applications to Google Kubernetes Engine
  • 1. Managing configurations and secrets
  • 2. Configuring scaling, auto-scaling, and updates
  • 3. Creating and managing workloads and services
Designing highly scalable, secure, and reliable cloud-native applications32%- 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. Optimizing for latency and throughput
  • 3. Designing for high availability and fault tolerance
- Designing for observability and monitoring
  • 1. Designing for debugging and troubleshooting
  • 2. Planning logging, metrics, and tracing strategies
Integrating applications with Google Cloud services21%- Consuming Google Cloud APIs and services
  • 1. Using client libraries, REST, and gRPC
  • 2. Enabling and managing APIs
  • 3. Integrating with AI/ML and generative AI services
- Implementing application performance monitoring
  • 1. Instrumenting code for metrics and traces
  • 2. Using operations suite tools
- 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
Building and testing applications23%- Building applications and containers
  • 1. Configuring build pipelines and provenance
  • 2. Implementing containerization best practices
  • 3. Using Cloud Build and Artifact Registry
- 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 (Q391-Q396):

NEW QUESTION # 391
You have a container deployed on Google Kubernetes Engine. The container can sometimes be slow to launch, so you have implemented a liveness probe. You notice that the liveness probe occasionally fails on launch. What should you do?

Answer: A

Explanation:
https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-readiness-startup-probes/#configure-probes


NEW QUESTION # 392
You are developing a new web application using Cloud Run and committing code to Cloud Source Repositories. You want to deploy new code in the most efficient way possible. You have already created a Cloud Build YAML file that builds a container and runs the following command: gcloud run deploy. What should you do next?

Answer: D

Explanation:
https://cloud.google.com/build/docs/triggers
Cloud Build uses build triggers to enable CI/CD automation. You can configure triggers to listen for incoming events, such as when a new commit is pushed to a repository or when a pull request is initiated, and then automatically execute a build when new events come in. You can also configure triggers to build code on any changes to your source repository or only on changes that match certain criteria.


NEW QUESTION # 393
Your application takes an input from a user and publishes it to the user's contacts. This input is stored in a table in Cloud Spanner. Your application is more sensitive to latency and less sensitive to consistency.
How should you perform reads from Cloud Spanner for this application?

Answer: D

Explanation:
Reference: https://cloud.google.com/solutions/best-practices-cloud-spanner-gaming-database
Topic 1, HipLocal Case StudyCompany Overview
HipLocal is a community application designed to facilitate communication between people in close proximity.
It is used for event planning and organizing sporting events, and for businesses to connect with their local communities. HipLocal launched recently in a few neighborhoods in Dallas and is rapidly growing into a global phenomenon. Its unique style of hyper-local community communication and business outreach is in demand around the world.
Executive statement
We are the number one local community app; it's time to take our local community services global. Our venture capital investors want to see rapid growth and the same great experience for new local and virtual communities that come online, whether their members are 10 or 10,000 miles away from each other.
Solution concept
HipLocal wants to expand their existing service, with updated functionality, in new regions to better serve their global customers. They want to hire and train a new team to support these regions in their time zones.
They will need to ensure that the application scales smoothly and provides clear uptime data.
Existing technical environment
HipLocal's environment is a mix of on-premises hardware and infrastructure running in Google Cloud Platform. The HipLocal team understands their application well but has limited experience in global scale applications. Their existing technical environment is as follows:
* Existing APIs run on Compute Engine virtual machine instances hosted in GCP
* State is stored in a single instance MySQL database in GCP
* Data is exported to an on-premises Teradata/Vertica data warehouse
* Data analytics is performed in an on-premises Hadoop environment
* The application has no logging
* There are basic indicators of uptime; alerts are frequently fired when the APIs are unresponsive Business requirements HipLocal's investors want to expand their footprint and support the increase in demand they are seeing. Their requirements are:
* Expand availability of the application to new regions
* Increase the number of concurrent users that can be supported
* Ensure a consistent experience for users when they travel to different regions
* Obtain user activity metrics to better understand how to monetize their product
* Ensure compliance with regulations in the new regions (for example, GDPR)
* Reduce infrastructure management time and cost
* Adopt the Google-recommended practices for cloud computing
Technical requirements
* The application and backend must provide usage metrics and monitoring
* APIs require strong authentication and authorization
* Logging must be increased, and data should be stored in a cloud analytics platform
* Move to serverless architecture to facilitate elastic scaling
* Provide authorized access to internal apps in a secure manner


NEW QUESTION # 394
Tony would like to create a new Apple ID to use with iTunes. It is his preference not to give his credit card information.
Which of the following is the correct statement about his situation?

Answer: A

Explanation:
Explanation/Reference: https://support.apple.com/en-us/HT204034


NEW QUESTION # 395
You have deployed an HTTP(s) Load Balancer with the gcloud commands shown below.

Health checks to port 80 on the Compute Engine virtual machine instance are failing and no traffic is sent to your instances. You want to resolve the problem.
Which commands should you run?

Answer: D


NEW QUESTION # 396
......

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