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| Section | Weight | Objectives |
|---|
| Building and testing applications | 23% | - Testing applications
- 1. Writing unit, integration, and end-to-end tests
- 2. Using AI-assisted development tools
- 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
- Building applications and containers
- 1. Configuring build pipelines and provenance
- 2. Using Cloud Build and Artifact Registry
- 3. Implementing containerization best practices
|
| Configuring cloud-native applications for deployment | 24% | - Deploying to App Engine or Cloud Functions
- 1. Managing versions and traffic splitting
- 2. Configuring serverless deployments
- 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 applications to Google Kubernetes Engine
- 1. Creating and managing workloads and services
- 2. Managing configurations and secrets
- 3. Configuring scaling, auto-scaling, and updates
|
| 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. Securing data in transit and at rest
- 2. Applying security best practices and compliance requirements
- 3. Implementing authentication and authorization mechanisms
- 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
|
| Integrating applications with Google Cloud services | 21% | - 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. 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
|
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Google Certified Professional - Cloud Developer Sample Questions (Q74-Q79):
NEW QUESTION # 74
Case Study 1 - HipLocal
Company 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 10000 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.
HipLocal's .net-based auth service fails under intermittent load.
What should they do?
- A. Use a Compute Engine cluster for the service.
- B. Use Cloud Functions for autoscaling.
- C. Use App Engine for autoscaling.
- D. Use a dedicated Compute Engine virtual machine instance for the service.
Answer: C
Explanation:
https://cloud.google.com/appengine/docs/flexible/dotnet/how-instances-are-managed Automatic scaling creates instances based on request rate, response latencies, and other application metrics. You can specify thresholds for each of these metrics, as well as a minimum number instances to keep running at all times.
NEW QUESTION # 75
You are developing an application that will handle requests from end users. You need to secure a Cloud Function called by the application to allow authorized end users to authenticate to the function via the application while restricting access to unauthorized users. You will integrate Google Sign-In as part of the solution and want to follow Google-recommended best practices.
What should you do?
- A. Deploy from your local machine using gcloud and grant users the roles/cloudfunctions.admin role
- B. Deploy from your local machine using gcloud and grant users the roles/cloudfunctions.developer role
- C. Deploy from a source code repository and grant users the roles/cloudfunctions.viewer role.
- D. Deploy from a source code repository and grant users the roles/cloudfunctions.invoker role
Answer: D
Explanation:
Have the user account you are using to access Cloud Functions assigned a role that contains the cloudfunctions.functions.invoke permission. By default, the Cloud Functions Admin and Cloud Functions Developer roles have this permission. See Cloud Functions IAM Roles for the full list of roles and their associated permissions.
NEW QUESTION # 76
Your application is deployed in a Google Kubernetes Engine (GKE) cluster. When a new version of your application is released, your CI/CD tool updates the spec.template.spec.containers[0].image value to reference the Docker image of your new application version. When the Deployment object applies the change, you want to deploy at least 1 replica of the new version and maintain the previous replicas until the new replica is healthy.
Which change should you make to the GKE Deployment object shown below?

- A. Set the Deployment strategy to RollingUpdate with maxSurge set to 1, maxUnavailable set to 0.
- B. Set the Deployment strategy to RollingUpdate with maxSurge set to 0, maxUnavailable set to 1.
- C. Set the Deployment strategy to Recreate with maxSurge set to 0, maxUnavailable set to 1.
- D. Set the Deployment strategy to Recreate with maxSurge set to 1, maxUnavailable set to 0.
Answer: D
NEW QUESTION # 77
You are designing a chat room application that will host multiple rooms and retain the message history for each room. You have selected Firestore as your database. How should you represent the data in Firestore?
- A. Create a collection for the rooms, and create a document for each room. Create a separate collection for messages, with one document per message. Each room's document contains a list of references to the messages.

- B. Create a collection for the rooms. For each room, create a collection that contains a document for each message

- C. Create a collection for the rooms. For each room, create a document that contains a collection for documents, each of which contains a message.

- D. Create a collection for the rooms. For each room, create a document that lists the contents of the messages

Answer: C
Explanation:
https://firebase.google.com/docs/firestore/data-model#hierarchical-data
NEW QUESTION # 78
Your team manages a Google Kubernetes Engine (GKE) cluster where an application is running. A different team is planning to integrate with this application. Before they start the integration, you need to ensure that the other team cannot make changes to your application, but they can deploy the integration on GKE. What should you do?
- A. Create a new namespace in the existing cluster. Using Kubernetes role-based access control (RBAC), grant the Admin role on the new namespace to the other team.
- B. Create a new GKE cluster. Using Identity and Access Management (IAM), grant the Editor role on the cluster project to the other team.
- C. Using Identity and Access Management (IAM), grant the Viewer IAM role on the cluster project to the other team.
- D. Create a new namespace in the existing cluster. Using Identity and Access Management (IAM), grant the Editor role on the cluster project to the other team.
Answer: A
NEW QUESTION # 79
......
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