Quiz 2026 Efficient Google Professional-Cloud-Developer: Google Certified Professional - Cloud Developer Excellect Pass Rate

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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Weight	Objectives
Integrating applications with Google Cloud services	21%	- 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 - Implementing application performance monitoring 1. Instrumenting code for metrics and traces 2. Using operations suite tools - Consuming Google Cloud APIs and services 1. Integrating with AI/ML and generative AI services 2. Enabling and managing APIs 3. Using client libraries, REST, and gRPC
Designing highly scalable, secure, and reliable cloud-native applications	32%	- Designing high-performing applications and APIs 1. Selecting appropriate compute and deployment platforms 2. Designing for high availability and fault tolerance 3. Optimizing for latency and throughput - 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 - Designing for observability and monitoring 1. Planning logging, metrics, and tracing strategies 2. Designing for debugging and troubleshooting
Building and testing applications	23%	- 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. 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
Configuring cloud-native applications for deployment	24%	- Deploying applications to Google Kubernetes Engine 1. Managing configurations and secrets 2. Creating and managing workloads and services 3. Configuring scaling, auto-scaling, and updates - Deploying applications to Cloud Run 1. Integrating with event-driven services 2. Deploying from source code or containers 3. Configuring scaling, networking, and security - Deploying to App Engine or Cloud Functions 1. Configuring serverless deployments 2. Managing versions and traffic splitting

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Google Certified Professional - Cloud Developer Sample Questions (Q293-Q298):

NEW QUESTION # 293
You need to configure a Deployment on Google Kubernetes Engine (GKE). You want to include a check that verifies that the containers can connect to the database. If the Pod is failing to connect, you want a script on the container to run to complete a graceful shutdown. How should you configure the Deployment?

A. Create the Deployment with a PostStart lifecycle handler that checks the service availability. Configure a PreStop lifecycle handler that runs the shutdown script if the container is failing.
B. Create the Deployment with an initContainer that checks the service availability. Configure a Prestop lifecycle handler that runs the shutdown script if the Pod is failing.
C. Create two jobs: one that checks whether the container can connect to the database, and another that runs the shutdown script if the Pod is failing.
D. Create the Deployment with a livenessProbe for the container that will fail if the container can't connect to the database. Configure a Prestop lifecycle handler that runs the shutdown script if the container is failing.

Answer: D

Explanation:
https://cloud.google.com/architecture/best-practices-for-running-cost-effective-kubernetes-applications-on-gke#make_sure_your_applications_are_shutting_down_in_accordance_with_kubernetes_expectations

NEW QUESTION # 294
You recently migrated a monolithic application to Google Cloud by breaking it down into microservices. One of the microservices is deployed using Cloud Functions. As you modernize the application, you make a change to the API of the service that is backward-incompatible. You need to support both existing callers who use the original API and new callers who use the new API. What should you do?

A. Re-deploy the Cloud Function after making code changes to support the new API. Requests for both versions of the API are fulfilled based on a version identifier included in the call.
B. Leave the original Cloud Function as-is and deploy a second Cloud Function with the new API.
Use a load balancer to distribute calls between the versions.
C. Leave the original Cloud Function as-is and deploy a second Cloud Function that includes only the changed API. Calls are automatically routed to the correct function.
D. Leave the original Cloud Function as-is and deploy a second Cloud Function with the new API.
Use Cloud Endpoints to provide an API gateway that exposes a versioned API.

Answer: D

Explanation:
https://cloud.google.com/endpoints/docs/openapi/versioning-an-api#backwards-incompatible When you make changes to your API that breaks your customers' client code, as a best practice, increment the major version number of your API. Endpoints can run more than one major version of an API concurrently. By providing both versions of the API, your customers can pick which version they want to use and control when they migrate to the new version.

NEW QUESTION # 295
You are developing a dashboard that aggregates temperature readings from thousands of IoT devices monitoring a city's ambient temperature. You expect a large amount of viewing traffic resulting in a large amount of data egress once the dashboard is live. The dashboard temperature display data doesn't need to be real-time and can tolerate a few seconds of lag. You decide to deploy Memorystore for Redis as the storage backend. You want to ensure that the dashboard will be highly available. How should you configure the service in Memorystore for Redis?

A. Set up Serverless VPC Access to avoid receiving traffic over the internet.
B. Configure Memorystore to use read replicas.
C. Use Private Service Access to enable low-latency network throughput.
D. Update Memorystore for Redis to the latest version.

Answer: B

Explanation:
Using read replicas in Memorystore for Redis enhances availability by providing redundancy. If the primary instance experiences downtime, read replicas can continue serving requests, ensuring that the dashboard remains accessible. Read replicas also help distribute read traffic, which can be beneficial for high-demand applications, even though Redis itself is an in-memory store with fast access.
- Updating to the latest version may improve performance or security but does not directly improve availability.
- Private Service Access and Serverless VPC Access are network configurations that reduce latency and secure connections but do not inherently improve availability.

NEW QUESTION # 296
You are designing a deployment technique for your new applications on Google Cloud. As part of your deployment planning, you want to use live traffic to gather performance metrics for both new and existing applications. You need to test against the full production load prior to launch. What should you do?

A. Use A/B testing with traffic mirroring during deployment
B. Use blue/green deployment
C. Use rolling updates deployment
D. Use canary deployment

Answer: D

Explanation:
Reference: https://cloud.google.com/architecture/application-deployment-and-testing-strategies

NEW QUESTION # 297
You are developing an HTTP API hosted on a Compute Engine virtual machine instance that needs to be invoked by multiple clients within the same Virtual Private Cloud (VPC). You want clients to be able to get the IP address of the service.
What should you do?

A. Reserve a static external IP address and assign it to an HTTP(S) load balancing service's forwarding rule.
Clients should use this IP address to connect to the service.
B. Ensure that clients use Compute Engine internal DNS by connecting to the instance name with the url
https://[INSTANCE_NAME].[ZONE].c.[PROJECT_ID].internal/.
C. Ensure that clients use Compute Engine internal DNS by connecting to the instance name with the url
https://[API_NAME]/[API_VERSION]/.
D. Reserve a static external IP address and assign it to an HTTP(S) load balancing service's forwarding rule.
Then, define an A record in Cloud DNS. Clients should use the name of the A record to connect to the service.

Answer: C

NEW QUESTION # 298
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