Professional-Cloud-Developer Exam Lab Questions | Visual Professional-Cloud-Developer Cert Exam

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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Configuring cloud-native applications for deployment	24%	- Deploying applications to Cloud Run 1. Integrating with event-driven services 2. Configuring scaling, networking, and security 3. Deploying from source code or containers - 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 - Deploying to App Engine or Cloud Functions 1. Managing versions and traffic splitting 2. Configuring serverless deployments
Topic 2: Building and testing applications	23%	- Testing applications 1. Using AI-assisted development tools 2. Automating testing in CI/CD workflows 3. Writing unit, integration, and end-to-end tests - Building applications and containers 1. Configuring build pipelines and provenance 2. Using Cloud Build and Artifact Registry 3. Implementing containerization best practices - Setting up development environments 1. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations 2. Emulating Google Cloud services locally
Topic 3: Integrating applications with Google Cloud services	21%	- Implementing application performance monitoring 1. Instrumenting code for metrics and traces 2. Using operations suite tools - 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. Working with relational, NoSQL, and in-memory databases 2. Using object storage and file storage solutions 3. Implementing messaging and event streaming
Topic 4: Designing highly scalable, secure, and reliable cloud-native applications	32%	- Designing high-performing applications and APIs 1. Designing for high availability and fault tolerance 2. Optimizing for latency and throughput 3. Selecting appropriate compute and deployment platforms - 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

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Google Certified Professional - Cloud Developer Sample Questions (Q278-Q283):

NEW QUESTION # 278
You have a web application that publishes messages to Pub/Sub. You plan to build new versions of the application locally and want to quickly test Pub/Sub integration for each new build. How should you configure local testing?

A. Install Cloud Code on the integrated development environment (IDE). Navigate to Cloud APIs, and enable Pub/Sub against a valid Google Project ID. When developing locally, configure your application to call pubsub.googleapis.com.
B. Install the Pub/Sub emulator using gcloud, and start the emulator with a valid Google Project IWhen developing locally, configure your application to use the local emulator by exporting the PUBSUB_EMULATOR_HOST variable.
C. Install the Pub/Sub emulator using gcloud, and start the emulator with a valid Google Project ID.
When developing locally, configure your application to use the local emulator with ${gcloud beta emulators pubsub env-init}.
D. In the Google Cloud console, navigate to the API Library, and enable the Pub/Sub API. When developing locally, configure your application to call pubsub.googleapis.com.

Answer: C

Explanation:
https://cloud.google.com/pubsub/docs/emulator#automatically_setting_the_variables You can run gcloud beta emulators pubsub env-init in your own localhost within if your application and the emulator run on the same machine.

NEW QUESTION # 279
You are deploying a microservices application to Google Kubernetes Engine (GKE). The application will receive daily updates. You expect to deploy a large number of distinct containers that will run on the Linux operating system (OS). You want to be alerted to any known OS vulnerabilities in the new containers. You want to follow Google-recommended best practices.
What should you do?

A. Enable Container Analysis, and upload new container images to Artifact Registry. Review the vulnerability results before each deployment.
B. Use the Container Analysis REST API to call Container Analysis to scan new container images.Review the vulnerability results before each deployment.
C. Enable Container Analysis, and upload new container images to Artifact Registry. Review the critical vulnerability results before each deployment.
D. Use the gcloud CLI to call Container Analysis to scan new container images. Review the vulnerability results before each deployment.

Answer: A

Explanation:
Container Analysis is a service that provides vulnerability scanning and metadata storage for containers. The scanning service performs vulnerability scans on images in Container Registry and Artifact Registry, then stores the resulting metadata and makes it available for consumption through an API. Metadata storage allows storing information from different sources, including vulnerability scanning, other Google Cloud services, and third-party providers.
https://cloud.google.com/container-analysis/docs/container-analysis

NEW QUESTION # 280
You are building a new API. You want to minimize the cost of storing and reduce the latency of serving images.
Which architecture should you use?

A. App Engine backed by Cloud Storage
B. Compute Engine backed by Persistent Disk
C. Transfer Appliance backed by Cloud Filestore
D. Cloud Content Delivery Network (CDN) backed by Cloud Storage

Answer: D

Explanation:
D seems more suitable as Cloud Storage has low cost and CDN provides low serving latency.

NEW QUESTION # 281
You are working on a new application that is deployed on Cloud Run and uses Cloud Functions.
Each time new features are added, new Cloud Functions and Cloud Run services are deployed.
You use ENV variables to keep track of the services and enable interservice communication, but the maintenance of the ENV variables has become difficult. You want to implement dynamic discovery in a scalable way. What should you do?

A. Configure your microservices to use the Cloud Run Admin and Cloud Functions APIs to query for deployed Cloud Run services and Cloud Functions in the Google Cloud project.
B. Deploy Hashicorp Consul on a single Compute Engine instance. Register the services with Consul during deployment, and query during runtime.
C. Create a Service Directory namespace. Use API calls to register the services during deployment, and query during runtime.
D. Rename the Cloud Functions and Cloud Run services endpoint is using a well-documented naming convention.

Answer: C

Explanation:
https://cloud.google.com/service-directory/docs/overview

NEW QUESTION # 282
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?

A. gcloud compute instances add-tags ${NAME}-backend-instance-1 --tags http-server
B. gcloud compute instances add-access-config ${NAME}-backend-instance-1
C. gcloud compute firewall-rules create allow-lb --network load-balancer --allow tcp --source-ranges 130.211.0.0/22,35.191.0.0/16 --direction INGRESS
D. gcloud compute firewall-rules create allow-lb --network load-balancer --allow tcp --destination-ranges 130.211.0.0/22,35.191.0.0/16 --direction EGRESS

Answer: C

Explanation:
Reference: https://cloud.google.com/vpc/docs/special-configurations

NEW QUESTION # 283
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