Professional-Cloud-Developer VCE Dumps｜Ready to Pass The Google Certified Professional - Cloud Developer

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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 Google Kubernetes Engine 1. Managing configurations and secrets 2. Configuring scaling, auto-scaling, and updates 3. Creating and managing workloads and services - 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
Topic 2: Integrating applications with Google Cloud services	21%	- Integrating with data and storage services 1. Implementing messaging and event streaming 2. Using object storage and file storage solutions 3. Working with relational, NoSQL, and in-memory databases - 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
Topic 3: Building and testing applications	23%	- Building applications and containers 1. Implementing containerization best practices 2. Configuring build pipelines and provenance 3. Using Cloud Build and Artifact Registry - Setting up development environments 1. Emulating Google Cloud services locally 2. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations - Testing applications 1. Writing unit, integration, and end-to-end tests 2. Automating testing in CI/CD workflows 3. Using AI-assisted development tools
Topic 4: Designing highly scalable, secure, and reliable cloud-native applications	32%	- 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. Optimizing for latency and throughput 2. Designing for high availability and fault tolerance 3. Selecting appropriate compute and deployment platforms - Designing for observability and monitoring 1. Designing for debugging and troubleshooting 2. Planning logging, metrics, and tracing strategies

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Google Certified Professional - Cloud Developer Sample Questions (Q168-Q173):

NEW QUESTION # 168
You want to create "fully baked" or "golden" Compute Engine images for your application. You need to bootstrap your application to connect to the appropriate database according to the environment the application is running on (test, staging, production). What should you do?

A. When creating the Compute Engine instance, add a tag with the name of the database to be connected.
In your application, query the Compute Engine API to pull the tags for the current instance, and use the tag to construct the appropriate database connection string.
B. When creating the Compute Engine instance, create a metadata item with a key of "DATABASE" and a value for the appropriate database connection string. In your application, query the metadata server for the "DATABASE" value, and use the value to connect to the appropriate database.
C. When creating the Compute Engine instance, create a metadata item with a key of "DATABASE" and a value for the appropriate database connection string. In your application, read the "DATABASE" environment variable, and use the value to connect to the appropriate database.
D. Embed the appropriate database connection string in the image. Create a different image for each environment.

Answer: B

NEW QUESTION # 169
You configured your Compute Engine instance group to scale automatically according to overall CPU usage.
However, your application's response latency increases sharply before the cluster has finished adding up instances. You want to provide a more consistent latency experience for your end users by changing the configuration of the instance group autoscaler.
Which two configuration changes should you make? (Choose two.)

A. Decrease the target CPU usage for the instance group autoscaler.
B. Remove the health-check for individual VMs in the instance group.
C. Increase the target CPU usage for the instance group autoscaler.
D. Decrease the cool-down period for instances added to the group.
E. Add the label "AUTOSCALE" to the instance group template.

Answer: C,E

NEW QUESTION # 170
You need to load-test a set of REST API endpoints that are deployed to Cloud Run. The API responds to HTTP POST requests. Your load tests must meet the following requirements:
- Load is initiated from multiple parallel threads.
- User traffic to the API originates from multiple source IP addresses.
- Load can be scaled up using additional test instances.
You want to follow Google-recommended best practices. How should you configure the load testing?

A. Download the container image of a distributed load testing framework on Cloud Shell.Sequentially start several instances of the container on Cloud Shell to increase the load on the API.
B. Create an image that has cURL installed, and configure cURL to run a test plan. Deploy the image in a managed instance group, and run one instance of the image for each VM.
C. Create an image that has cURL installed, and configure cURL to run a test plan. Deploy the image in an unmanaged instance group, and run one instance of the image for each VM.
D. Deploy a distributed load testing framework on a private Google Kubernetes Engine cluster.
Deploy additional Pods as needed to initiate more traffic and support the number of concurrent users.

Answer: D

NEW QUESTION # 171
Your company has deployed a new API to a Compute Engine instance. During testing, the API is not behaving as expected. You want to monitor the application over 12 hours to diagnose the problem within the application code without redeploying the application. Which tool should you use?

A. Cloud Debugger logpoints
B. Cloud Trace
C. Cloud Debugger snapshots
D. Cloud Monitoring

Answer: A

Explanation:
https://cloud.google.com/debugger/docs/using/logpoints
Logpoints allow you to inject logging into running services without restarting or interfering with the normal function of the service

NEW QUESTION # 172
You recently deployed an Apigee API proxy to your organization across two regions. Both regions are configured with a separate backend that is hosting the API. You need to configure Apigee to route traffic to the appropriate local region backend. What should you do?

A. Configure a regional internal Application Load Balancer in each region, and use health checks to verify that each backend is active. Create a DNS A record that contains the IP addresses of both regions' load balancers. Configure a TargetServer for each region that uses this DNS name.
B. Configure a TargetServer for each region's backend host names. Configure the API proxy to choose the TargetServer based on the system.region.name flow variable.
C. Configure a global external Application Load Balancer and configure each region's backend with a different regional backend service. Each region communicates to this single global external Application Load Balancer as its TargetServer.
D. Create a TargetEndpoint with a weighted load balancing algorithm. Configure the API proxy to use the same weights for each region's backend.

Answer: B

Explanation:
https://cloud.google.com/apigee/docs/api-platform/reference/api-proxy-configuration-reference

NEW QUESTION # 173
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