Professional-Cloud-Developer Exam Fee, Relevant Professional-Cloud-Developer Questions

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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. 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. Configuring scaling, auto-scaling, and updates 3. Managing configurations and secrets - Deploying to App Engine or Cloud Functions 1. Configuring serverless deployments 2. Managing versions and traffic splitting
Topic 2: Designing highly scalable, secure, and reliable cloud-native applications	32%	- Designing high-performing applications and APIs 1. Optimizing for latency and throughput 2. Selecting appropriate compute and deployment platforms 3. Designing for high availability and fault tolerance - 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
Topic 3: Building and testing applications	23%	- Testing applications 1. Automating testing in CI/CD workflows 2. Writing unit, integration, and end-to-end tests 3. Using AI-assisted development tools - 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. Emulating Google Cloud services locally 2. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations
Topic 4: Integrating applications with Google Cloud services	21%	- 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. Implementing messaging and event streaming 2. Using object storage and file storage solutions 3. Working with relational, NoSQL, and in-memory databases

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Google Certified Professional - Cloud Developer Sample Questions (Q57-Q62):

NEW QUESTION # 57
Case Study
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.
Which service should HipLocal use to enable access to internal apps?

A. Virtual Private Cloud
B. Cloud Armor
C. Cloud VPN
D. Cloud Identity-Aware Proxy

Answer: D

Explanation:
Explanation/Reference: https://cloud.google.com/iap/docs/cloud-iap-for-on-prem-apps-overview

NEW QUESTION # 58
You are trying to connect to your Google Kubernetes Engine (GKE) cluster using kubectl from Cloud Shell.
You have deployed your GKE cluster with a public endpoint. From Cloud Shell, you run the following command:

You notice that the kubectl commands time out without returning an error message. What is the most likely cause of this issue?

A. The Cloud Shell is not part of the same VPC as the GKE cluster.
B. A VPC firewall is blocking access to the cluster's endpoint.
C. Your Cloud Shell external IP address is not part of the authorized networks of the cluster.
D. Your user account does not have privileges to interact with the cluster using kubectl.

Answer: C

Explanation:
Explanation
https://cloud.google.com/kubernetes-engine/docs/how-to/private-clusters#cloud_shell If you want to use Cloud Shell to access the cluster, you must add the public IP address of your Cloud Shell to the cluster's list of authorized networks.

NEW QUESTION # 59
You are a developer at a large organization. You are deploying a web application to Google Kubernetes Engine (GKE). The DevOps team has built a CI/CD pipeline that uses Cloud Deploy to deploy the application to Dev Test, and Prod clusters in GKE. After Cloud Deploy successfully deploys the application to the Dev cluster you want to automatically promote it to the Test Cluster. How should you configure this process following Google-recommended best practices?

A. 1 Create a Cloud Build pipeline that uses the gke-deploy builder
2 Create a Cloud Build trigger that listens to SUCCEEDED Pub/Sub messages from the cloud-builds topic
3 Configure this pipeline to run a deployment step to the Test cluster
B. 1 Create a Cloud Function that calls the Google Cloud Deploy API to promote the application to the Test cluster
2 Configure this function to be triggered by SUCCEEDED Pub/Sub messages from the cloud-builds topic
C. 1 Create a Cloud Build trigger that listens for SUCCEEDED Pub/Sub messages from the clouddeploy-operations topic.
2 Configure Cloud Build to include a step that promotes the application to the Test cluster
D. 1 Create a Cloud Function that calls the Google Cloud Deploy API to promote the application to the Test cluster
2 Configure this function to be triggered by SUCCEEDED Pub/Sub messages from the clouddeploy operations topic

Answer: B

NEW QUESTION # 60
You want to use the Stackdriver Logging Agent to send an application's log file to Stackdriver from a Compute Engine virtual machine instance.
After installing the Stackdriver Logging Agent, what should you do first?

A. Configure the application log file as a custom source.
B. Enable the Error Reporting API on the project.
C. Create a Stackdriver Logs Export Sink with a filter that matches the application's log entries.
D. Grant the instance full access to all Cloud APIs.

Answer: D

NEW QUESTION # 61
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 Recreate with maxSurge set to 0, maxUnavailable set to 1.
B. Set the Deployment strategy to RollingUpdate with maxSurge set to 1, maxUnavailable set to 0.
C. Set the Deployment strategy to Recreate with maxSurge set to 1, maxUnavailable set to 0.
D. Set the Deployment strategy to RollingUpdate with maxSurge set to 0, maxUnavailable set to 1.

Answer: C

NEW QUESTION # 62
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