Professional-Cloud-DevOps-Engineer Practice Tests - Valid Professional-Cloud-DevOps-Engineer Test Objectives

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Google Professional-Cloud-DevOps-Engineer Exam Syllabus Topics:

Section	Objectives
Topic 1: Implement site reliability engineering (SRE) practices	- Incident management and postmortems 1. Alerting and on-call practices - Define and manage SLI, SLO, and SLA 1. Error budgets and monitoring strategies
Topic 2: Implement security and compliance	- Compliance and governance 1. Audit logging and policy enforcement - Secure CI/CD pipelines 1. IAM and least privilege access 2. Secret and credential management
Topic 3: Optimize performance and continuous delivery	- Monitoring and observability 1. Performance tuning and feedback loops 2. Cloud Monitoring and Logging - System performance optimization 1. Scaling strategies and load handling
Topic 4: Develop and implement CI/CD pipelines	- Build and manage CI/CD pipelines using Google Cloud tools 1. Artifact repository management 2. Cloud Build pipeline design - Automate build, test, and deployment processes 1. Release management practices 2. Deployment automation strategies

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Valid Professional-Cloud-DevOps-Engineer Test Objectives & Professional-Cloud-DevOps-Engineer Examinations Actual Questions

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q54-Q59):

NEW QUESTION # 54
The new version of your containerized application has been tested and is ready to be deployed to production on Google Kubernetes Engine (GKE) You could not fully load-test the new version in your pre-production environment and you need to ensure that the application does not have performance problems after deployment Your deployment must be automated What should you do?

A. Deploy the application through a continuous delivery pipeline by using canary deployments Use Cloud Monitoring to look for performance issues, and ramp up traffic as supported by the metrics
B. Deploy the application through a continuous delivery pipeline by using blue/green deployments Migrate traffic to the new version of the application and use Cloud Monitoring to look for performance issues
C. Deploy the application by using kubectl and use Config Connector to slowly ramp up traffic between versions. Use Cloud Monitoring to look for performance issues
D. Deploy the application by using kubectl and set the spec. updatestrategy. type field to RollingUpdate Use Cloud Monitoring to look for performance issues, and run the kubectl rollback command if there are any issues.

Answer: A

NEW QUESTION # 55
You are deploying an application that needs to access sensitive information. You need to ensure that this information is encrypted and the risk of exposure is minimal if a breach occurs. What should you do?

A. Store the encryption keys in Cloud Key Management Service (KMS) and rotate the keys frequently
B. Inject the secret at the time of instance creation via an encrypted configuration management system.
C. Leverage a continuous build pipeline that produces multiple versions of the secret for each instance of the application.
D. Integrate the application with a Single sign-on (SSO) system and do not expose secrets to the application

Answer: A

Explanation:
Explanation
https://cloud.google.com/security-key-management

NEW QUESTION # 56
Your company runs an ecommerce website built with JVM-based applications and microservice architecture in Google Kubernetes Engine (GKE) The application load increases during the day and decreases during the night Your operations team has configured the application to run enough Pods to handle the evening peak load You want to automate scaling by only running enough Pods and nodes for the load What should you do?

A. Configure the Horizontal Pod Autoscaler but keep the node pool size static
B. Configure the Horizontal Pod Autoscaler and enable the cluster autoscaler
C. Configure the Vertical Pod Autoscaler and enable the cluster autoscaler
D. Configure the Vertical Pod Autoscaler but keep the node pool size static

Answer: B

Explanation:
The best option for automating scaling by only running enough Pods and nodes for the load is to configure the Horizontal Pod Autoscaler and enable the cluster autoscaler. The Horizontal Pod Autoscaler is a feature that automatically adjusts the number of Pods in a deployment or replica set based on observed CPU utilization or custom metrics. The cluster autoscaler is a feature that automatically adjusts the size of a node pool based on the demand for node capacity. By using both features together, you can ensure that your application runs enough Pods to handle the load, and that your cluster runs enough nodes to host the Pods. This way, you can optimize your resource utilization and cost efficiency.

NEW QUESTION # 57
You are responsible for creating and modifying the Terraform templates that define your Infrastructure. Because two new engineers will also be working on the same code, you need to define a process and adopt a tool that will prevent you from overwriting each other's code. You also want to ensure that you capture all updates in the latest version. What should you do?

A. * Store your code as text files in Google Drive in a defined folder structure that organizes the files.* At the end of each day. confirm that all changes have been captured in the files within the folder structure.* Rename the folder structure with a predefined naming convention that increments the version.
B. * Store your code as text files in Google Drive in a defined folder structure that organizes the files.* At the end of each day, confirm that all changes have been captured in the files within the folder structure and create a new .zip archive with a predefined naming convention.* Upload the .zip archive to a versioned Cloud Storage bucket and accept it as the latest version.
C. * Store your code in a Git-based version control system.* Establish a process that allows developers to merge their own changes at the end of each day.* Package and upload code lo a versioned Cloud Storage bucket as the latest master version.
D. * Store your code in a Git-based version control system.* Establish a process that includes code reviews by peers and unit testing to ensure integrity and functionality before integration of code.* Establish a process where the fully integrated code in the repository becomes the latest master version.

Answer: D

NEW QUESTION # 58
Your company runs services by using multiple globally distributed Google Kubernetes Engine (GKE) clusters Your operations team has set up workload monitoring that uses Prometheus-based tooling for metrics alerts: and generating dashboards This setup does not provide a method to view metrics globally across all clusters You need to implement a scalable solution to support global Prometheus querying and minimize management overhead What should you do?

A. Configure Google Cloud Managed Service for Prometheus
B. Configure Prometheus hierarchical federation for centralized data access
C. Configure Prometheus cross-service federation for centralized data access
D. Configure workload metrics within Cloud Operations for GKE

Answer: A

NEW QUESTION # 59
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