Professional-Cloud-Architect Deutsche - Professional-Cloud-Architect Prüfungs-Guide

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Google Professional-Cloud-Architect Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Managing implementation	12.5%	- Testing and validating solutions 1. Functional, performance, and security testing 2. Disaster recovery and failover testing - Using Google Cloud tools and APIs programmatically 1. Cloud SDK, Cloud Shell, and Cloud Code 2. Infrastructure as Code (Terraform, Deployment Manager) - Guiding development and deployment teams 1. Application and infrastructure deployment strategies 2. CI/CD pipelines and automation
Topic 2: Designing and planning a cloud solution architecture	25%	- Planning cloud migration and hybrid/multi-cloud environments 1. Interoperability and integration design 2. Migration planning and execution 3. Data transfer and synchronization - Designing cloud solution infrastructure aligned with business requirements 1. Compliance and regulatory requirements consideration 2. Cost optimization strategies 3. Scalability, high availability, and fault tolerance design - Evaluating and selecting Google Cloud services 1. Compute, storage, database, and networking service selection 2. Serverless and managed service adoption
Topic 3: Ensuring solution and operations excellence	12.5%	- Implementing monitoring, logging, and observability 1. Alerting, dashboarding, and root cause analysis 2. Cloud Monitoring, Logging, and Error Reporting - Planning for continuous improvement 1. Feedback loops and optimization cycles 2. Technology updates and architecture evolution - Applying Well-Architected Framework principles 1. Operational excellence, reliability, security, cost, and performance pillars
Topic 4: Managing and provisioning solution infrastructure	15%	- Configuring network topologies and connectivity 1. VPC design, peering, and hybrid connectivity 2. Load balancing and CDN configuration - Provisioning and managing compute resources 1. Auto-scaling and resource management 2. VMs, GKE, App Engine, Cloud Run deployment and management - Managing storage and data services 1. Database deployment, replication, and backup 2. Cloud Storage, Filestore, Persistent Disk management
Topic 5: Analyzing and optimizing technical and business processes	15%	- Streamlining operational workflows 1. Change management and incident response 2. Stakeholder communication and alignment - Optimizing cost and resource efficiency 1. Committed use discounts and pricing models 2. Resource right-sizing and usage monitoring - Improving reliability and performance 1. Latency reduction and throughput optimization 2. SLO, SLA, and error budgeting
Topic 6: Designing for security and compliance	17.5%	- Implementing identity and access management 1. IAM roles, permissions, and service accounts 2. Organizational policies and resource hierarchy - Enforcing compliance and governance 1. VPC Service Controls and security perimeters 2. Security controls, auditing, and logging - Securing data and communications 1. Key management and secret security 2. Encryption at rest and in transit

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Google Certified Professional - Cloud Architect (GCP) Professional-Cloud-Architect Prüfungsfragen mit Lösungen (Q143-Q148):

143. Frage
For this question, refer to the Dress4Win case study.
As part of their new application experience, Dress4Wm allows customers to upload images of themselves.
The customer has exclusive control over who may view these images. Customers should be able to upload images with minimal latency and also be shown their images quickly on the main application page when they log in. Which configuration should Dress4Win use?

A. Store image files in a Google Cloud Storage bucket. Add custom metadata to the uploaded images in Cloud Storage that contains the customer's unique ID.
B. Store image files in a Google Cloud Storage bucket. Use Google Cloud Datastore to maintain metadata that maps each customer's ID and their image files.
C. Use a distributed file system to store customers' images. As storage needs increase, add more persistent disks and/or nodes. Use a Google Cloud SQL database to maintain metadata that maps each customer's ID to their image files.
D. Use a distributed file system to store customers' images. As storage needs increase, add more persistent disks and/or nodes. Assign each customer a unique ID, which sets each file's owner attribute, ensuring privacy of images.

Antwort: B

144. Frage
You deploy your custom Java application to Google App Engine. It fails to deploy and gives you the following stack trace.

What should you do?

A. Upload missing JAR files and redeploy your application.
B. Recompile the CLoakedServlet class using and MD5 hash instead of SHA1
C. Digitally sign all of your JAR files and redeploy your application

Antwort: C

145. Frage
You want to enable your running Google Kubernetes Engine cluster to scale as demand for your application changes.
What should you do?

A. Update the existing Kubernetes Engine cluster with the following command:gcloud alpha container clustersupdate mycluster - -enable-autoscaling - -min-nodes=1 - -max-nodes=10
B. Add a tag to the instances in the cluster with the following command:gcloud compute instances add-tagsINSTANCE - -tags enable-autoscaling max-nodes-10
C. Add additional nodes to your Kubernetes Engine cluster using the following command:gcloud container clusters resizeCLUSTER_Name - -size 10
D. Create a new Kubernetes Engine cluster with the following command:gcloud alpha container clusterscreate mycluster - -enable-autoscaling - -min-nodes=1 - -max-nodes=10and redeploy your application

Antwort: A

Begründung:
https://cloud.google.com/kubernetes-engine/docs/concepts/cluster-autoscaler To enable autoscaling for an existing node pool, run the following command:
gcloud container clusters update [CLUSTER_NAME] --enable-autoscaling \ --min-nodes 1 --max-nodes 10 --zone [COMPUTE_ZONE] --node-pool default-pool

146. Frage
You are managing several projects on Google Cloud and need to interact on a daily basis with BigQuery, Bigtable and Kubernetes Engine using the gcloud CLI tool You are travelling a lot and work on different workstations during the week You want to avoid having to manage the gcloud CLI manually What should you do?

A. Create a Compute Engine instance and install gcloud on the instance Connect to this instance via SSH to always use the same gcloud installation when interacting with Google Cloud
B. Install gcloud on all of your workstations Run the command gcloud components auto-update on each workstation
C. Use Google Cloud Shell in the Google Cloud Console to interact with Google Cloud
D. Use a package manager to install gcloud on your workstations instead of installing it manually

Antwort: C

Begründung:
Explanation
This option allows you to use the gcloud CLI tool without having to install or manage it manually on different workstations. Google Cloud Shell is a browser-based command-line tool that provides you with a temporary Compute Engine virtual machine instance preloaded with the Cloud SDK, including the gcloud CLI tool. You can access Google Cloud Shell from any web browser and use it to interact with BigQuery, Bigtable and Kubernetes Engine using the gcloud CLI tool. The other options are not optimal for this scenario, because they either require installing and updating the gcloud CLI tool on multiple workstations (A, C), or creating and maintaining a Compute Engine instance for the sole purpose of using the gcloud CLI tool (B). References:
https://cloud.google.com/shell/docs/overview
https://cloud.google.com/sdk/gcloud/

147. Frage
For this question, refer to the Dress4Win case study. Considering the given business requirements, how would you automate the deployment of web and transactional data layers?

A. Deploy Nginx and Tomcat using Cloud Launcher. Deploy a MySQL server using Cloud Launcher. Deploy Jenkins to Compute Engine using Cloud Deployment Manager scripts.
B. Migrate Nginx and Tomcat to App Engine. Deploy a MySQL server using Cloud Launcher. Deploy Jenkins to Compute Engine using Cloud Launcher.
C. Deploy Nginx and Tomcat using Cloud Deployment Manager to Compute Engine. Deploy a Cloud SQL server to replace MySQL. Deploy Jenkins using Cloud Deployment Manager.
D. Migrate Nginx and Tomcat to App Engine. Deploy a Cloud Datastore server to replace the MySQL server in a high-availability configuration. Deploy Jenkins to Compute Engine using Cloud Launcher.

Antwort: C

148. Frage
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