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Um ein Google Certified Professional - Cloud Architect zu werden, müssen die Kandidaten die GCP -Zertifizierungsprüfung bestehen. Die Prüfung besteht aus Multiple-Choice-Fragen und wird online geliefert. Die Kandidaten haben zwei Stunden Zeit, um die Prüfung abzuschließen, und sie müssen mindestens 70% erzielen, um zu bestehen. Die Prüfungsgebühr beträgt 200 USD, und es wird empfohlen, dass die Kandidaten vor der Prüfung mindestens drei Jahre Branchenerfahrung haben.

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Die Prüfung besteht aus Fragen mit Mehrfachauswahl und Szenariobasierten Fragen und ist darauf ausgelegt, das Wissen und die Fähigkeiten des Kandidaten in verschiedenen Bereichen zu testen, wie zum Beispiel: Design und Planung einer Cloud-Lösungsarchitektur, Verwaltung und Bereitstellung einer Cloud-Infrastruktur, Optimierung von Cloud-Lösungen für Kosten und Leistung sowie Sicherheit und Compliance von Cloud-Lösungen.

Google Certified Professional - Cloud Architect (GCP) Professional-Cloud-Architect Prüfungsfragen mit Lösungen (Q340-Q345):

340. Frage
You deploy your custom java application to google app engine.
It fails to deploy and gives you the following stack trace:

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

Antwort: B

341. Frage
Refer to the Altostrat Media case study for the following solution regarding the performance analysis of their media processing pipeline.
Altostrat needs to analyze the performance of its media processing pipeline running on Java-based Cloud Run function. You need to select the most effective tool for the task. What should you do?

A. Inspect data from Snapshot Debugger.
B. Query logs in Cloud Logging.
C. Instrument the code to use Cloud Trace.
D. Analyze the data via Cloud Profiler.

Antwort: D

Begründung:
According to Google Cloud documentation on Application Performance Management (APM) , Cloud Profiler is the most effective tool for identifying resource-intensive parts of an application ' s source code.
For Altostrat ' s Java-based media processing pipeline, which likely involves CPU-intensive tasks such as metadata extraction or transcoding, understanding exactly which methods or lines of code consume the most CPU or memory is critical.
Cloud Profiler is a statistical, low-overhead profiler that continuously gathers performance data (CPU usage, heap allocation, etc.) from production applications with less than 0.5% impact on performance. It presents this data in an interactive flame graph , allowing developers to pinpoint bottlenecks in the media processing logic.
While Cloud Trace (Option C) is excellent for monitoring latency across distributed services, it primarily tracks the " outer shell " of the request-showing how long a function took to execute or how long an external API call lasted-but does not provide the deep, code-level insight into internal Java method execution that Profiler does. Cloud Logging (Option A) is useful for troubleshooting specific events but is not a performance analysis tool, and Snapshot Debugger (Option D) is designed for inspecting variables at specific execution points rather than aggregate performance profiling. Given Altostrat ' s goal to " Optimize cloud storage costs " and " Accelerate... operational workflows, " using Cloud Profiler to create more efficient, less resource-hungry processing code is the architecturally sound choice.

342. Frage
To reduce costs, the Director of Engineering has required all developers to move their development infrastructure resources from on-premises virtual machines (VMs) to Google Cloud Platform. These resources go through multiple start/stop events during the day and require state to persist. You have been asked to design the process of running a development environment in Google Cloud while providing cost visibility to the finance department.
Which two steps should you take? Choose 2 answers.

A. Use the - -no-auto-delete flag on all persistent disks and stop the VM
B. Store all state in Google Cloud Storage, snapshot the persistent disks, and terminate the VM
C. Apply VM CPU utilization label and include it in the BigQuery billing export
D. Store all state into local SSD, snapshot the persistent disks, and terminate the VM
E. Use the - -auto-delete flag on all persistent disks and terminate the VM
F. Use Google BigQuery billing export and labels to associate cost to groups

Antwort: C,D

Begründung:
C: Billing export to BigQuery enables you to export your daily usage and cost estimates automatically throughout the day to a BigQuery dataset you specify.
Labels applied to resources that generate usage metrics are forwarded to the billing system so that you can break down your billing charges based upon label criteria. For example, the Compute Engine service reports metrics on VM instances. If you deploy a project with 2,000 VMs, each of which is labeled distinctly, then only the first 1,000 label maps seen within the 1 hour window will be preserved.
E: You cannot stop an instance that has a local SSD attached. Instead, you must migrate your critical data off of the local SSD to a persistent disk or to another instance before you delete the instance completely.
You can stop an instance temporarily so you can come back to it at a later time. A stopped instance does not incur charges, but all of the resources that are attached to the instance will still be charged. Alternatively, if you are done using an instance, delete the instance and its resources to stop incurring charges.
Reference:
https://cloud.google.com/billing/docs/how-to/export-data-bigquery
https://cloud.google.com/compute/docs/instances/stopping-or-deleting-an-instance

343. Frage
For this question, refer to the TerramEarth case study
Your development team has created a structured API to retrieve vehicle data. They want to allow third parties to develop tools for dealerships that use this vehicle event data. You want to support delegated authorization against this data. What should you do?

A. Build or leverage an OAuth-compatible access control system.
B. Build SAML 2.0 SSO compatibility into your authentication system.
C. Create secondary credentials for each dealer that can be given to the trusted third party.
D. Restrict data access based on the source IP address of the partner systems.

Antwort: A

Begründung:
Explanation
https://cloud.google.com/appengine/docs/flexible/go/authorizing-apps
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations#delegate_application_autho Delegate application authorization with OAuth2 Cloud Platform APIs support OAuth 2.0, and scopes provide granular authorization over the methods that are supported. Cloud Platform supports both service-account and user-account OAuth, also called three-legged OAuth.
References:
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations#delegate_application_autho
https://cloud.google.com/appengine/docs/flexible/go/authorizing-apps
Topic 2, Mountkirk Games Case Study
Company Overview
Mountkirk Games makes online, session-based. multiplayer games for the most popular mobile platforms.
Company Background
Mountkirk Games builds all of their games with some server-side integration and has historically used cloud providers to lease physical servers. A few of their games were more popular than expected, and they had problems scaling their application servers, MySQL databases, and analytics tools.
Mountkirk's current model is to write game statistics to files and send them through an ETL tool that loads them into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics and take advantage of its autoscaling server environment and integrate with a managed NoSQL database.
Technical Requirements
Requirements for Game Backend Platform
1. Dynamically scale up or down based on game activity.
2. Connect to a managed NoSQL database service.
3. Run customized Linx distro.
Requirements for Game Analytics Platform
1. Dynamically scale up or down based on game activity.
2. Process incoming data on the fly directly from the game servers.
3. Process data that arrives late because of slow mobile networks.
4. Allow SQL queries to access at least 10 TB of historical data.
5. Process files that are regularly uploaded by users' mobile devices.
6. Use only fully managed services
CEO Statement
Our last successful game did not scale well with our previous cloud provider, resuming in lower user adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs) to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into usage patterns so we can adapt the gams to target users.
CTO Statement
Our current technology stack cannot provide the scale we need, so we want to replace MySQL and move to an environment that provides autoscaling, low latency load balancing, and frees us up from managing physical servers.
CFO Statement
We are not capturing enough user demographic data usage metrics, and other KPIs. As a result, we do not engage the right users. We are not confident that our marketing is targeting the right users, and we are not selling enough premium Blast-Ups inside the games, which dramatically impacts our revenue.

344. Frage
Your organization requires that metrics from all applications be retained for 5 years for future analysis in possible legal proceedings. Which approach should you use?

A. Configure Stackdriver Monitoring for all Projects, and export to BigQuery.
B. Configure Stackdriver Monitoring for all Projects with the default retention policies.
C. Grant the security team access to the logs in each Project.
D. Configure Stackdriver Monitoring for all Projects, and export to Google Cloud Storage.

Antwort: D

Begründung:
https://cloud.google.com/monitoring/api/v3/metrics

345. Frage
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