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Google Professional-Cloud-Developer Exam Overview:

Certification Vendor:	Google Cloud
Exam Name:	Google Cloud Certified Professional - Cloud Developer Exam
Exam Number:	Professional-Cloud-Developer
Real Exam Qty:	50-60
Available Languages:	Japanese, English
Exam Format:	Multiple choice, Multiple select
Related Certifications:	Google Cloud Certified Professional - Cloud Architect Google Cloud Certified Associate - Cloud Engineer
Exam Duration:	120 minutes
Certificate Validity Period:	2 years
Passing Score:	Not publicly disclosed
Exam Price:	$200 USD (plus tax where applicable)
Recommended Training:	Official Exam Guide Google Cloud Professional Cloud Developer Learning Path
Exam Registration:	Google Cloud Certification Registration
Sample Questions:	Google Professional-Cloud-Developer Sample Questions
Exam Way:	Online-proctored (remote) or onsite-proctored at authorized testing centers
Pre Condition:	No formal prerequisites; recommended: 3+ years industry experience, 1+ year designing/managing Google Cloud solutions
Official Syllabus URL:	https://cloud.google.com/learn/certification/cloud-developer

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Google Certified Professional - Cloud Developer Professional-Cloud-Developer Prüfungsfragen mit Lösungen (Q301-Q306):

301. Frage
Your team is writing a backend application to implement the business logic for an interactive voice response (IVR) system that will support a payroll application. The IVR system has the following technical characteristics:
* Each customer phone call is associated with a unique IVR session.
* The IVR system creates a separate persistent gRPC connection to the backend for each session.
* If the connection is interrupted, the IVR system establishes a new connection, causing a slight latency for that call.
You need to determine which compute environment should be used to deploy the backend application. Using current call data, you determine that:
* Call duration ranges from 1 to 30 minutes.
* Calls are typically made during business hours.
* There are significant spikes of calls around certain known dates (e.g., pay days), or when large payroll changes occur.
You want to minimize cost, effort, and operational overhead. Where should you deploy the backend application?

A. Compute Engine
B. Cloud Run
C. Google Kubernetes Engine cluster in Standard mode
D. Cloud Functions

Antwort: B

Begründung:
This page shows Cloud Run-specific details for developers who want to use gRPC to connect a Cloud Run service with other services, for example, to provide simple, high performance communication between internal microservices. You can use all gRPC types, streaming or unary, with Cloud Run.
Possible use cases include:
Communication between internal microservices.
High loads of data (gRPC uses protocol buffers, which are up to seven times faster than REST calls).
Only a simple service definition is needed, you don't want to write a full client library.
Use streaming gRPCs in your gRPC server to build more responsive applications and APIs.
https://cloud.google.com/run/docs/tutorials/secure-services#:~:text=The%20backend%20service%20is%20private,Google%20Cloud%20except%20where%20necessary.

302. Frage
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. Embed the appropriate database connection string in the image. Create a different image for each environment.
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, query the metadata server for the "DATABASE" value, and use the value to connect to the appropriate database.
D. 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.

Antwort: D

303. Frage
Your analytics system executes queries against a BigQuery dataset. The SQL query is executed in batch and passes the contents of a SQL file to the BigQuery CLI. Then it redirects the BigQuery CLI output to another process. However, you are getting a permission error from the BigQuery CLI when the queries are executed.
You want to resolve the issue. What should you do?

A. Create a new dataset in BigQuery, and copy the source table to the new dataset Query the new dataset and table from the CLI.
B. Grant the service account BigQuery Data Viewer and BigQuery Job User roles.
C. Create a view in BigQuery from the SQL query and SELECT* from the view in the CLI.
D. Grant the service account BigQuery Data Editor and BigQuery Data Viewer roles.

Antwort: B

Begründung:
https://cloud.google.com/bigquery/docs/access-control#bigquery

304. Frage
You are developing a single-player mobile game backend that has unpredictable traffic patterns as users interact with the game throughout the day and night. You want to optimize costs by ensuring that you have enough resources to handle requests, but minimize over-provisioning. You also want the system to handle traffic spikes efficiently. Which compute platform should you use?

A. Compute Engine with managed instance groups
B. Cloud Run
C. Compute Engine with unmanaged instance groups
D. Google Kubernetes Engine using cluster autoscaling

Antwort: B

305. Frage
You plan to deploy a new application revision with a Deployment resource to Google Kubernetes Engine (GKE) in production. The container might not work correctly. You want to minimize risk in case there are issues after deploying the revision. You want to follow Google-recommended best practices. What should you do?

A. Perform a rolling update with a HorizontalPodAutoscaler scale-down policy value of 0.
B. Convert the Deployment to a StatefulSet, and perform a rolling update with a PodDisruptionBudget of
80%.
C. Perform a rolling update with a PodDisruptionBudget of 80%.
D. Convert the Deployment to a StatefulSet, and perform a rolling update with a HorizontalPodAutoscaler scale-down policy value of 0.

Antwort: C

Begründung:
https://cloud.google.com/blog/products/containers-kubernetes/ensuring-reliability-and-uptime-for-your-gke-clust Setting PodDisruptionBudget ensures that your workloads have a sufficient number of replicas, even during maintenance. Using the PDB, you can define a number (or percentage) of pods that can be terminated, even if terminating them brings the current replica count below the desired value. With PDB configured, Kubernetes will drain a node following the configured disruption schedule. New pods will be deployed on other available nodes. This approach ensures Kubernetes schedules workloads in an optimal way while controlling the disruption based on the PDB configuration.
https://blog.knoldus.com/how-to-avoid-outages-in-your-kubernetes-cluster-using-pdb/

306. Frage
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