Professional-Cloud-Developer Prüfungsinformationen & Professional-Cloud-Developer Deutsch

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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Weight	Objectives
Integrating applications with Google Cloud services	21%	- Integrating with data and storage services 1. Using object storage and file storage solutions 2. Working with relational, NoSQL, and in-memory databases 3. Implementing messaging and event streaming - Consuming Google Cloud APIs and services 1. Integrating with AI/ML and generative AI services 2. Using client libraries, REST, and gRPC 3. Enabling and managing APIs - Implementing application performance monitoring 1. Instrumenting code for metrics and traces 2. Using operations suite tools
Building and testing applications	23%	- Building applications and containers 1. Implementing containerization best practices 2. Configuring build pipelines and provenance 3. Using Cloud Build and Artifact Registry - Setting up development environments 1. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations 2. Emulating Google Cloud services locally - Testing applications 1. Using AI-assisted development tools 2. Writing unit, integration, and end-to-end tests 3. Automating testing in CI/CD workflows
Designing highly scalable, secure, and reliable cloud-native applications	32%	- Designing for observability and monitoring 1. Designing for debugging and troubleshooting 2. Planning logging, metrics, and tracing strategies - Designing high-performing applications and APIs 1. Designing for high availability and fault tolerance 2. Optimizing for latency and throughput 3. Selecting appropriate compute and deployment platforms - Designing secure applications 1. Securing data in transit and at rest 2. Implementing authentication and authorization mechanisms 3. Applying security best practices and compliance requirements
Configuring cloud-native applications for deployment	24%	- Deploying applications to Cloud Run 1. Integrating with event-driven services 2. Configuring scaling, networking, and security 3. Deploying from source code or containers - Deploying applications to Google Kubernetes Engine 1. Configuring scaling, auto-scaling, and updates 2. Managing configurations and secrets 3. Creating and managing workloads and services - Deploying to App Engine or Cloud Functions 1. Configuring serverless deployments 2. Managing versions and traffic splitting

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Google Certified Professional - Cloud Developer Professional-Cloud-Developer Prüfungsfragen mit Lösungen (Q232-Q237):

232. Frage
Diego is servicing an embedded battery and it begins to swell. Which of the following is the proper response by Diego?

A. Remove the swelling battery and move it to a fire-proof safety cabinet.
B. Immediately pour sand on the battery to cover it completely.
C. Evacuate the room for fifteen minutes.
D. Wait to see if the battery stops swelling or continues to thermal event.

Antwort: B

233. Frage
You are designing a schema for a table that will be moved from MySQL to Cloud Bigtable. The MySQL table is as follows:

How should you design a row key for Cloud Bigtable for this table?

A. Set Account_id as a key.
B. Set Account_id_Event_timestamp as a key.
C. Set Event_timestamp_Account_id as a key.
D. Set Event_timestamp as a key.

Antwort: C

234. Frage
You migrated your applications to Google Cloud Platform and kept your existing monitoring platform. You now find that your notification system is too slow for time critical problems.
What should you do?

A. Replace your entire monitoring platform with Stackdriver.
B. Install the Stackdriver agents on your Compute Engine instances.
C. Use Stackdriver to capture and alert on logs, then ship them to your existing platform.
D. Migrate some traffic back to your old platform and perform AB testing on the two platforms concurrently.

Antwort: B

Begründung:
Reference:
https://cloud.google.com/monitoring/

235. 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, 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.
B. 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.
C. Embed the appropriate database connection string in the image. Create a different image for each environment.
D. 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.

Antwort: B

Begründung:
https://cloud.google.com/compute/docs/metadata/querying-metadata

236. Frage
You are developing a web application using Cloud Run and Cloud Storage. You are notified of a production issue that you need to troubleshoot immediately. You need to implement a workaround that requires you to execute a script on a Git repository. Your corporate laptop is unavailable but you have your personal computer. You can use your corporate credentials to access the required Git repository and Google Cloud resources. You want to fix the issue as quickly and efficiently as possible while minimizing additional cost. What should you do?

A. Download and install the gcloud CLI on your personal computer. Authenticate and set up API access. Clone the Git repository and execute the workaround script. Ensure that the issue has been fixed.
B. Install VS Code and the extension Cloud Code for VS Code on your personal computer. Check the Cloud Run logs in Cloud Code to confirm the error. Execute the workaround script. Ensure that the issue has been fixed.
C. Connect to the Google Cloud console and open Cloud Shell on your personal computer. Clone the Git repository and execute the workaround script. Ensure that the issue has been fixed.
D. Create and launch a workstation with Cloud Workstations on your personal computer.
Authenticate and set up API access in the workstation. Clone the Git repository and execute the workaround script. Ensure that the issue has been fixed.

Antwort: C

Begründung:
https://cloud.google.com/run/docs/troubleshooting

237. Frage
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