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Google Professional-Cloud-Developer Exam Syllabus Topics:

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

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Google Certified Professional - Cloud Developer Professional-Cloud-Developer Prüfungsfragen mit Lösungen (Q21-Q26):

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

Antwort: B

Begründung:
Include a timestamp as part of your row key if you often need to retrieve data based on the time when it was recorded.
For example, your application might need to record performance-related data, such as CPU and memory usage, once per second for a large number of machines. Your row key for this data could combine an identifier for the machine with a timestamp for the data (for example, machine_4223421#1425330757685). Keep in mind that row keys are sorted lexicographically.
https://cloud.google.com/bigtable/docs/schema-design

22. Frage
You are planning to deploy your application in a Google Kubernetes Engine (GKE) cluster The application exposes an HTTP-based health check at /healthz. You want to use this health check endpoint to determine whether traffic should be routed to the pod by the load balancer.
Which code snippet should you include in your Pod configuration?

A. Option B
B. Option D
C. Option C
D. Option A

Antwort: A

Begründung:
For the GKE ingress controller to use your readinessProbes as health checks, the Pods for an Ingress must exist at the time of Ingress creation. If your replicas are scaled to 0, the default health check will apply.

23. Frage
You are deploying your applications on Compute Engine. One of your Compute Engine instances failed to launch. What should you do? (Choose two.)

A. Troubleshoot firewall rules or routes on an instance.
B. Check whether network traffic to or from your instance is being dropped.
C. Access Compute Engine as a different SSH user.
D. Determine whether your file system is corrupted.
E. Check whether your instance boot disk is completely full.

Antwort: D,E

Begründung:
https://cloud.google.com/compute/docs/troubleshooting/vm-
startup#identify_the_reason_why_the_boot_disk_isnt_booting
- Verify that your boot disk is not full.
If your boot disk is completely full and your operating system does not support automatic resizing, you won't be able to connect to your instance. You must create a new instance and recreate the boot disk.
- Verify that your disk has a valid file system.
If your file system is corrupted or otherwise invalid, you won't be able to launch your instance.

24. Frage
You are developing an application that uses microservices architecture that includes Cloud Run, Bigtable, and Pub/Sub. You want to conduct the testing and debugging process as quickly as possible to create a minimally viable product with minimal cost. What should you do?

A. Use Cloud Code to develop, deploy, and test microservices resources. Use Cloud Logging to review the resource logs.
B. Use Cloud Build to create a pipeline, and add the unit testing stage and the manual approval stage. Deploy the code to your Google Cloud project.
C. Use Cloud Shell Editor and Cloud Shell to deploy the application, and test the functionality by using the Google Cloud console in the project.
D. Use emulators to test the functionality of cloud resources locally, and deploy the code to your Google Cloud project.

Antwort: A

Begründung:
https://cloud.google.com/blog/topics/developers-practitioners/microservices-architecture-google- cloud

25. Frage
You are tasked with using C++ to build and deploy a microservice for an application hosted on Google Cloud.
The code needs to be containerized and use several custom software libraries that your team has built. You do not want to maintain the underlying infrastructure of the application How should you deploy the microservice?

A. Use Cloud Shell to containerize your microservice. and deploy it on a Container-Optimized OS Compute Engine instance.
B. Use Cloud Build to create the container, and deploy it on Cloud Run.
C. Use Cloud Functions to deploy the microservice.
D. Use Cloud Shell to containerize your microservice. and deploy it on GKE Standard.

Antwort: B

26. Frage
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