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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Building and testing applications	23%	- Setting up development environments 1. Emulating Google Cloud services locally 2. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations - Testing applications 1. Automating testing in CI/CD workflows 2. Writing unit, integration, and end-to-end tests 3. Using AI-assisted development tools - Building applications and containers 1. Configuring build pipelines and provenance 2. Using Cloud Build and Artifact Registry 3. Implementing containerization best practices
Topic 2: Configuring cloud-native applications for deployment	24%	- 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 - Deploying applications to Cloud Run 1. Deploying from source code or containers 2. Integrating with event-driven services 3. Configuring scaling, networking, and security
Topic 3: 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. Optimizing for latency and throughput 2. Designing for high availability and fault tolerance 3. Selecting appropriate compute and deployment platforms - Designing secure applications 1. Implementing authentication and authorization mechanisms 2. Applying security best practices and compliance requirements 3. Securing data in transit and at rest
Topic 4: Integrating applications with Google Cloud services	21%	- Implementing application performance monitoring 1. Using operations suite tools 2. Instrumenting code for metrics and traces - Integrating with data and storage services 1. Working with relational, NoSQL, and in-memory databases 2. Implementing messaging and event streaming 3. Using object storage and file storage solutions - Consuming Google Cloud APIs and services 1. Enabling and managing APIs 2. Integrating with AI/ML and generative AI services 3. Using client libraries, REST, and gRPC

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Google Certified Professional - Cloud Developer Sample Questions (Q216-Q221):

NEW QUESTION # 216
You are developing a web application that contains private images and videos stored in a Cloud Storage bucket. Your users are anonymous and do not have Google Accounts. You want to use your application-specific logic to control access to the images and videos. How should you configure access?

A. Cache each web application user's IP address to create a named IP table using Google Cloud Armor.
Create a Google Cloud Armor security policy that allows users to access the backend bucket.
B. Generate a signed URL that grants read access to the bucket. Allow users to access the URL after authenticating through your web application.
C. Configure Identity-Aware Proxy (IAP) to authenticate users into the web application. Allow users to access the bucket after authenticating through IAP.
D. Grant the Storage Object Viewer IAM role to allUsers. Allow users to access the bucket after authenticating through your web application.

Answer: B

Explanation:
https://cloud.google.com/storage/docs/access-control/signed-urls#should-you-use In some scenarios, you might not want to require your users to have a Google account in order to access Cloud Storage, but you still want to control access using your application-specific logic. The typical way to address this use case is to provide a signed URL to a user, which gives the user read, write, or delete access to that resource for a limited time. You specify an expiration time when you create the signed URL. Anyone who knows the URL can access the resource until the expiration time for the URL is reached or the key used to sign the URL is rotated.

NEW QUESTION # 217
Your development team has been tasked with maintaining a .NET legacy application. The application incurs occasional changes and was recently updated. Your goal is to ensure that the application provides consistent results while moving through the CI/CD pipeline from environment to environment. You want to minimize the cost of deployment while making sure that external factors and dependencies between hosting environments are not problematic. Containers are not yet approved in your organization. What should you do?

A. Use Cloud Build to deploy the application as a new Compute Engine image for each build. Use this image in each environment.
B. Rewrite the application using .NET Core, and deploy to Cloud Run. Use revisions to separate the environments.
C. Deploy the application using MS Web Deploy, and make sure to always use the latest, patched MS Windows Server base image in Compute Engine.
D. Use Cloud Build to package the application, and deploy to a Google Kubernetes Engine cluster.Use namespaces to separate the environments.

Answer: A

Explanation:
https://cloud.google.com/architecture/modernization-path-dotnet-applications-google- cloud#phase_1_rehost_in_the_cloud

NEW QUESTION # 218
You are deploying a Python application to Cloud Run using Cloud Build. The Cloud Build pipeline is shown below:

You want to optimize deployment times and avoid unnecessary steps What should you do?

A. Add the -cache-from argument to the Docker build step in your build config file.
B. Remove the step that pushes the container to Artifact Registry.
C. Store image artifacts in a Cloud Storage bucket in the same region as the Cloud Run instance.
D. Deploy a new Docker registry in a VPC and use Cloud Build worker pools inside the VPC to run the build pipeline.

Answer: A

Explanation:
https://cloud.google.com/build/docs/optimize-builds/speeding-up-builds#using_a_cached_docker_image

NEW QUESTION # 219
Your team develops services that run on Google Kubernetes Engine. You need to standardize their log data using Google-recommended practices and make the data more useful in the fewest number of steps. What should you do? (Choose two.)

A. Write log output to standard output (stdout) as single-line JSON to be ingested into Cloud Logging as structured logs.
B. Mandate the use of the Pub/Sub API to write structured data to Pub/Sub and create a Dataflow streaming pipeline to normalize logs and write them to BigQuery for analytics.
C. Mandate the use of the Logging API in the application code to write structured logs to Cloud Logging.
D. Create aggregated exports on application logs to Cloud Storage to facilitate log analytics.
E. Create aggregated exports on application logs to BigQuery to facilitate log analytics.

Answer: A,C

NEW QUESTION # 220
Your company has created an application that uploads a report to a Cloud Storage bucket. When the report is uploaded to the bucket, you want to publish a message to a Cloud Pub/Sub topic. You want to implement a solution that will take a small amount to effort to implement. What should you do?

A. Create a Cloud Function that is triggered by the Cloud Storage bucket. In the Cloud Function, publish a message to the Cloud Pub/Sub topic.
B. Create an App Engine application to receive the file; when it is received, publish a message to the Cloud Pub/Sub topic.
C. Configure the Cloud Storage bucket to trigger Cloud Pub/Sub notifications when objects are modified.
D. Create an application deployed in a Google Kubernetes Engine cluster to receive the file; when it is received, publish a message to the Cloud Pub/Sub topic.

Answer: A

Explanation:
Explanation
https://cloud.google.com/storage/docs/pubsub-notifications

NEW QUESTION # 221
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