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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: 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 Cloud Run 1. Configuring scaling, networking, and security 2. Integrating with event-driven services 3. Deploying from source code or containers - Deploying applications to Google Kubernetes Engine 1. Creating and managing workloads and services 2. Managing configurations and secrets 3. Configuring scaling, auto-scaling, and updates
Topic 2: Designing highly scalable, secure, and reliable cloud-native applications	32%	- Designing secure applications 1. Applying security best practices and compliance requirements 2. Securing data in transit and at rest 3. Implementing authentication and authorization mechanisms - 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. Designing for debugging and troubleshooting 2. Planning logging, metrics, and tracing strategies
Topic 3: Building and testing applications	23%	- Testing applications 1. Writing unit, integration, and end-to-end tests 2. Automating testing in CI/CD workflows 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 - Setting up development environments 1. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations 2. Emulating Google Cloud services locally
Topic 4: Integrating applications with Google Cloud services	21%	- Implementing application performance monitoring 1. Instrumenting code for metrics and traces 2. Using operations suite tools - Integrating with data and storage services 1. Implementing messaging and event streaming 2. Using object storage and file storage solutions 3. Working with relational, NoSQL, and in-memory databases - 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 (Q178-Q183):

NEW QUESTION # 178
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. Install the Stackdriver agents on your Compute Engine instances.
B. Use Stackdriver to capture and alert on logs, then ship them to your existing platform.
C. Replace your entire monitoring platform with Stackdriver.
D. Migrate some traffic back to your old platform and perform AB testing on the two platforms concurrently.

Answer: A

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

NEW QUESTION # 179
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. Deploy the application using MS Web Deploy, and make sure to always use the latest, patched MS Windows Server base image in Compute Engine.
B. Rewrite the application using .NET Core, and deploy to Cloud Run. Use revisions to separate the environments.
C. Use Cloud Build to deploy the application as a new Compute Engine image for each build. Use this image in each environment.
D. Use Cloud Build to package the application, and deploy to a Google Kubernetes Engine cluster. Use namespaces to separate the environments.

Answer: C

Explanation:
Explanation
https://cloud.google.com/architecture/modernization-path-dotnet-applications-google-cloud#phase_1_rehost_in_
https://cloud.google.com/architecture/modernization-path-dotnet-applications-google-cloud

NEW QUESTION # 180
You are in the final stage of migrating an on-premises data center to Google Cloud. You are quickly approaching your deadline, and discover that a web API is running on a server slated for decommissioning.
You need to recommend a solution to modernize this API while migrating to Google Cloud. The modernized web API must meet the following requirements:
* Autoscales during high traffic periods at the end of each month
* Written in Python 3.x
* Developers must be able to rapidly deploy new versions in response to frequent code changes You want to minimize cost, effort, and operational overhead of this migration. What should you do?

A. Ask the development team to re-write the application to run as a Docker container on Google Kubernetes Engine.
B. Deploy the modernized application to an n1-standard-1 Compute Engine instance.
C. Modernize and deploy the code on App Engine flexible environment.
D. Modernize and deploy the code on App Engine standard environment.

Answer: D

Explanation:
https://cloud.google.com/appengine/docs/standard

NEW QUESTION # 181
You are developing an ecommerce application that stores customer, order, and inventory data as relational tables inside Cloud Spanner. During a recent load test, you discover that Spanner performance is not scaling linearly as expected. Which of the following is the cause?

A. The use of the STRING data type for arbitrary-precision values.
B. The use of Version 1 UUIDs as primary keys that increase monotonically.
C. The use of LIKE instead of STARTS_WITH keyword for parameterized SQL queries.
D. The use of 64-bit numeric types for 32-bit numbers.

Answer: B

Explanation:
https://cloud.google.com/spanner/docs/schema-and-data-model#choosing_a_primary_key

NEW QUESTION # 182
Your application is deployed in a Google Kubernetes Engine (GKE) cluster. When a new version of your application is released, your CI/CD tool updates the spec.template.spec.containers[0].image value to reference the Docker image of your new application version. When the Deployment object applies the change, you want to deploy at least 1 replica of the new version and maintain the previous replicas until the new replica is healthy.
Which change should you make to the GKE Deployment object shown below?

A. Set the Deployment strategy to Recreate with maxSurge set to 1, maxUnavailable set to 0.
B. Set the Deployment strategy to Recreate with maxSurge set to 0, maxUnavailable set to 1.
C. Set the Deployment strategy to RollingUpdate with maxSurge set to 0, maxUnavailable set to 1.
D. Set the Deployment strategy to RollingUpdate with maxSurge set to 1, maxUnavailable set to 0.

Answer: A

NEW QUESTION # 183
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