100% Pass 2026 Google Professional-Cloud-Developer: Useful Google Certified Professional - Cloud Developer Lead2pass Review

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Google Professional-Cloud-Developer Exam Syllabus Topics:

SectionWeightObjectives
Designing highly scalable, secure, and reliable cloud-native applications32%- Designing high-performing applications and APIs
  • 1. Optimizing for latency and throughput
  • 2. Selecting appropriate compute and deployment platforms
  • 3. Designing for high availability and fault tolerance
- Designing for observability and monitoring
  • 1. Designing for debugging and troubleshooting
  • 2. Planning logging, metrics, and tracing strategies
- 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 deployment24%- 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
Integrating applications with Google Cloud services21%- 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
- Integrating with data and storage services
  • 1. Implementing messaging and event streaming
  • 2. Working with relational, NoSQL, and in-memory databases
  • 3. Using object storage and file storage solutions
- Implementing application performance monitoring
  • 1. Using operations suite tools
  • 2. Instrumenting code for metrics and traces
Building and testing applications23%- Building applications and containers
  • 1. Configuring build pipelines and provenance
  • 2. Implementing containerization best practices
  • 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

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Google Certified Professional - Cloud Developer Sample Questions (Q178-Q183):

NEW QUESTION # 178
You want to migrate an on-premises container running in Knative to Google Cloud. You need to make sure that the migration doesn't affect your application's deployment strategy, and you want to use a fully managed service. Which Google Cloud service should you use to deploy your container?

Answer: B

Explanation:
https://cloud.google.com/blog/products/serverless/knative-based-cloud-run-services-are-ga


NEW QUESTION # 179
Your team is developing an application in Google Cloud that executes with user identities maintained by Cloud Identity. Each of your application's users will have an associated Pub/Sub topic to which messages are published, and a Pub/Sub subscription where the same user will retrieve published messages. You need to ensure that only authorized users can publish and subscribe to their own specific Pub/Sub topic and subscription. What should you do?

Answer: B


NEW QUESTION # 180
You are developing a dashboard that aggregates temperature readings from thousands of IoT devices monitoring a city's ambient temperature. You expect a large amount of viewing traffic resulting in a large amount of data egress once the dashboard is live. The dashboard temperature display data doesn't need to be real-time and can tolerate a few seconds of lag. You decide to deploy Memorystore for Redis as the storage backend. You want to ensure that the dashboard will be highly available. How should you configure the service in Memorystore for Redis?

Answer: D

Explanation:
Using read replicas in Memorystore for Redis enhances availability by providing redundancy. If the primary instance experiences downtime, read replicas can continue serving requests, ensuring that the dashboard remains accessible. Read replicas also help distribute read traffic, which can be beneficial for high-demand applications, even though Redis itself is an in-memory store with fast access.
- Updating to the latest version may improve performance or security but does not directly improve availability.
- Private Service Access and Serverless VPC Access are network configurations that reduce latency and secure connections but do not inherently improve availability.


NEW QUESTION # 181
You are deploying your application on a Compute Engine instance that communicates with Cloud SQL. You will use Cloud SQL Proxy to allow your application to communicate to the database using the service account associated with the application's instance. You want to follow the Google-recommended best practice of providing minimum access for the role assigned to the service account. What should you do?

Answer: A


NEW QUESTION # 182
You are creating an App Engine application that writes a file to any user's Google Drive.
How should the application authenticate to the Google Drive API?

Answer: A


NEW QUESTION # 183
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