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Google Professional-Cloud-Developer Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Designing highly scalable, secure, and reliable cloud-native applications32%- 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
- Designing high-performing applications and APIs
  • 1. Selecting appropriate compute and deployment platforms
  • 2. Optimizing for latency and throughput
  • 3. Designing for high availability and fault tolerance
Topic 2: Configuring cloud-native applications for deployment24%- 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 to App Engine or Cloud Functions
  • 1. Managing versions and traffic splitting
  • 2. Configuring serverless deployments
- 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
Topic 3: Integrating applications with Google Cloud services21%- 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
- 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
Topic 4: Building and testing applications23%- 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. Emulating Google Cloud services locally
  • 2. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations
- 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 (Q215-Q220):

NEW QUESTION # 215
You are a lead developer working on a new retail system that runs on Cloud Run and Firestore. A web UI requirement is for the user to be able to browse through alt products. A few months after go-live, you notice that Cloud Run instances are terminated with HTTP 500: Container instances are exceeding memory limits errors during busy times This error coincides with spikes in the number of Firestore queries You need to prevent Cloud Run from crashing and decrease the number of Firestore queries. You want to use a solution that optimizes system performance What should you do?

Answer: B


NEW QUESTION # 216
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

Explanation:
https://developers.google.com/drive/api/v3/about-auth


NEW QUESTION # 217
You are a developer at a company that operates an ecommerce website. The website stores the customer order data in a Cloud SQL for PostgreSQL database. Data scientists on the marketing team access this data to run their reports. Every time they run these reports, the website's performance is negatively affected. You want to provide access to up-to-date customer order datasets without affecting your website. What should you do?

Answer: B

Explanation:
https://careerfoundry.com/en/blog/data-analytics/where-to-find-free-datasets/


NEW QUESTION # 218
Your company just experienced a Google Kubernetes Engine (GKE) API outage due to a zone failure. You want to deploy a highly available GKE architecture that minimizes service interruption to users in the event of a future zone failure. What should you do?

Answer: D

Explanation:
https://cloud.google.com/kubernetes-engine/docs/concepts/types-of-clusters#regional_clusters A regional cluster has multiple replicas of the control plane, running in multiple zones within a given region. Nodes in a regional cluster can run in multiple zones or a single zone depending on the configured node locations. By default, GKE replicates each node pool across three zones of the control plane's region. When you create a cluster or when you add a new node pool, you can change the default configuration by specifying the zone(s) in which the cluster's nodes run. All zones must be within the same region as the control plane.


NEW QUESTION # 219
You are responsible for deploying a new API. That API will have three different URL paths:
* https://yourcompany.com/students
* https://yourcompany.com/teachers
* https://yourcompany.com/classes
You need to configure each API URL path to invoke a different function in your code. What should you do?

Answer: A

Explanation:
Explanation
https://cloud.google.com/load-balancing/docs/https/setup-global-ext-https-serverless


NEW QUESTION # 220
......

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