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Main Exam Details

Google Professional Cloud Developer exam lasts for 2 hours and costs $200. Usually, the questions in it come in form of multiple choice and multiple select items. The exam is available across the globe in Japanese and English languages and has two recognized delivery modes. Firstly, candidates can enroll in the online-proctored test and take it from any location. However, if you fancy the idea of sitting for the exam from a physical location, choosing the onsite proctored format makes more sense.

Usually, there are no prerequisites for the Google Professional Cloud Developer test. However, Google recommends that learners should have a minimum of 3 years of proven industry experience that includes one year of creating as well as managing solutions with GCP.

Reference: https://cloud.google.com/certification/cloud-developer

To earn the Google Professional-Cloud-Developer certification, candidates must pass a three-hour exam consisting of multiple-choice and multiple-select questions. Professional-Cloud-Developer exam is computer-based and can be taken remotely or at a testing center. The passing score for the exam is 70%, and the certification is valid for two years. Candidates are required to renew their certification every two years to demonstrate their ongoing expertise in GCP development.

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Google Professional-Cloud-Developer Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Configuring cloud-native applications for deployment24%- Deploying applications to Cloud Run
  • 1. Integrating with event-driven services
  • 2. Deploying from source code or containers
  • 3. Configuring scaling, networking, and security
- Deploying to App Engine or Cloud Functions
  • 1. Managing versions and traffic splitting
  • 2. Configuring serverless deployments
- Deploying applications to Google Kubernetes Engine
  • 1. Managing configurations and secrets
  • 2. Creating and managing workloads and services
  • 3. Configuring scaling, auto-scaling, and updates
Topic 2: Integrating applications with Google Cloud services21%- 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
- Consuming Google Cloud APIs and services
  • 1. Integrating with AI/ML and generative AI services
  • 2. Enabling and managing APIs
  • 3. Using client libraries, REST, and gRPC
Topic 3: Designing highly scalable, secure, and reliable cloud-native applications32%- Designing for observability and monitoring
  • 1. Planning logging, metrics, and tracing strategies
  • 2. Designing for debugging and troubleshooting
- Designing secure applications
  • 1. Securing data in transit and at rest
  • 2. Applying security best practices and compliance requirements
  • 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
Topic 4: Building and testing applications23%- Testing applications
  • 1. Writing unit, integration, and end-to-end tests
  • 2. Automating testing in CI/CD workflows
  • 3. Using AI-assisted development tools
- 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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