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Exam Overview

The Professional Cloud Developer certification exam is a 2-hour test covering the multiple-choice and multiple-select questions. It can be taken in English or Japanese and is available as an online proctored and an on-site proctored exam. The registration process costs $200, and this is for the delivery of a single test. The candidates who do not pass the exam must retake it to obtain the associated certificate. To do this, they must pay a new exam fee for their retake.

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

Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Weight	Objectives
Building and testing applications	23%	- Testing applications 1. Writing unit, integration, and end-to-end tests 2. Using AI-assisted development tools 3. Automating testing in CI/CD workflows - Building applications and containers 1. Using Cloud Build and Artifact Registry 2. Implementing containerization best practices 3. Configuring build pipelines and provenance - Setting up development environments 1. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations 2. Emulating Google Cloud services locally
Integrating applications with Google Cloud services	21%	- 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 - 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 - Implementing application performance monitoring 1. Instrumenting code for metrics and traces 2. Using operations suite tools
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. Designing for high availability and fault tolerance 2. Selecting appropriate compute and deployment platforms 3. Optimizing for latency and throughput - 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
Configuring cloud-native applications for deployment	24%	- Deploying to App Engine or Cloud Functions 1. Managing versions and traffic splitting 2. Configuring serverless deployments - 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