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Updated: Aug 05, 2026

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Important Details

The candidates for this certification are the Cloud developers who have competence in building highly available and scalable apps with the Google-recommended tools and practices. They also have proficiency in a minimum of one general-purpose programming language. It is recommended that the individuals for the Professional Cloud Developer certificate have at least three years of practical experience with Google Cloud solutions and products. They should also possess at least one year of designing and managing solutions with the use of GCP. Please note that you should also understand the content of the prerequisite exam before attempting it.

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

Google Professional-Cloud-Developer Exam Overview:

Certification Vendor:Google Cloud
Exam Name:Google Cloud Certified Professional - Cloud Developer Exam
Exam Number:Professional-Cloud-Developer
Related Certifications:Google Cloud Certified Associate - Cloud Engineer
Google Cloud Certified Professional - Cloud Architect
Real Exam Qty:50-60
Exam Duration:120 minutes
Available Languages:English, Japanese
Exam Price:$200 USD (plus tax where applicable)
Passing Score:Not publicly disclosed
Exam Format:Multiple choice, Multiple select
Certificate Validity Period:2 years
Recommended Training:Google Cloud Professional Cloud Developer Learning Path
Official Exam Guide
Exam Registration:Google Cloud Certification Registration
Sample Questions:Google Professional-Cloud-Developer Sample Questions
Exam Way:Online-proctored (remote) or onsite-proctored at authorized testing centers
Pre Condition:No formal prerequisites; recommended: 3+ years industry experience, 1+ year designing/managing Google Cloud solutions
Official Syllabus URL:https://cloud.google.com/learn/certification/cloud-developer

Section 5: Managing Application Performance Monitoring

The last module of the certification test focuses on the ability of the applicants to perform the following technical tasks: managing Compute Engine Virtual Machines (VMs), managing Google Kubernetes Engine workloads, as well as troubleshooting the application performance.

Some of the questions included in the Google Professional Cloud Developer certification exam may guide you to a case study describing a fictitious solution and business concept. This will provide you with additional context to choose the right answer(s). You can get an idea of a possible case study by studying the example contained in the official study guide.

Google Professional-Cloud-Developer Exam Syllabus Topics:

SectionWeightObjectives
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. Using object storage and file storage solutions
  • 2. Implementing messaging and event streaming
  • 3. Working with relational, NoSQL, and in-memory databases
- Consuming Google Cloud APIs and services
  • 1. Using client libraries, REST, and gRPC
  • 2. Enabling and managing APIs
  • 3. Integrating with AI/ML and generative AI services
Configuring cloud-native applications for deployment24%- 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
- Deploying applications to Cloud Run
  • 1. Integrating with event-driven services
  • 2. Deploying from source code or containers
  • 3. Configuring scaling, networking, and security
Building and testing applications23%- Testing applications
  • 1. Using AI-assisted development tools
  • 2. Writing unit, integration, and end-to-end tests
  • 3. Automating testing in CI/CD workflows
- 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. Emulating Google Cloud services locally
  • 2. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations
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. Designing for high availability and fault tolerance
  • 2. Optimizing for latency and throughput
  • 3. Selecting appropriate compute and deployment platforms

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