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Google Cloud Exam Syllabus

Professional Cloud Database Engineer syllabus, skills measured, and exam topics

A Professional Cloud Database Engineer is a database professional with experience in designing, creating, managing, and troubleshooting Google Cloud databases used by applications to store and retrieve data. The Professional Cloud Database Engineer should be

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Skills measured by domain

Use the weighting table to decide where to spend the most study time.

Domain Weight
Section 2: Manage a solution that can span multiple database technologies 25%
Section 3: Migrate data solutions 23%
Section 4: Deploy scalable and highly available databases in Google Cloud 20%

What to know before you study

These sections explain the role, audience, and exam framing behind the outline.

Section 1: Design innovative, scalable, and highly available cloud database

  • solutions (~32% of the exam)
  • 1.1 Analyze relevant variables to perform database capacity and usage planning
  • Considerations include:
  • Perform solution sizing based on current environment workload metrics and future
  • requirements
  • Evaluate performance and cost tradeo￾s of di￾erent database con￾gurations (e.g.,
  • machine types, storage types)
  • Size database compute and storage based on performance requirements
  • 1.2 Evaluate database high availability and disaster recovery options given the requirements
  • Considerations include:
  • Evaluate tradeo￾s between multi-regional, regional, and zonal database deployment
  • strategies

Detailed outline

Scan each section as a working study checklist instead of one long wall of text.

Section 2: Manage a solution that can span multiple database technologies (~25%

  • of the exam)
  • 2.1 Determine database connectivity and access management considerations
  • Considerations include:
  • Determine Identity and Access Management (IAM) and policies for database
  • connectivity and access control
  • Manage database users including authentication and access
  • 2.2 Con￾gure database monitoring and troubleshooting options
  • Considerations include:
  • Assess slow running queries, database locking - identify missing indexes
  • Monitor and investigate database vitals - RAM, CPU storage, I/O, and audit logging
  • Monitor and update quotas
  • Investigate database resource contention

Section 3: Migrate data solutions (~23% of the exam)

  • 3.1 Design and implement data migration and replication
  • Considerations include:
  • Develop and execute migration strategies and plans, including zero/near-zero
  • downtime, extended outage, and fallback
  • Reverse replication from Google Cloud to source
  • Plan and perform database migration, including fallback plans and DDL/DML conversion
  • Determine the correct database migration tools for a given scenario (e.g., databases
  • hosted outside of Google Cloud)

Section 4: Deploy scalable and highly available databases in Google Cloud (~20%

  • of the exam)
  • 4.1 Apply concepts to implement scalable and highly available databases in Google Cloud.
  • Considerations include:
  • Provision highly available database solutions in Google Cloud
  • Test high availability and disaster recovery strategies
  • Set up multi-regional replication for databases
  • Deploy and scale read replicas
  • Automate database instance provisioning
  • Con￾gure monitoring for highly available databases