Exam: Google Professional Cloud Data Engineer certification (GOOGPCDE)

A Professional Cloud Database Engineer is a database professional with two years of Google Cloud experience and five years of overall database and IT experience. The Professional Cloud Database Engineer designs, creates, manages, and troubleshoots Google Cloud databases used by applications to store and retrieve data. The Professional Cloud Database Engineer should be comfortable translating business and technical requirements into scalable and cost-effective database solutions.

Length: 2 hours

Registration fee: $200 (plus tax where applicable)

Language: English

Exam format: 50-60 multiple choice and multiple select questions

Exam Delivery Method:

a. Take the online-proctored exam from a remote location.

b. Take the onsite-proctored exam at a testing center - search for Google Cloud. 

Prerequisites: None

Recommended experience: 5+ years of overall database and IT experience, including 2 years of hands-on experience working with Google Cloud database solutions

Certification renewal: Candidates may renew their certification within the renewal eligibility period. For more information about the renewal process, eligibility period, and certification validity timeline, please refer to the Renewal FAQs below.

The Professional Cloud Database Engineer exam assesses your ability to:

• Design scalable and highly available cloud database solutions
• Manage a solution that can span multiple database solutions
• Migrate data solutions
• Deploy scalable and highly available databases in Google Cloud

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 tradeoffs of different database configurations (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 tradeoffs between multi-regional, regional, and zonal database deployment strategies
• Define maintenance windows and notifications based on application availability requirements
• 1.3 Determine how applications wil connect to the database Considerations include:
• Configure networking, key management, encryption, and security
• Justify the use of session pooler services
• Assess auditing policies for managed services
• 1.4 Evaluate appropriate database solutions on Google Cloud Considerations include:
• Differentiate between managed and unmanaged database services (e.g., self-managed, bare metal, Google-managed, Google Cloud native and partner database offerings)
• Distinguish between SQL and NoSQL business requirements (e.g., structured, semi-structured, unstructured, vector)
• Analyze the cost of running database solutions in Google Cloud (comparative analysis)
• Assess application and database dependencies
• Identify solutions to support regulatory and compliance requirements
• Understand implications of organizational policies on database strategy 
• Consider solutions that span multiple database technologies (e.g. federation, exports, hybrid deployments)
• Leverage database technologies to support generative AI and LLM use cases 

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 Configure 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
• Set up alerts for errors and performance metrics
• 2.3 Design database backup and recovery solutions Considerations include:
• Given requirements, recommend backup and recovery options (automatic scheduled backups)
• Configure export and import data for databases
• Design for RTO, RPO, and PITR
• Manage data retention 
• 2.4 Optimize database cost and performance in Google Cloud Considerations include:
• Assess scaling up and scaling out options
• Scale database instances based on current and upcoming workload
• Define replication strategies 
• Continuously assess and optimize the cost of running a database solution
• Optimize queries for cost and performance 
• 2.5 Automate common database tasks  Considerations include:
• Perform database maintenance (e.g., rebuilding indexes, data exports)
• Schedule database exports
• Manage upgrades for Google Cloud-managed databases
• Monitor database SLA/SLOs 

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 falback 
• Reverse replication from Google Cloud to source
• Plan and perform database migration, including falback 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
• Configure monitoring for highly available databases

Recommended experience: 5+ years of overall database and IT experience, including 2 years of hands-on experience working with Google Cloud database solutions