Professional Cloud Database Engineer
Certification exam guide
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.
Section 1: Design scalable and highly available cloud database solutions
1.1 Analyze relevant variables to perform database
capacity and usage planning. Activities include: ● Given a scenario, perform
solution sizing based on current environment workload
metrics and future requirements ● Evaluate performance and cost
tradeoffs of different database configurations (machine
types, HDD versus SSD, etc.) ● Size database compute and storage
based on performance requirements 1.2 Evaluate database high availability and disaster
recovery options given the requirements. Activities
include: ● Evaluate tradeoffs between
multi-region, region, and zonal database deployment
strategies ● Given a scenario, define
maintenance windows and notifications based on
application availability requirements ● Plan database upgrades for Google
Cloud-managed databases 1.3 Determine how applications will connect to the
database. Activities include: ● Design scalable, highly
available, and secure databases ● Configure network and security
(Cloud SQL Auth Proxy, CMEK, SSL certificates) ● Justify the use of session pooler
services ● Assess auditing policies for
managed services 1.4 Evaluate appropriate database solutions on Google
Cloud. Activities include: ● Differentiate between managed and
unmanaged database services (self-managed, bare metal,
Google-managed databases and partner database offerings)
● Distinguish between SQL and NoSQL
business requirements (structured, semi-structured,
unstructured) ● Analyze the cost of running
database solutions in Google Cloud (comparative
analysis) ● Assess application and database
dependencies
Section 2: Manage a solution that can span multiple database solutions
2.1 Determine database connectivity and access
management considerations. Activities include: ● Determine Identity and Access
Management (IAM) policies for database connectivity and
access control ● Manage database users, including
authentication and access 2.2 Configure database monitoring and troubleshooting
options. Activities include: ● Assess slow running queries and
database locking and identify missing indexes ● Monitor and investigate database
vitals: RAM, CPU storage, I/O, Cloud 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.
Activities include: ● Given SLAs and SLOs, recommend
backup and recovery options (automatic scheduled
backups) ● Configure export and import data
for databases ● Design for recovery time
objective (RTO) and recovery point objective (RPO) 2.4 Optimize database cost and performance in Google
Cloud. Activities include: ● Assess options for scaling up and
scaling out. ● Scale database instances based on
current and upcoming workload ● Define replication strategies ● Continuously assess and optimize
the cost of running a database solution 2.5 Determine solutions to automate database tasks.
Activities include: ● Perform database maintenance ● Assess table fragmentation ● Schedule database exports
Section 3: Migrate data solutions
3.1 Design and implement data migration and
replication. Activities include: ● Develop and execute migration
strategies and plans, including zero downtime, near-zero
downtime, extended outage, and fallback plans ● Reverse replication from Google
Cloud to source ● Plan and perform database
migration, including fallback plans and schema
conversion ● Determine the correct database
migration tools for a given scenario
Section 4: Deploy scalable and highly available databases in Google Cloud
4.1 Apply concepts to implement highly scalable and
available databases in Google Cloud. Activities include:
● Provision high availability
database solutions in Google Cloud ● Test high availability and
disaster recovery strategies periodically ● Set up multi-regional replication
for databases ● Assess requirements for read
replicas ● Automate database instance
provisioning