If you work with structured data in the Google Cloud Platform or would like to, you might be interested in Google’s new Professional Cloud Database Engineer certification, which is currently in beta. A person with this qualification “designs, creates, manages, and troubleshoots Google Cloud databases used by applications to store and retrieve data,” according to Google. Furthermore, they “must be at ease translating business and technical requirements into scalable and cost-effective database solutions.” Let us look at New Google Professional Cloud Database Engineer Exam Launched.
About the exam
Professional Cloud Database Engineer is a database professional with two years of experience in Google Cloud and five years of overall database and IT experience. The Professional Cloud Database Engineer creates, manages, and troubleshoots Google Cloud databases, which are used by applications to store and retrieve data. The Professional Cloud Database Engineer must be able to translate business and technical requirements into scalable and cost-effective database solutions.
Exam Details
- 4 hours is the total duration of the exam.
- The registration fee is $120. (plus tax where applicable)
- The language is English.
- Multiple-choice and multiple-select examination formats
- Method of Exam Delivery:
- a. Take the proctored online exam from a remote location.
- b. Attend an onsite-proctored exam at a testing facility.
- There are no prerequisites.
- 5+ years of overall database and IT experience, including 2 years of hands-on experience working with Google Cloud database solutions, is preferred.
Course Outline
These are the following domains that the exam will be covering –
Section 1: Design scalable and highly available cloud database solutions (42%)
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 (Google Documentation: Migrate to Google Cloud: Assess and discover your workloads)
● Evaluate performance and cost tradeoffs of different database configurations (machine types, HDD versus SSD, etc.) (Google Documentation: Choose between SSD and HDD storage)
● Size database compute and storage based on performance requirements (Google Documentation: Configure disks to meet 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 (Google Documentation: Geography and regions, Multi-regional deployment on Compute Engine)
● Given a scenario, define maintenance windows and notifications based on application availability requirements (Google Documentation: Maintenance windows and exclusions)
● Plan database upgrades for Google Cloud-managed databases (Google Documentation: Upgrade the database major version in-place)
1.3 Determine how applications will connect to the database. Activities include:
● Design scalable, highly available, and secure databases (Google Documentation: Design for scale and high availability)
● Configure network and security (Cloud SQL Auth Proxy, CMEK, SSL certificates) (Google Documentation: Configure SSL/TLS certificates, Cloud SQL Auth Proxy)
● Justify the use of session pooler services (Google Documentation: Sessions)
● Assess auditing policies for managed services (Google Documentation: Organization Policy audit logging)
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) (Google Documentation: Comparative analysis of Google Cloud deployment archetypes)
● Assess application and database dependencies (Google Documentation: Migrate to Google Cloud: Assess and discover your workloads)
Section 2: Manage a solution that can span multiple database solutions (34%)
2.1 Determine database connectivity and access management considerations. Activities include:
● Determine Identity and Access Management (IAM) policies for database connectivity and access control (Google Documentation: Identity and Access Management (IAM))
● Manage database users, including authentication and access (Google Documentation: Manage users with built-in authentication, Manage users with IAM database authentication)
2.2 Configure database monitoring and troubleshooting options. Activities include:
● Assess slow running queries and database locking and identify missing indexes (Google Documentation: Use Query Insights to improve query performance)
● Monitor and investigate database vitals: RAM, CPU storage, I/O, Cloud Logging (Google Documentation: Cloud Logging overview)
● Monitor and update quotas (Google Documentation: View and manage quotas)
● Investigate database resource contention (Google Documentation: Troubleshooting resource contention issues, Introspection tools overview)
● Set up alerts for errors and performance metrics (Google Documentation: Create metric-threshold alerting policies)
2.3 Design database backup and recovery solutions. Activities include:
● Given SLAs and SLOs, recommend backup and recovery options (automatic scheduled backups) (Google Documentation: Backups overview, Create and manage on-demand and automatic backups)
● Configure export and import data for databases (Google Documentation: Exporting and Importing Entities)
● Design for recovery time objective (RTO) and recovery point objective (RPO) (Google Documentation: Disaster recovery planning guide)
2.4 Optimize database cost and performance in Google Cloud. Activities include:
● Assess options for scaling up and scaling out. (Google Documentation: Autoscaling groups of instances)
● Scale database instances based on current and upcoming workload (Google Documentation: Scaling based on schedules)
● Define replication strategies (Google Documentation: Replication)
● Continuously assess and optimize the cost of running a database solution
2.5 Determine solutions to automate database tasks. Activities include:
● Perform database maintenance (Google Documentation: About maintenance on Cloud SQL instances)
● Assess table fragmentation (Google Documentation: Handle processing response)
● Schedule database exports (Google Documentation: Scheduling an Export)
Section 3: Migrate data solutions (14%)
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 (Google Documentation: Migrate to Google Cloud: Best practices for validating a migration plan)
● Reverse replication from Google Cloud to source (Google Documentation: Reverse and resume a replication)
● Plan and perform database migration, including fallback plans and schema conversion (Google Documentation: Database migration: Concepts and principles: Part 1 and Part 2)
● Determine the correct database migration tools for a given scenario (Google Documentation: Overview of Database Migration Service)
Section 4: Deploy scalable and highly available databases in Google Cloud (10%)
4.1 Apply concepts to implement highly scalable and available databases in Google Cloud. Activities include:
● Provision high availability database solutions in Google Cloud (Google Documentation: Enable and disable high availability)
● Test high availability and disaster recovery strategies periodically (Google Documentation: About disaster recovery (DR) in Cloud SQL)
● Set up multi-regional replication for databases (Google Documentation: Regional and multi-region configurations)
● Assess requirements for read replicas (Google Documentation: About read replicas)
● Automate database instance provisioning (Google Documentation: Create instances)
Why should you take the beta exam?
Six to eight weeks after the beta period ends, participants are notified of their exam results. To obtain this certification, you must pass the Professional Cloud Database Engineer beta exam.
Why is beta used?
- Become Google Cloud Certified
- If you pass the beta exam, you can claim a low certificate number.
- Also, Reduce the cost of certification by 40%.
- Furthermore, Beta exam attempts are permitted with vouchers.
- Moreover, Does not count toward the total number of exam attempts allowed.
- Also, Purchase Google-branded apparel.
Study resources for the exam
You can refer to the following resources for clearing the exam –
Google Cloud Free Tier
The Google Cloud Free Tier gives the candidate access to free resources for researching Google Cloud services. This is especially beneficial for candidates who are new to the platform and need to learn the fundamentals. On the other hand, if you’re an existing customer looking to try out new solutions, the Google Cloud Free Tier has you covered.
Study Groups
Candidates may benefit from online study groups when studying for exams. Joining study groups, in other words, will keep you in touch with experts and professionals who have previously walked this path. This group can also be used to discuss and study for any test-related issues or problems.
Practice tests
Finally, it’s time to assess oneself. Take it from us: self-evaluation is the final step toward success. As a result, Google Cloud Certified Professional Data Engineer Practice Exams are all that you require. It is better for you to practice as much as possible. It not only helps you understand where you are lacking, but it also ensures you are improving your skills. So, keep taking as many practice tests as you can.
Hurry up and start preparing with the help of the amazing resources available at TPT!
