I have aimed to take a Google certification since starting my career. However, I only had the opportunity to work with Google’s products in the last 3 years, when I began working with GCP Cloud. Therefore, I started my preparation in the segment that is my domain: databases. And, mainly because I wanted to go deeper into a product that as Athena for AWS and Oracle as RDBMS, it became one of my favorite products to work with, which is Google’s fully managed, serverless data warehouse named BigQuery.
To my surprise, Google is straightforward in how to succeed in this exam by providing an exam overview by offering access to the Google Cloud Free Tier, sample questions from https://cloud.google.com/certification/cloud-database-engineer:
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
Additionally, Google provides a complete Database Engineer Learning Path, which I love!
I will take the exam and will update this post once I get the confirmation of my results, and in case of a successful or failed attempt, I will update it anyway.
Update Thursday, the 12th of January: I passed!!! I am happy about it, but Google is doing its procedural process to release the official results.:
Update Saturday, the 14th of January: Finally, I received the e-mail from Google confirming my approval! I was not used to the Google post-certification process, but now I know how it works, and I got my first certification from Google. I wish you good studies, and I hope this post helps you!
Hi! I am Bruno, a Brazilian born and bred, and I am also a naturalized Swedish citizen. I am a former Oracle ACE and, to keep up with academic research, I am a Computer Scientist with an MSc in Data Science and another MSc in Software Engineering. I have over ten years of experience working with companies such as IBM, Epico Tech, and Playtech across three different countries (Brazil, Hungary, and Sweden), and I have joined projects remotely in many others. I am super excited to share my interests in Databases, Cybersecurity, Cloud, Data Science, Data Engineering, Big Data, AI, Programming, Software Engineering, and data in general.
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