PROFESSIONAL-CLOUD-DATABASE-ENGINEER Question #199: Real Exam Question with Answer & Explanation

Question

Your e-learning platform runs on a Cloud SQL for PostgreSQL instance (16 VCPUs, 60 GB memory and 1TB SSD) serving users in North America. Your analytics team runs complex reporting queries that often consume 80% of CPU resources, causing slow response times for student transactions during peak hours. Current workload includes 8,000 transactions per second with 60% reads and 40% writes. The reporting queries involve JOIN operations across multiple large tables with millions of rows requiring highly efficient analytical processing. The platform also experiences sudden spikes in analytical reporting demand, requiring an elastic scaling of read capacity. You need to improve the query performance for your analytics team to run their reports efficiently without impacting transactional users. You also need to plan for future traffic growth. What should you do-

Options

• AUpgrade to Cloud SAL for PostgreSQL Enterprise Edition and route transaction and analytical
• BMigrate to AlloyDB for PostgreSQL and upgrade the machine type of the primary instance to 32
• CMigrate to AlloyDB for PostgreSQL with a 16 vCPU primary instance and enable columnar engine
• DUpgrade the Cloud SQL for PostgreSQL instance to db-n1-highmem-32 and implement

Explanation

Migrating to AlloyDB for PostgreSQL with the columnar engine is the best option for this mixed workload. The columnar engine accelerates analytical queries such as multi-table JOINs on large datasets, while the primary instance continues handling transactional traffic. Using read pools isolates analytical reporting from transactional operations and provides elastic scaling to handle sudden spikes in reporting demand. This ensures efficient reporting without degrading transactional performance and supports future growth.

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