Google Professional Cloud Database Engineer exam dumps

Google Professional Cloud Database Engineer practice question 165 of 259

Professional Cloud Database Engineer. Professional level, Google Cloud. Free question with the correct answer and a full explanation.

Google Professional Cloud Database Engineer Question 165

Select 3Google Cloud Platform

Your company has a web application hosted on Google Cloud that experiences highly variable traffic patterns, with peak loads on weekends. The application uses a Cloud SQL instance for its relational database. During peak traffic, the database often becomes a bottleneck, causing increased latency for users. You are tasked with improving the database's performance to handle the peak loads while minimizing costs. Which of the following solutions should you implement?

  1. A

    Enable Read Replicas in Cloud SQL and redirect read-heavy queries to the replicas.

  2. B

    Upgrade the Cloud SQL instance to a larger machine type with more CPU and memory.

  3. C

    Set up a horizontal sharding strategy by splitting the database across multiple Cloud SQL instances.

  4. D

    Enable automatic storage increases in Cloud SQL to handle larger datasets during peak traffic.

  5. E

    Use Cloud Spanner instead of Cloud SQL for built-in horizontal scaling and global consistency.

Show answer and explanation

Correct answers: A, B, E

Explanation

To address the performance bottlenecks, combining strategies like enabling Read Replicas (for read-heavy workloads), scaling up the machine type (for immediate performance needs), and considering Cloud Spanner (for long-term scalability) is ideal. Horizontal sharding is complex to implement quickly, and automatic storage increases do not solve the compute-related bottlenecks.

  • A. Correct.

    Using Read Replicas in Cloud SQL is a cost-effective way to handle read-heavy workloads by offloading read queries to replicas, which can improve performance during peak traffic.

  • B. Correct.

    Scaling up by upgrading to a larger machine type addresses the immediate need for more CPU and memory to handle increased traffic, making it a quick and effective solution for short-term scaling.

  • C. Incorrect.

    While horizontal sharding can improve scalability, it requires significant application changes and is not a native feature of Cloud SQL, making it less ideal for immediate implementation.

  • D. Incorrect.

    Enabling automatic storage increases in Cloud SQL only helps with storage capacity and does not directly address CPU or memory bottlenecks caused by peak traffic.

  • E. Correct.

    Cloud Spanner is a horizontally scalable database designed for high throughput and global consistency, making it a suitable choice for long-term scalability, though it may require significant re-architecture of the application.

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