Google Professional Cloud Developer Question 183
Select 4Google Cloud PlatformYour application processes user-uploaded images and stores them in a Google Cloud Storage bucket. You are experiencing an increase in traffic, and the data volume is growing significantly. You need to ensure that your solution is scalable and cost-efficient while maintaining high availability. What should you do?
- A
Use multi-regional Google Cloud Storage buckets to store the images.
- B
Implement Object Lifecycle Management policies to automatically delete older images.
- C
Store the images in a single Compute Engine instance with an attached persistent disk.
- D
Compress the images before uploading them to reduce storage costs.
- E
Use a Content Delivery Network (CDN) to serve frequently accessed images.
Show answer and explanation
Correct answers: A, B, D, E
Explanation
As your application's data volume grows, it is crucial to build a scalable and cost-efficient solution. Multi-regional Google Cloud Storage ensures high availability, while Object Lifecycle Management and image compression reduce storage costs. Additionally, a CDN improves performance for frequently accessed data. Storing data on a single Compute Engine instance is not suitable for scaling with increasing traffic, as it introduces bottlenecks and risks of failure.
- A. Correct.
Using multi-regional buckets ensures high availability and faster access across different regions, which is ideal for scalable and global applications.
- B. Correct.
Implementing Object Lifecycle Management policies helps reduce storage costs by automatically deleting or transitioning older data to lower-cost storage classes.
- C. Incorrect.
Storing images in a single Compute Engine instance is not scalable or cost-efficient for handling large volumes of data, especially with growing traffic.
- D. Correct.
Compressing images reduces the amount of data stored, which directly lowers storage costs, making it a cost-efficient approach.
- E. Correct.
Using a CDN helps in serving frequently accessed images more efficiently, reducing latency and offloading requests from the storage bucket.