The application reliability team at your company has added a debug feature to their backend service to send all server events to Google Cloud Storage for eventual analysis. The event records are at…

The correct answer is D. Append metadata to file body. https://cloud.google.com/storage/docs/request-rate Use a naming convention that distributes load evenly across key ranges Auto-scaling of an index range can be slowed when using sequential names, such as object keys based on a sequence of numbers or timestamp. This occurs…

Submitted by eva_at· Mar 30, 2026Managing implementation

Question

The application reliability team at your company has added a debug feature to their backend service to send all server events to Google Cloud Storage for eventual analysis. The event records are at least 50 KB and at most 15 MB and are expected to peak at 3,000 events per second. You want to minimize data loss. Which process should you implement?

Options

AAppend metadata to file body.
BBatch every 10,000 events with a single manifest file for metadata.
CCompress individual files.
DAppend metadata to file body.

How the community answered

(61 responses)

A
8% (5)
B
15% (9)
C
3% (2)
D
74% (45)

Explanation

https://cloud.google.com/storage/docs/request-rate Use a naming convention that distributes load evenly across key ranges Auto-scaling of an index range can be slowed when using sequential names, such as object keys based on a sequence of numbers or timestamp. This occurs because requests are constantly shifting to a new index range, making redistributing the load harder and less effective. In order to maintain a high request rate, avoid using sequential names. Using completely random object names will give you the best load distribution.

Topics

#Cloud Storage#event ingestion#high throughput#metadata handling

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