Practice Test 2 | Google Cloud Certified Professional Cloud Architect | Dumps | Mock Test
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?
A. Append metadata to file body. Compress individual files. Name files with a random prefix pattern. Save files to one bucket
B. Batch every 10,000 events with a single manifest file for metadata. Compress event files and manifest file into a single archive file. Name files using serverName-EventSequence. Create a new bucket if bucket is older than 1 day and save the single archive file to the new bucket. Otherwise, save the single archive file to existing bucket.
C. Compress individual files. Name files with serverName-EventSequence. Save files to one bucket Set custom metadata headers for each object after saving.
D. Append metadata to file body. Compress individual files. Name files with serverName-Timestamp. Create a new bucket if bucket is older than 1 hour and save individual files to the new bucket. Otherwise, save files to existing bucket
Correct Answer A
Feedback
Avoid using sequential filenames such as timestamp-based filenames if you are uploading many files in parallel. Because files with sequential names are stored consecutively, they are likely to hit the same backend server, meaning that throughput will be constrained. In order to achieve optimal throughput, you can add the hash of the sequence number as part of the filename to make it non-sequential https://cloud.google.com/storage/docs/best-practices
Answer A (Correct) – since it uses “Name files with a random prefix pattern.”
Answer C , B, and D are incorrect since they use either “Name files with serverName-EventSequence” Or “Name files with serverName-Timestamp” which will cause the files unevenly distributed in the backend. For example, a specific server may generate much more events than other, or at certain time period the system may generate much more events than other period…
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