The application reliability team at your company this 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?

The correct option minimizes data loss and optimizes for high-volume, small-to-medium object storage. Appending metadata to the file body ensures data integrity with the event itself. Compressing individual files reduces storage costs and improves upload efficiency. Naming files with a random prefix pattern distributes writes across Google Cloud Storage (GCS) shards, preventing hot-spotting and maximizing ingestion rates for 3,000 events per second. Saving to one bucket simplifies management and avoids unnecessary bucket creation overhead. The other options introduce complexities or inefficiencies. Batching events with a manifest file (option 2) adds latency and a single point of failure for metadata. Creating new buckets based on age (options 1 and 2) is an anti-pattern for high-volume ingestion and adds management overhead without clear benefits. Setting custom metadata headers after saving (option 3) adds an extra operation per object, increasing cost and latency.