Distributed storage has always faced a major challenge—single point of failure. Walrus addresses this problem with a combination of sharding and erasure coding. Its core advantage is that even if more than 2/3 of data shards are damaged or nodes go offline, the system can quickly restore the complete file through mathematical algorithms. This is like providing redundant backups for data, but not through bulky full copies, rather through a smart distributed design.

Compared to traditional solutions, the brilliance of this mechanism lies in—don't put all your eggs in one basket. Coupled with random challenges and Merkle tree dual verification, the cost for nodes to maliciously act is extremely high, making such behavior almost unprofitable. For users, important data such as AI model training sets, in-game assets, and social content finally have a reliable decentralized storage solution. No longer worrying about data loss every day, but having infrastructure that can truly be used in production environments.