ISO逍遥

I keep coming back to the same bottleneck when I think about building for AI or heavy duty Web3 apps and that is Data Storage. It is either centralized and risky or decentralized and painfully inefficient. After going through $WAL | Walrus technical documentation and their announcements from last year, what stands out to me is not just another storage layer, but a specific engineering choice that flips the script on the usual trade offs. The team at Mysten Labs did not just optimize an existing model, they built a new one from the ground up to handle the specific chaos of a permissionless network.
Most decentralized storage systems force you to pick your poison. You can have full replication, like in traditional blockchains, where data is copied across every validator. This gives you great availability and simple recovery, but the cost is absurdly high overhead, think 25x replication or more for strong security. The other path is erasure coding, which chops data into pieces so you do not need full copies. This is far more efficient on storage but historically falls apart when nodes in the network churn. Recovering a lost piece required broadcasting the entire original file across the network again, obliterating any bandwidth savings. It created systems that were efficient only in perfectly static conditions, which does not exist in the real world of decentralized nodes.
Walrus core innovation, detailed in their April 2025 whitepaper, is a novel two dimensional erasure coding protocol they call Red Stuff. This is the pivot. It breaks the data into slivers in a way that allows for what they term "self healing" recovery. When a storage node goes offline, the network can repair the lost data using only a small, proportional subset from other nodes, not the entire original file. The outcome is a system that keeps strong security with an replication factor of just 4.5x, a reasonable leap from the 25x required for full replication. More importantly, the practical outcome is a network that can keep efficient and resilient even with nodes continuously joining and leaving. This is not a marginal improvement, it changes the economic viability of storing massive datasets in a decentralized way.
#WAL $WAL @WalrusProtocol

I keep coming back to the same bottleneck when I think about building for AI or heavy duty Web3 apps and that is Data Storage. It is either centralized and risky or decentralized and painfully inefficient. After going through $WAL | Walrus technical documentation and their announcements from last year, what stands out to me is not just another storage layer, but a specific engineering choice that flips the script on the usual trade offs. The team at Mysten Labs did not just optimize an existing model, they built a new one from the ground up to handle the specific chaos of a permissionless network.
Most decentralized storage systems force you to pick your poison. You can have full replication, like in traditional blockchains, where data is copied across every validator. This gives you great availability and simple recovery, but the cost is absurdly high overhead, think 25x replication or more for strong security. The other path is erasure coding, which chops data into pieces so you do not need full copies. This is far more efficient on storage but historically falls apart when nodes in the network churn. Recovering a lost piece required broadcasting the entire original file across the network again, obliterating any bandwidth savings. It created systems that were efficient only in perfectly static conditions, which does not exist in the real world of decentralized nodes.
Walrus core innovation, detailed in their April 2025 whitepaper, is a novel two dimensional erasure coding protocol they call Red Stuff. This is the pivot. It breaks the data into slivers in a way that allows for what they term "self healing" recovery. When a storage node goes offline, the network can repair the lost data using only a small, proportional subset from other nodes, not the entire original file. The outcome is a system that keeps strong security with an replication factor of just 4.5x, a reasonable leap from the 25x required for full replication. More importantly, the practical outcome is a network that can keep efficient and resilient even with nodes continuously joining and leaving. This is not a marginal improvement, it changes the economic viability of storing massive datasets in a decentralized way.
$WAL #walrus @WalrusProtocol