Imagine your meticulously built system—whether it's a database storing core customer data, a media content library accumulated over years, or a source code repository for your products—that one day becomes an "antique" you dare not touch.



Why? Because every data unit inside it relates to real value and bears real responsibility. Once something goes wrong, the idea of "starting over" becomes a luxury you can't afford. You simply don't have that opportunity.

How does traditional thinking approach this? By making multiple backups and storing them in different locations. Have you experienced hard drive failures? Data loss in cloud services? At that moment, you'll realize that the so-called "distributed backup" is actually like putting eggs into several paper baskets. The baskets are still paper, and a storm will ruin them all at once.

It wasn't until I encountered the concept of "structural-level fault tolerance" that I truly understood the root of the problem. This is a completely different dimension from the "multiple backups" strategy.

To give an analogy: your system isn't protected from disasters by buying a few more insurance( backups). Instead, from the very beginning of its design, it is built to withstand even if half of the load-bearing walls burn down, the overall structure remains standing.

Recently, I’ve been paying attention to the Walrus project, which addresses this very issue. Its approach to handling files isn't just simple copying. Instead, it employs a highly sophisticated strategy—breaking data objects into fragments, transcoding them, and fragmenting into many pieces, then dispersing them across a global network of nodes.

The key technology is "erasure coding"(Erasure Coding). What does this mean? It means you don't have to wait for all fragments to be intact—if enough fragments survive, the entire file can be fully recovered. If a node goes offline? No problem. If storage in a region crashes? It continues to operate seamlessly.

This is true structural-level fault tolerance—not just stacking backups, but designing the underlying architecture with resilience built in.
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AirDropMissedvip
· 01-11 03:58
The idea of erasure coding is indeed brilliant. It's much more reliable than multiple backups, and finally, there's a project genuinely aiming to solve this pain point.
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GasGuruvip
· 01-11 03:54
Erasure coding is indeed a shift in thinking, but whether Walrus can truly be implemented depends on...
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ruggedNotShruggedvip
· 01-11 03:54
Erasure coding sounds complicated, but it's actually just breaking eggs into pieces and dispersing them so you no longer have to worry about one basket tipping over and everything being lost. Walrus's approach is indeed impressive, fundamentally changing the game rules. The old method of multiple backups should have been phased out long ago; finally, someone has exposed it. This is what true decentralized storage should look like, not just a slogan.
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MysteriousZhangvip
· 01-11 03:35
Erasure coding should have been popularized long ago; it's much more reliable than those flashy "cloud backups" touted by cloud service providers. Really, I once had a hard drive crash, and it was a heart attack. Now I see that this kind of architecture design is the real way to go. I've been following Walrus's sharding strategy; it definitely has some substance, but the deployment cost is a bit steep. Wow, so backups really are just paper baskets. No wonder every time there's a failure. This is what Web3 should be doing—decentralized storage must have this level of fault tolerance design.
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