The biggest cost black hole for operations and maintenance teams is not in the computing layer, but in disaster recovery plans. Many teams store T-level server snapshots in traditional cloud providers' archives, which initially seem incredibly cheap. However, when it comes to recovery drills, the costs for data retrieval and egress bandwidth alone can break the entire quarterly budget. This feeling of being hostage to centralized service providers is well understood in the industry.

Blockchain-level distributed storage solutions are now beginning to change this situation. The key lies in technological architecture innovation—using efficient erasure coding algorithms. The network no longer needs to maintain dozens of data copies like traditional public blockchains; just 4-5 times redundancy is enough to achieve Byzantine-level fault tolerance. This directly reduces the unit storage cost.

More importantly, the design differences in recovery mechanisms matter. Traditional cloud services perform centralized single-point data retrieval, with cloud providers charging exorbitant rates for egress bandwidth. Distributed solutions allow clients to directly and parallelly fetch data slices from multiple decentralized nodes, avoiding "punitive fees" from middlemen, and bandwidth costs can be controlled within predictable ranges.

From the perspective of DevOps practical needs, distributed storage offers a balanced solution: it provides Byzantine-level fault tolerance (a single data center failure does not affect data availability), while maintaining a pricing model close to Web2 costs. This is the truly implementable decentralized infrastructure approach, rather than idealism stuck in technical whitepapers.