Previous discussions about Blob have focused more on what it can store and how to store it. But to truly understand why Walrus can become a sustainable data layer infrastructure, the key is not in the storage itself, but in the Blob's full lifecycle management mechanism. This involves time constraints, cost design, and the underlying economic model — which are fundamental to whether the entire system can operate stably in the long term.

From a different perspective, data in any real-world system is not static. It is created, frequently accessed, modified, replaced, and eventually either becomes invalid or is cleaned up. If a system only addresses "how to efficiently write data" but ignores the evolution of data over time, the complexity and costs will snowball, increasing more and more until they become uncontrollable.

Walrus's approach is entirely different. It does not treat Blob as something that is "written once and permanently stored," but explicitly defines it as a long-term object that consumes network resources. This means that the existence of a Blob itself continuously consumes storage space, bandwidth, and node maintenance capacity. Since there is consumption, there must be clear time boundaries and cost constraints to support it, rather than using vague billing methods like some centralized cloud storage providers to hide true costs. This is the key to making the entire data layer infrastructure truly coherent and sustainable.