Decentralized storage does not scale in the same way as traditional cloud infrastructure. In centralized systems, growth is mostly a matter of adding servers and bandwidth. The control plane remains the same. In decentralized systems, growth changes the structure of the network itself. Every new node adds not only capacity, but also a new economic actor with its own incentives, risks, and potential to influence outcomes. Walrus was designed with this reality in mind. Its architecture treats growth as a process of continuous economic and cryptographic rebalancing rather than simple capacity expansion. At small scale, a decentralized storage network can rely on informal assumptions. A few dozen operators can coordinate implicitly. Failure modes are limited. As the network grows to hundreds or thousands of nodes and holds large volumes of economically valuable data, those assumptions break down. Power concentrates. Information asymmetries emerge. Attack surfaces multiply. A storage protocol that cannot adapt to this transformation will either become centralized or unstable. Walrus addresses this by making adaptation part of the protocol itself. The core idea is that network growth is not just about more data. It is about more capital being committed to the system. Every storage node stakes WAL. Every file stored is backed by economic guarantees. As the network grows, the total amount of capital securing the data grows with it. This creates a scaling curve where security increases alongside usage rather than lagging behind it. This is different from many storage networks that treat capacity and security as separate. In Walrus, they are the same thing. A node cannot offer storage without staking. A dataset cannot exist without being economically collateralized. Growth therefore increases not only how much data the network can hold, but also how expensive it becomes to attack or corrupt that data. However, capital alone does not solve the problem. If that capital were allowed to concentrate into a few large operators, the network would become fragile. Walrus avoids this by ensuring that economic weight does not translate into permanent control. Stake influences eligibility and capacity, but it does not create ownership over specific data. That distinction is what allows the system to scale without ossifying. As more nodes join, the protocol does not simply assign them unused space. It recomputes the entire allocation of responsibility. Storage is treated as a fluid resource that is continuously redistributed based on the current state of the network. This means that growth causes a network-wide reconfiguration, not just an extension at the edges. This reconfiguration is important for two reasons. First, it allows new participants to become economically relevant immediately. They do not have to wait for new data to arrive. They are integrated into the custody of existing data through protocol-driven reassignment. Second, it prevents incumbents from accumulating structural advantage. Even if a node has been in the system for a long time, it cannot assume it will continue to hold the same datasets as the network expands. From an economic perspective, this turns Walrus into a continuously clearing market for storage responsibility. Each epoch effectively reopens the market. Nodes compete to hold data. Performance, stake, and availability determine outcomes. No one receives a permanent franchise. As data volume grows, this market becomes deeper rather than more concentrated. More nodes means more bidders for storage responsibility. More stake means more security backing each dataset. Growth increases competition instead of reducing it. This dynamic also allows Walrus to absorb technological change. Hardware improves. Network conditions evolve. Some nodes upgrade. Others do not. Because responsibility is continuously redistributed, the system naturally shifts data toward the most capable infrastructure. There is no need for manual intervention or migration plans. The protocol performs this adaptation automatically through its economic and cryptographic rules. Growth also creates regulatory and institutional pressure. As more valuable data and more serious applications depend on the network, the cost of failure increases. Walrus responds to this by increasing the cost of misbehavior at the same pace. More usage means more stake locked. More stake locked means more collateral at risk for every storage operator. The security of the system therefore scales with its importance. This is a crucial difference from networks that rely primarily on technical redundancy. Redundancy helps with outages. It does not help with coordinated abuse or economic capture. Walrus treats growth as a process of increasing the financial gravity of the system. Attacking it becomes more expensive as it becomes more useful. What emerges from this design is a network that does not simply get bigger. It becomes more robust, more competitive, and more economically dense. Storage capacity grows, but so does the cost of corruption. Participation grows, but so does the difficulty of coordination among attackers. This is what allows Walrus to remain decentralized as it scales. It does not rely on the hope that participants will remain honest. It relies on the fact that honesty remains the most profitable strategy no matter how large the system becomes. In this sense, Walrus treats growth not as a stress test, but as a reinforcing loop. More data brings more stake. More stake brings more security. More security attracts more serious users. That cycle is what allows decentralized storage to move from experimental infrastructure into long-term economic foundation. That is how Walrus adapts as its network grows.