In the early commercial Internet, some of the most strategically valuable locations were those that combined network access, fiber connectivity, and proximity to established Internet infrastructure. It was the place where another network already existed, because every new connection reduced the distance between customers, carriers, content providers, and other networks. That logic created a different kind of real estate economics, where physical proximity became a mechanism for reducing network friction rather than simply a way to shorten a construction schedule. Once that concentration formed, a new site had to compete not only on land economics but also with the accumulated connectivity surrounding the existing network cluster. Northern Virginia became one of the clearest examples of that process, while the South Bay developed a related model around the dense concentration of technology companies, carriers, exchanges, and network routes.

Fiber Intersections Became Commercial Gravity

The early Northern Virginia story began with networks looking for practical places to exchange traffic, and that requirement gave physical infrastructure a new commercial role. MAE-East emerged in the early commercial Internet era as an exchange environment in Northern Virginia, with its roots in network interconnection around the Washington metropolitan area. Its importance came from the fact that networks could reach one another without building entirely separate paths between every participant, making the exchange itself a valuable piece of infrastructure. The surrounding fiber routes then became more valuable because they provided access to an expanding population of networks that had already chosen to interconnect in the same region. When additional network operators arrived, the original location became more useful rather than less useful, because each participant increased the potential connectivity available to the others.

Ashburn inherited that momentum as network activity moved toward more scalable and commercially oriented interconnection environments. The transition from the original exchange architecture toward carrier-neutral environments did not erase the geographic advantage created by the earlier network concentration, because the participants themselves carried their connectivity requirements into the new ecosystem. A location that already had dense fiber access could therefore support a broader range of interconnection choices than an otherwise comparable site starting from scratch. This mattered because customers increasingly wanted direct relationships with networks, content providers, cloud services, and other connected parties rather than relying on a single upstream path. The commercial value of the site consequently became increasingly associated with the range of network connections that could be established from it.

The Exchange Became More Valuable Than the Site

The next stage of the Ashburn effect came when interconnection itself became part of what customers were buying from a data center. Space and power remained necessary, but they did not fully explain why certain locations attracted a growing concentration of networks and digital services. A customer entering a dense interconnection environment could establish relationships with multiple networks from a common location, reducing the need to build independent physical paths to each one. Cross-connects transformed that possibility into a tangible service, allowing parties within the same environment to establish direct physical links between their systems. As the number of available counterparties increased, the value of entering that environment also increased because a new customer gained access to more potential connections from the same starting point. The resulting economics favored locations where interconnection could compound rather than locations where infrastructure had to be assembled independently for every new customer.

That model also changed the meaning of carrier neutrality. A carrier-neutral environment could host multiple network operators without forcing customers to depend on one network architecture, allowing the site to function as a meeting point between competing and complementary connectivity providers. The more diverse the network population became, the more useful the location became for customers with different routing requirements. A content provider could use one connection for one relationship and another for a separate relationship without relocating its core infrastructure. A cloud connection, private network, content delivery path, or direct peering arrangement could therefore become part of the same physical ecosystem. The site accumulated commercial value because its connectivity options expanded with every additional participant. That mechanism helped turn interconnection from a supporting feature of data center real estate into one of the central reasons customers selected particular locations.

Santa Clara Followed a Related Network Logic

Northern Virginia was not the only market where connectivity concentration shaped data center geography. Santa Clara developed within a technology corridor where fiber infrastructure, data centers, and connections to Silicon Valley exchange points supported a concentrated connectivity environment. The South Bay’s existing technology ecosystem meant that network infrastructure did not arrive in isolation, because it developed alongside companies whose operations depended on rapid access to other networks and digital services. Local fiber infrastructure reinforced that position by connecting the city into broader exchange points across the Silicon Valley region. The result was a location where existing network infrastructure provided new participants with access to an already connected environment. Santa Clara therefore demonstrates a broader principle: interconnection advantage can emerge from the interaction between fiber geography and the concentration of organizations that need to exchange data.

This history matters because it changes how the traditional data center location question should be interpreted. A site with cheaper land could appear attractive when evaluated through construction economics alone, yet the comparison could change when network access became part of the customer’s operating model. A dense interconnection market reduced the amount of physical infrastructure required to reach important counterparties and created more options for routing, peering, and service delivery. The advantage accumulated gradually, which made it difficult for a new market to reproduce through construction spending alone. Legacy hubs effectively carried a form of network memory, because previous deployments had already created routes and connection points that new customers could use. The result was a self-reinforcing location advantage that persisted even as individual exchange technologies changed. Understanding that mechanism is essential before examining why new fiber routes and distributed architectures are now beginning to loosen the same geographic concentration.

Interconnection Density As Strategy, Not Just Network Architecture

The economics of a dense interconnection market became more powerful when customers stopped viewing connectivity as a background utility and began treating it as part of the location itself. A data center could offer secure space and reliable power, yet those attributes did not automatically reproduce the network relationships available inside an established connectivity cluster. Cross-connects created direct physical paths between networks, cloud platforms, content providers, and other connected systems, allowing customers to build relationships without extending every connection across an external route. That structure made the surrounding ecosystem part of the site’s commercial proposition rather than a separate telecommunications consideration. As more networks entered the same environment, customers gained additional choices without having to move their core infrastructure. The result was an interconnection economy in which network density could influence location decisions alongside land economics.

Cross-Connect Economics Changed What Customers Bought

Cross-connects mattered because they converted network proximity into an immediately usable technical relationship. A customer did not simply gain access to a building when entering a dense connectivity environment; it gained a pathway toward other systems already present in that environment. That pathway could support private peering, direct network access, cloud connectivity, or links between separate systems that needed predictable communication. The value therefore came from reducing the physical and commercial effort required to establish those relationships elsewhere. A less expensive site could still provide ample room for equipment, but it could not automatically recreate the same collection of counterparties within reach of a direct connection. This made interconnection density a strategic property of the location rather than a secondary feature attached to the building.

The economics became stronger as network participants accumulated around the same geography. A new entrant could connect to an existing ecosystem instead of building an independent route toward every important network relationship, while an incumbent participant gained another potential connection without leaving its established position. That reciprocal benefit encouraged additional network presence and gave existing locations a continuing advantage over isolated alternatives. The network effect did not require every participant to communicate with every other participant, because the availability of multiple interconnection options increased the usefulness of the environment. Carrier diversity also mattered because customers could design connectivity around different providers rather than treating one route as the only available path. Over time, the physical concentration of networks therefore became an operating advantage that could influence where digital infrastructure was deployed.

Carrier Neutrality Turned Density Into A Platform

Carrier neutrality strengthened the model because it allowed multiple network providers to coexist within the same physical environment. Customers could choose among connectivity options rather than accepting a location tied to a single network architecture. That choice became particularly important as digital infrastructure diversified beyond traditional enterprise traffic into cloud access, content distribution, private networking, and increasingly distributed application architectures. A dense site could support several relationships from one physical position, giving customers more flexibility as their traffic patterns changed. The commercial proposition therefore shifted from simply providing a connected building to providing access to an ecosystem of network choices.

Carrier neutrality also changed the way customers thought about future connectivity. A site did not have to predict every network relationship that a customer might eventually need if the surrounding ecosystem could accommodate new providers and new connections. That flexibility reduced the risk associated with selecting a location whose current connectivity profile looked adequate but might become restrictive later. Network choice became an architectural option that could be exercised as requirements evolved. The resulting value included network optionality, because a customer could establish new relationships within an existing interconnection environment without undertaking a fundamental relocation. This made dense interconnection environments particularly attractive to businesses whose network requirements continued to change.

Content Density Reinforced The Network Effect

Content distribution added another layer to the interconnection economy because traffic increasingly needed to move toward users rather than only between traditional network cores. When content, networks, and service providers concentrated in the same metropolitan environment, direct interconnection could reduce dependence on longer external paths. The resulting ecosystem made the location useful to parties that wanted efficient access to a broad set of networks without creating separate physical arrangements for each relationship. Content distribution could reinforce network density by creating additional reasons for networks and service providers to connect within the same metropolitan environment. The two forces could develop together without requiring a single organization to control the entire ecosystem.

That feedback loop also explains why established hubs could remain commercially important after the original Internet exchange structures changed. The physical exchange point might evolve, move, close, or be replaced, but the surrounding ecosystem could retain its value through new interconnection environments and additional network routes. Participants had already established relationships in the region, while new entrants could access those relationships through successor infrastructure. This gave the broader metro area a form of continuity that individual buildings could not provide on their own. The resulting location advantage depended less on a particular exchange and more on the accumulated density of networks, routes, services, and customers across the surrounding geography.

Why Latency Clustering Outpriced Land Economics

The economics of network proximity became more visible as applications moved from isolated systems toward distributed architectures that depended on frequent communication between locations. A workload could reside in one building while users, databases, storage systems, content caches, and supporting services operated elsewhere, making the quality of the paths between those components increasingly important. The value of a location therefore extended beyond the equipment installed inside its walls, because the surrounding network determined how efficiently that equipment could communicate with the rest of the digital environment. A site close to a dense connectivity cluster could participate in those relationships with fewer physical extensions and fewer network dependencies than an isolated site. This created a period when developers could accept higher real estate costs because the location delivered network utility that cheaper land could not reproduce immediately.

Proximity Became A Workload Variable

Latency became strategically important when application architectures began treating geographically separated components as parts of one operating system rather than independent services. Replication, content delivery, cloud access, storage synchronization, and private network connections all created situations where the distance between systems could influence application behavior. The relevant distance was not simply the mileage between two buildings, because routing paths, network equipment, congestion, and interconnection arrangements also shaped the effective path experienced by traffic. A location inside a dense network environment could therefore provide access to shorter or more direct paths than a site that looked geographically close but lacked comparable connectivity. This made proximity a technical property that depended on network architecture as much as physical geography.

The same pattern now appears in AI inference, although the workload characteristics have changed substantially from earlier Internet applications. Production inference increasingly involves movement between users, application layers, private data, model services, retrieval systems, and supporting tools, which can create multiple network paths inside a single interaction. Current architecture guidance from several infrastructure providers emphasizes placing inference closer to users and data when latency, data movement, or regional requirements make centralized processing less suitable. That does not eliminate centralized compute, because large model training and some inference workloads still benefit from concentrated resources. It does, however, make the metro network itself more important because the relevant architecture can span several locations within one urban area.

The Premium Was Really About Network Reach

The historical value attached to legacy hubs was therefore not simply a matter of being physically close to another building. It represented access to an existing network of routes, counterparties, exchanges, carriers, content providers, and cloud connections that could support many different traffic patterns. A customer entering such an environment could establish connectivity through an existing ecosystem instead of waiting for an entirely new network structure to emerge around an isolated site. That reduced the strategic uncertainty associated with future connectivity requirements, because the location already offered several paths toward external systems. The commercial value came from having options available at the moment they were needed rather than paying only for the theoretical possibility of obtaining them later. This helps explain why cheaper land often failed to displace established hubs even when construction economics appeared favorable.

The long-standing hierarchy began to change when network operators could extend high-capacity routes into secondary markets without requiring those markets to reproduce the entire historical ecosystem before becoming useful. Long-haul networks increasingly connected metropolitan clusters through diverse routes, while metro networks created additional paths between emerging sites and established interconnection centers. A new location could therefore remain physically outside a legacy hub while gaining access to networks and services connected to that hub through long-haul infrastructure. The effective boundary of the old cluster began moving outward as connectivity reached locations that once sat beyond the practical radius of dense interconnection. This process does not make distance irrelevant, because network paths still introduce latency and operational dependencies, but it changes which distances matter most. The location advantage can increasingly extend beyond the dominant hub toward locations that connect efficiently into a broader network of hubs and corridors.

Long-Haul Diversity Is Redefining What Proximity Means

For much of the legacy data center market, proximity meant physical closeness to a dominant interconnection cluster. That definition becomes less rigid when long-haul networks offer diverse paths into established metros and when secondary markets gain their own local connectivity ecosystems. A site can sit outside the traditional center while still reaching major network destinations through dedicated transport and diverse entrance paths. This changes the geography of interconnection because the relevant question becomes how a site connects to the network rather than whether the site sits inside the historic hub. Modern fiber planning can therefore create intermediate locations that combine local infrastructure with access to major metropolitan markets.

Diverse Routes Expand The Effective Hub

Long-haul diversity changes location economics by allowing network planners to separate physical geography from logical connectivity. A new site does not need to sit directly inside an established hub if it can reach that hub through robust and appropriately diverse transport paths. The availability of routes between major metropolitan markets also gives secondary locations a way to connect into broader ecosystems without replicating every network function locally. Eastern Pennsylvania illustrates this pattern, with fiber infrastructure connecting the corridor toward New York, New Jersey, and Philadelphia while supporting access to major cloud connectivity options. Such architecture gives emerging locations a network position that extends beyond their immediate local market.

The significance of that development goes beyond the existence of another fiber route. Multiple physical paths can reduce dependence on a single geographic corridor and allow operators to design connectivity around route diversity rather than simple proximity. A location can therefore sit outside a traditional hub while maintaining several network relationships into that hub and other markets. The result is a wider connectivity field in which the boundary between primary and secondary locations becomes less rigid. Long-haul infrastructure effectively turns some previously peripheral sites into connected extensions of established metropolitan ecosystems. A site then participates in two layers of connectivity at once: a local ecosystem serving nearby customers and a wider transport system reaching other metropolitan markets.

Fiber Extensions Are Moving The Boundary

The emergence of diverse long-haul routes also changes how network operators evaluate the physical boundary of a metropolitan market. A location that previously sat outside the practical reach of dense interconnection can become viable once fiber reaches it through multiple paths and provides direct access to established network destinations. That process does not recreate the full density of the original hub, but it can provide enough connectivity for a new market to serve workloads that do not require physical adjacency to every major network participant. Eastern Pennsylvania provides a current example of this model, where metro fiber connects emerging locations toward established connectivity centers while supporting distributed workloads.

This shift also introduces a more nuanced definition of proximity for C-level infrastructure decisions. Physical distance still affects latency, but network diversity, route quality, local interconnection, and access to major markets can determine whether that distance creates a meaningful operational disadvantage. A site connected through several well-designed routes may offer greater resilience and network flexibility than a site that sits closer to a major hub but depends on fewer physical pathways. The competitive question therefore moves from “How close is the site?” toward “How efficiently and diversely does the site connect?” That change is one of the clearest mechanisms through which the historical location moat can weaken while interconnection itself remains strategically important.

From Hub Concentration To Corridor Formation

The geography of digital infrastructure is beginning to look less like a collection of dominant nodes and more like a connected field of markets. Legacy hubs still hold substantial interconnection value, but the network surrounding them increasingly extends into adjacent regions through long-haul routes, metro fiber, carrier-neutral sites, and direct connections between secondary markets. That expansion creates additional options for locations that can maintain strong network relationships with the hub without sitting inside its most concentrated zone. The resulting corridor can contain several sites that exchange traffic directly while also maintaining access to larger network ecosystems farther away. This structure creates a broader form of density in which connectivity spreads across geography without losing its commercial usefulness. Recent network deployments in the Mid-Atlantic illustrate how regional fiber systems can connect secondary markets directly with Northern Virginia and other established connectivity locations.

Corridors Are Becoming The New Network Unit

The corridor model begins when several connected locations develop enough local capability to support traffic without routing every relationship through one dominant center. A site in an emerging market can connect to nearby sites, reach a larger metropolitan exchange, and maintain diverse long-haul paths toward other regions. That architecture reduces the need for every workload to sit inside the historical hub while preserving access to the services that made the hub valuable in the first place. Network operators can consequently design around a sequence of connected markets rather than a single geographic destination. The economic significance of the corridor can expand as new sites, routes, and customers become connected. The underlying interconnection advantage survives, but its physical expression becomes more distributed.

Northern Virginia itself now provides evidence of this broader structure because interconnection can extend across several carrier-neutral locations rather than depending on a single building or exchange point. A network can participate across multiple sites within the region while retaining access to peers across that wider environment. The architecture demonstrates how interconnection density can become metropolitan rather than building-specific. Once that model extends beyond the traditional center, the definition of a hub becomes more fluid because the relevant network community can occupy several connected locations. The market still benefits from concentration, but concentration no longer requires every participant to occupy the same immediate geography. That evolution provides a bridge between the old hub model and the emerging corridor model.

Pennsylvania, Boston And Denver Illustrate The Shift

Evidence of corridor formation is visible where connectivity links emerging sites with established metropolitan centers without requiring every deployment to occupy the historical core. Pennsylvania offers one example because regional fiber infrastructure can connect locations toward New York, New Jersey, Philadelphia, and other major markets while supporting local connectivity requirements. Boston presents another type of corridor opportunity because its position within the Northeast network geography allows infrastructure to participate in relationships extending toward New York and other established markets. Denver occupies a different geographic position, while regional network infrastructure connects the market with broader connectivity ecosystems. These markets do not need identical histories to participate in the same structural transition.

The important factor is not whether every secondary market becomes another Ashburn or Santa Clara. That outcome would simply reproduce the old concentration pattern in another place and would miss the structural change taking place in network architecture. The emerging model instead allows different markets to specialize while remaining tightly connected to one another. One location may offer access to a large customer population, another may provide land and power availability, while another may serve as a network exchange point for regional traffic. Long-haul connectivity allows those strengths to operate together rather than forcing every requirement into one metropolitan cluster. The corridor therefore becomes a distributed economic unit assembled from complementary locations.

The Early Signals That The Moat Is Thinning, Not Collapsing

The weakening of the legacy location moat should not be confused with the disappearance of interconnection economics. The stronger signal is that customers can increasingly obtain valuable network relationships from more locations than before. Secondary peering environments, metro connectivity, regional fiber routes, and distributed AI architectures are creating additional places where traffic can exchange efficiently. The market therefore retains its preference for density while becoming less dependent on one physical concentration of density. That is why the current transition looks gradual rather than disruptive. The moat remains strongest where networks, content, clouds, and customers continue to converge, but the number of places capable of supporting meaningful convergence is expanding.

Secondary Peering Is An Early Warning Signal

Growth in secondary peering can indicate that connectivity value is becoming available beyond legacy centers. An exchange environment does not need to rival the largest historical hub to become useful, because a regional community can benefit when networks establish direct relationships closer to their customers and traffic sources. Each additional local peer can reduce the need for traffic to travel through a distant exchange, particularly when the applications involved have strong regional demand. As more networks participate, the secondary environment gains a larger role in the surrounding digital architecture. That process creates a smaller but increasingly meaningful version of the network effect that originally strengthened the major hubs.

The network implication is significant because distributed inference changes the shape of traffic rather than simply increasing its volume. A production AI application can involve several interconnected components, including user access, data retrieval, model execution, application logic, and supporting services. Those components can occupy different locations when architecture, power availability, data requirements, or regional considerations favor distribution. Network operators therefore face a system in which several data center locations must communicate efficiently instead of one center serving as the universal destination. Recent industry analysis describes AI inference as increasingly dependent on inter-data-center connectivity across multiple sites, reinforcing the movement toward distributed network architectures.

Metro Mesh Is Challenging The Single-Core Model

A metro mesh can differ from a hub-and-spoke model by allowing several locations to exchange traffic without making one location the center of every relationship. Such a mesh can include carrier-neutral sites, cloud connections, regional compute, inference resources, and enterprise networks distributed across the same metropolitan area. The connectivity value of each site can depend on the quality of its relationships with other sites, rather than solely on its distance from one dominant exchange. This structure can create meaningful density without reproducing the exact physical concentration that characterized earlier Internet markets. The architecture also allows workloads to move between locations as application requirements change.

This is why the early warning signs should be read as evidence of moat thinning rather than moat collapse. Legacy hubs still possess accumulated network relationships that newer locations cannot reproduce instantly, and major exchanges continue to attract participants because network density remains valuable. At the same time, distributed inference, regional peering, long-haul diversity, and metro interconnection give customers more ways to obtain useful connectivity without locating inside the historic core. The competitive boundary therefore expands outward while the core retains its role as an anchor. The strongest markets in the next phase may be those that combine legacy connectivity with the ability to extend that density into neighboring locations.

How Emerging Urban Markets Are Engineering Density Without Legacy

New markets can become relevant to modern workloads without reproducing the full historical development path of established network hubs. They can design connectivity as a foundational requirement from the beginning, using multiple carriers, open interconnection arrangements, diverse fiber routes, and direct relationships with regional network ecosystems. That approach differs from the historical model because connectivity is no longer something that develops only after customers arrive. Developers and network operators can coordinate the physical and logical architecture so that a new site enters the market with meaningful connectivity options already available. The approach is not necessarily to imitate the historical hub but to create a network position suited to current traffic patterns. AI infrastructure makes that approach more relevant because distributed workloads require connectivity between several locations from the outset.

Open Fabrics Can Accelerate Network Density

An open interconnection fabric gives a new market a way to aggregate network relationships without depending on one carrier or one physical location. Multiple providers can connect into the same regional ecosystem, allowing customers to select paths according to application requirements and resilience objectives. That structure can increase the usefulness of the fabric as additional participants establish connections with existing participants. A market can therefore create network value through architecture even before it accumulates the full historical concentration found in older hubs. The approach shifts the emphasis from inherited density toward designed density.

AI strengthens this requirement because modern inference architectures can involve geographically distributed compute and data resources. Current deployments and network strategies increasingly position AI infrastructure across regional and metro locations, with interconnection providing the mechanism that allows those components to operate as a coordinated system. The architecture can place inference closer to users and data while retaining connections to cloud, model, and data ecosystems. That creates a different form of density, where the critical asset is not physical concentration alone but the number of useful relationships that can operate across the network. Emerging markets can therefore develop connectivity around workload behavior rather than relying solely on historical network concentration.

AI Data Movement Is Creating A Different Kind Of Location Value

The location requirements of AI inference are helping redefine what customers need from an urban market. A centralized compute center can remain highly valuable for workloads that benefit from concentrated resources, but production inference can require infrastructure closer to users, data sources, and application systems. That creates demand for metropolitan locations that combine compute, connectivity, and access to regional networks. The value of the site therefore depends on how effectively it participates in a broader AI data movement architecture. A market with strong interconnection but limited access to users may serve one workload profile, while a connected urban location can support a wider range of distributed inference applications.

The emerging urban model therefore does not eliminate the historical importance of network density. It changes how density can be created, measured, and expanded. Legacy hubs accumulated connectivity through years of network decisions, while new markets can engineer connectivity as part of the initial architecture and extend it through regional corridors. AI inference makes this model particularly relevant because its traffic patterns reward proximity to users and data while also requiring strong links among distributed resources. The markets that succeed will not necessarily be those with the cheapest land or the largest single site, but those capable of creating a dense and extensible network environment around their available infrastructure.

Conclusion: Density Will Disperse, Not Disappear

The history of Northern Virginia and Santa Clara shows how interconnection became an important location advantage. Fiber intersections created the initial conditions, exchange points concentrated network relationships, and carrier-neutral environments converted those relationships into a durable commercial ecosystem. The resulting connectivity provided access to networks and services within an established interconnection environment. Land economics could influence development decisions, but connectivity shaped the customer’s ability to participate in the wider digital system. That accumulated network value created the location moat that defined much of the commercial Internet era.

Legacy Hubs Will Remain Anchors

The weakening of that moat does not make legacy hubs irrelevant because the network relationships built there continue to support customers across multiple applications. Established interconnection environments still provide access to dense communities of networks and services, while newer connectivity programs continue to expand the number of locations that can participate in those ecosystems. The important change is that connectivity once concentrated within established markets can increasingly extend into surrounding markets through regional fiber and metro connectivity. Legacy hubs can therefore remain anchors while network value becomes accessible across a wider set of connected locations. The market can preserve the center while expanding the network around it.

The most durable advantage will therefore belong to markets that can extend density rather than merely inherit it. A legacy hub begins with accumulated relationships, while an emerging corridor must create enough useful connections to attract the next layer of participants. Long-haul diversity, regional peering, metro meshes, and distributed AI workloads provide mechanisms for doing that without reproducing the original geography of the Internet. The result is likely to be a broader network of interconnected markets in which several locations share the value once concentrated in one dominant node. Interconnection density remains the moat, but the moat itself is becoming geographically wider and structurally more distributed.

The Future Belongs To Replicable Density

The next phase of data center geography may place greater emphasis on reproducing useful connectivity across several markets rather than concentrating every requirement within a single hub. A successful location will need access to diverse fiber, multiple network relationships, regional demand, and architectures capable of supporting traffic between distributed compute resources. Power and land will remain important because no network can operate without physical infrastructure, but those inputs increasingly compete within a larger system of connectivity requirements. Emerging markets may be better positioned when physical infrastructure and network architecture develop together rather than sequentially. That model gives customers more choice while preserving the strategic value of density.

The transition also means that the old definition of proximity is becoming less useful for strategic planning. Proximity once meant locating directly inside the dominant exchange ecosystem, while modern network design can create effective proximity through diverse transport, regional interconnection, and distributed compute. The physical distance between sites still matters, but the quality of the network connecting those sites can determine whether that distance becomes operationally significant. A well-connected secondary market can therefore compete with a legacy location for workloads that once required direct adjacency. The competitive question shifts from ownership of the historic center toward the ability to participate in a wider connected geography. Northern Virginia and Santa Clara retain the advantages created by decades of network accumulation, yet emerging corridors can now build meaningful density through deliberate fiber architecture and distributed workloads