What is Distributed Cloud?

Distributed cloud: definition and core principles

At its core, distributed cloud is the application of cloud computing technologies to interconnect data and applications across multiple geographic locations.

While standard cloud computing relies on centralized regions (massive data centres located in specific zones), distributed cloud extends these public cloud services to different physical locations.

How distributed cloud differs from traditional cloud models

The traditional public cloud model is centralized. While this offers immense scalability, it creates an almost air-gapped distance between the connected data source (users, IoT devices, local servers) and the processing power.

Distributed cloud inverts this dynamic. It allows the public cloud provider to run their software stack on hardware located outside their primary regions.

Distributed cloud vs hybrid cloud vs multi-cloud

Because distributed cloud is based on an on-premise cloud platform and edge environments, it is often confused with hybrid or multi-cloud connected setups. The difference lies in who manages the infrastructure and the consistency of the software stack.

• Distributed cloud vs. hybrid cloud: Hybrid Cloud typically involves a "do-it-yourself" integration of a private cloud (managed by the customer) and a public cloud (managed by the provider). Distributed Cloud is a single, consistent software stack managed entirely by the cloud provider, even when it runs in the customer's own data centre. It is not two clouds connected; it is one cloud extended.
   
• Distributed cloud vs. multi-cloud: Multi-cloud is the strategy of using services from two or more different cloud providers. Distributed Cloud usually refers to a single provider's services running in multiple locations. However, a distributed architecture can enable a multi-cloud strategy by allowing different clouds to interact more seamlessly at the edge.

Distributed clouds are delivered by decoupling the control plane (management and governance) from the data plane (physical execution and storage). In this architecture, the public cloud provider retains central authority over the connected control plane while physically dispersing the data plane infrastructure to wherever the customer needs it.

To support this, providers deliver specialized infrastructure nodes to these distributed locations. These nodes are tethered to the central cloud for instructions and governance, but are based on the local compute power to process data independently in real-time.

While often used interchangeably, it is important to learn that distributed cloud and edge computing are distinct concepts that share a symbiotic relationship. It is most accurate to view edge computing as the physical location where processing happens, and distributed cloud as the operational model that makes managing those locations possible.

Edge computing defines the "where." It refers to the philosophy of moving workloads out of centralized data centres and closer to the source of data generation.

Distributed cloud provides the end and the "how." It acts as the connected delivery vehicle for edge computing, extending the consistent services, APIs, and governance of the public cloud out to these edge locations.

Key use cases for the distributed cloud

Because distributed cloud is based on processing power that we deliver to the exact location where it is needed, it unlocks scenarios that were previously difficult or impossible with a purely centralized cloud model.

• Intelligent manufacturing and IoT: Modern factories generate terabytes of data daily from sensors and robotic arms. Sending all this data to a central cloud for analysis creates lag and consumes massive bandwidth.
   
• Telecommunications and 5G networks: Telcos use distributed cloud capabilities to virtualize their networks (vRAN) and deploy Multi-access Edge Computing (MEC). By placing cloud infrastructure at cell towers or aggregation points, they can offer ultra-low latency services to their subscribers.
   
• Content delivery and cloud gaming: For media streaming and cloud gaming, milliseconds matter. Distributed cloud enables providers to host rendering engines and content caches in local metros rather than distant regions.
   
• Regulated finance and healthcare: Banks and hospitals often operate under strict data residency laws that forbid sensitive customer, pricing, or patient data from leaving a specific jurisdiction. Distributed cloud allows these institutions to use public cloud services for agility and analytics while physically storing and processing the sensitive data within compliant, local facilities or even on-premises data centres.

Adopting a distributed cloud architecture delivers tangible operational and economic advantages beyond just performance improvements.

One of the biggest hurdles in end-user IT is "tool sprawl", where solutions are based on different software for private data centres, public cloud, and edge devices. Distributed cloud eliminates this by providing a single set of tools, APIs, and governance standards across all environments. IT teams can manage thousands of disparate locations through one interface ("single pane of glass"), significantly reducing overhead and complexity.

Also, with distributed cloud, a connected application built for the central cloud can be deployed to an edge node without modification. This "build once, deploy anywhere" capability speeds up time-to-market and allows engineering teams to focus on features rather than infrastructure compatibility.

Finally, transmitting vast amounts of raw data from the edge to a central cloud is expensive in terms of pricing (egress fees) and bandwidth-intensive. By processing and filtering data locally using distributed cloud nodes, organizations only need to send the final insights or summaries to the central cloud.

While distributed cloud offers significant advantages, it introduces a layer of operational complexity that organizations must carefully manage. The most immediate challenge is the sheer scale of infrastructure endpoints.

Unlike a centralized model where resources are consolidated in a few massive, provider-managed facilities, a distributed cloud involves managing hundreds or even thousands of micro-nodes spread across diverse locations.

Connectivity and offline survivability also represent critical considerations. Distributed cloud relies heavily on the tether between the central control plane and the edge nodes for updates, monitoring, and security patching.

As a last point, physical security shifts from being solely the connected provider's responsibility to a shared concern. In a traditional public cloud region, the provider guarantees military-grade end-to-end physical security with biometric access and 24/7 surveillance. In a distributed model, an edge node might sit in a server closet at a branch office or a cabinet on a factory floor, making it far more vulnerable to theft, tampering, or environmental hazards.

OVHcloud is based on a distributed cloud with a philosophy grounded in freedom, interoperability, and strict data sovereignty. Rather than locking users into a proprietary "walled garden," the ecosystem is designed to extend the open standards of the cloud to wherever the data resides, whether in a hyperscale region, a local metro, or an isolated on-premises rack.

To solve connected latency challenges, OVHcloud complements its global network of hyperscale regions with Local Zones. These are smaller, strategically placed deployment points located closer to end-users in major metro areas.

For the most sensitive environments, such as defense or critical infrastructure, OVHcloud provides the On-Prem Cloud Platform. This solution brings the cloud management layer directly to the customer’s facility and is capable of operating in a fully disconnected or air gap mode.