How do you evaluate the trade-offs between centralized and decentralized network architectures?

As with all architectures you need to design with resilience and diversity in mind. Proper failure mode analysis on critical control components is essential. In terms of Centralised control, as long as you have good resilience abstracting your control plane from your nodes allows you to do higher order functions such as path computation and this allows you to inject business intent in a software defined way.

Centralized architecture patterns are also visible in Application Architecture. Take monolithic applications as an example. Typically, a monolithic application has multiple functional components. In addition, the data persistence layer, data access layer, business processing logic involving compute are all developed within the same application. It leads to efficiency, and reliability but can be challenging to maintain, manage, scale and provide backup and resiliency.

As Colin alludes to, it is important to recognize that a network can be viewed as consisting of different layers - commonly “data plane”, “control plane” and “management plane” Different functions are performed at each layer, and each can be considered as being more or less “centralized” versus “distributed”. So one can have a centralized control plane with a distributed data plane. Is that a “centralized” architecture or a “distributed” one? Both I would say - it depends

Centralized networks are built around a single, centralized server/master node, which handles all major data processing and stores data and user information that other users can access. From there, client nodes can be connected to the main server and submit data requests instead of performing them directly. The majority of web services — including YouTube, a mobile app store, or your online banking account — are coordinated by a centralized network owner, meaning that all data transactions within these networks require verification via a third-party authority.

The early network controllers and SDN (Software Defined Networks) were based on centralized control, management, and data planes. This did not scale well because all data had to be handled through a centralized controller. Some still believe that for smaller-scale networks (buildings, campuses), high-bandwidth uplinks between core, distribution, and access layers with centralized control, management, and data planes are beneficial. However, most have shifted to a centralized control and management plane with a distributed data plane.

By contrast, a decentralized network distributes information-processing workloads across multiple devices instead of relying on a single central server. Each of these separate devices serves as a mini central unit that interacts independently with other nodes. As a result, even if one of the master nodes crashes or is compromised, the other servers can continue providing data access to users, and the overall network will continue to operate with limited or zero disruption.

Decentralized networks are made possible by recent technological advancements that have equipped computers and other devices with a significant amount of processing power and can be synced up and leveraged for distributed processing. However, while decentralized networks are substantially different from centralized networks, it’s important to note that decentralized networks do not distribute data storage and processing evenly across the entire network and still rely on main servers, albeit more than one per network.

If you orchestrate a decentralized architecture with automation platforms like Ansible and Terraform, and utilize a single source of truth like NetBox, you can maintain good control of the decentralized architecture as long as it is within your jurisdiction and management control.

Modern networks designed to support AI and cloud-based applications often use a hybrid approach that combines the benefits of centralized and decentralized architectures. In this context, Software-Defined Networking (SDN) introduces the idea of an agile network. SDN centralizes the control and management planes offering a holistic view of the network while allowing the data plane functionality be distributed across Network devices. This makes SDN the best industrial example for a hybrid model that aims to offer flexibility and efficiency in managing networks to meet the dynamic needs of today's world.

Every single device and IP (Internet Protocol) address within your control is part of your infrastructure. Today, this extends to the public cloud, over the internet, via VPNs, and Internet of Things (IoT) devices connected over private 4G/5G APNs. As long as you have security and juridical responsibility, it's part of your infrastructure. This is the true world of hybrid environments. You gain control by defining smaller domains (e.g., DC network, Campus network), setting security policies for each, and establishing integration policies for each connection.

Some other factors to weigh in are: -> simplicity vs scalability: Centralized architectures are simple to implement while the decentralized may fair a little less here but are very easy to scale. -> Consistency vs. Flexibility: Centralized systems offer consistency while decentralized offer more flexibility. -> Resource Efficiency vs. Redundancy: Centralized architectures may optimize resource allocation, while decentralized architectures may require more resources to offer redundancy and fault tolerance.

There are only two factors that should guide the choice for any infrastructure domain: requirements and constraints. Requirements will eliminate options that lack the needed functionality. Constraints will indicate which options you should avoid. There can always be something "better" – make sure you know your requirements and constraints, and the pieces will naturally fall into place.

Because distributed networks do not have a central server or a separate set of master nodes, the burden of data processing is crowdsourced across the network, with all users granted equal access to data. The decision-making process on a distributed network therefore typically involves individual nodes voting to change to a new state, and the final behavior of the system changes in accordance with the aggregate results of the decisions each individual node votes on. The specific processes by which a distributed network votes and makes decisions is contingent on the network’s consensus mechanism. All forms of distributed decision-making involve the network’s individual components interacting with one another in order to achieve a common goal.

A distributed network is similar to a decentralized network in the sense that it forgoes a single centralized master server in favor of multiple network owners. However, distributed networks are composed of equal, interconnected nodes, meaning that data ownership and computational resources are shared evenly across the entire network. The term “distributed network” is sometimes used to describe a network that is simply geographically distributed but may follow a top-down node hierarchy model. In most instances, though, the term refers to a network where node locations and computational resources are evenly distributed.

I remember rolling out IPT in the early days, when networks were still daisy-chained with hubs – it was a catastrophe. Some customers never returned to IPT. Similarly, with some of the early "Software Defined Networks" that had centralized management, control, and data planes, I had two very similar customers: for one, it worked perfectly, while for the other, it didn't. The takeaway here is that if it's bleeding-edge technology, make sure that you (or the customer) are prepared to try new and not yet matured technology.