Is Autonomous Networking Just Hype?

  • Cars that drive themselves.
  • Facial recognition that controls doors at research facilities and factories.
  • Organs available for transplants at the right time for the right patient.

These are real-world capabilities that autonomous networking can and does enable.

An autonomous network is a network that can run with minimal or even no human intervention. It can configure, monitor, maintain and secure itself in perfect alignment with a government agency's policies, goals or strategies.

"IT leaders should consider an autonomous network as a way of modernizing the network, so it's optimized for digital businesses."
-Digital Transformation Requires an Autonomous Network

For any organization, including local and federal government departments or agencies, the "network" is a critical enabler of employee productivity and efficiency, business continuity, and customer (aka "constituent) focus. But to keep up with the evolving economic, political, business, and social landscape, these entities need to think past slow, manual, expensive and insecure legacy networks and embrace autonomous networks.

But even if total autonomous networking is "the next evolutionary step in networking," is it worth the hype?

How are Autonomous Networks Different from Automated Networks

An autonomous network is not synonymous with an automated network, even though the two terms are often interchangeable.

Automated systems are typically restricted in the tasks they can perform. Moreover, all their actions and decisions are based on pre-defined parameters or conditions that are geared towards repeatedly performing specific functions as efficiently as possible.

On the other hand, an autonomous network pretty much runs itself because it adapts to its environment and learns from its data. For example, AI and Machine Learning can quickly learn from increasing datasets faster and more reliably than humans. Autonomous systems also evolve as the environment changes and ensure that operations remain optimal, secure, and well-aligned with business goals. In short, autonomous networks are adaptive, agile and programmable – particularly with a software-defined implementation approach.

When is an Autonomous Network "Superior" to an Automated Network

Autonomous networks can provide more complex processing capabilities and are often considered "superior" to an automated network. However, such comparisons should only be made in the proper context.

An automated network with well-defined inputs and outputs is ideal when predictability, repetition, and efficiency are required. So it is best when manual or everyday tasks related to the configuring, testing, deploying and operating of physical and virtual devices need to be controlled and managed. Moreover, its simplified network architecture is easier to maintain and provides good network service availability. It can also minimize human error and lower operating costs.

Autonomous systems are superior in non-deterministic environments where all conditions cannot be tested ahead of time, and there is a need to adapt or learn as conditions evolve. Such a network consists of an open ecosystem, closed-loop automation agents, software-driven infrastructure, intelligent decision engines, and analytics, which support greater learning and adaption, and enhance operations as the environment evolves.

Autonomous networks do more than optimize application performance, improve system reliability, predictability and efficiency, and ensure minimal downtime. However, the most significant advantage of an autonomous network is that it helps improve human experiences by leveraging the innovation capabilities of technologies like AI, 5G, Machine Learning, virtualization, and edge computing. And since it can learn and adapt on its own, it provides government organizations the flexibility and freedom to:

  • Leverage different networks, devices, apps and technologies to introduce new, innovative solutions for smart public transport and surveillance/safety systems
  • Centralize network management and enhance security against cyber attacks and data leaks. Here's how the City Government of Tamba in Japan did it!
  • Provide "Zero-X" experiences to users, e.g., zero-wait or zero-touch
  • Collaborate with digital partners to form robust, mutually-beneficial ecosystems like smart cities
  • Take advantage of new revenue opportunities

Autonomous Networking: Hype or Truth?

Autonomous networks are already used in multiple real-world applications, for example, network intrusion detection. Using ML, such networks look for anomalies like credential stuffing attacks to distinguish legitimate network traffic and block attempted attacks to endpoints invisible to traditional security tools. Autonomous systems can also block and disarm zero-day exploits before they execute, limiting the possibility of damage.

Autonomous networks are also used for compliance with Health Insurance Portability and Accountability Act (HIPAA). For example, suppose a hospital's policy dictates that all patient data must be kept in its own secure segment to comply with HIPAA. In that case, an autonomous network will ensure that this happens even if the environment changes. Such networks play a similar role in the retail and financial sectors, where compliance with PCI-DSS is required. So if a device moves out of the reach of a secure segment, the network will automatically redefine itself to protect customer data and ensure that the organization's policies continually meet business goals.

Autonomous networks with predictive management enable government IT teams to move out of inefficient "firefighting" mode. Instead, they get proactive notice with greater end-to-end network visibility before current or potential issues become an operational bottleneck. An autonomous network also supports NetDevOps principles, which helps align the network with the rest of the organization and speeds up application development and delivery.

Over time, networks will move towards total autonomy, ushering in a new era of more secure, efficient, easy-to-manage networking. Customizable autonomous networks will find numerous applications in medicine, healthcare, retail, automotive (self-driving cars!), transportation, and of course, government, as well as areas like cloud management, Knowledge-as-a-Service (KaaS), and the end-to-end automation of F5G networks.


Soon, questions around how autonomous networks are implemented, whether it is designed with "by default, always-on" security, and how it will potentially benefit users will remain important considerations. But networks will be granted greater autonomy over their actions and decisions, accelerating the move towards this technology. Therefore, it is clear that total autonomous networking is not hype but a reality – one that we are inexorably moving towards.

The Total Autonomous Networking solution from Allied Telesis provides automatic edge security, advanced intelligence, and easy network management. It enables organizations and governments to improve their decision-making and handle more complexity in the evolving operational landscape.

To implement total autonomous networking in your local, state or federal government organization, read this quick guide to get you started. Then, for more help leveraging its benefits, contact Allied Telesis today. Also, please look at our other local government solutions our self-defending network.