Self-Healing Networks: How Are They Used in the Public Sector?

What Are Self-Healing Networks and How Do They Work?

As the name suggests, self-healing networks are “automated systems designed to detect, diagnose and resolve network failures in real time, without the need for human intervention,” says Loudon Blair, senior director of corporate strategy at Ciena.

“They can handle faults, bounce back quickly, and even adjust when demand suddenly spikes,” Blair says. “These networks continuously monitor their health and adapt or ‘heal’ in real time to keep services running smoothly.”

Consider a scenario in which the office internet service goes down.

“You have multiple internet connections coming in, and if you have a self-healing type of environment, it automatically channels from one to another source, with minimal if any downtime,” says ICMA CIO Hemant Desai.

Self-healing networks have big potential for IT teams.

“Imagine a network so intelligent that it identifies and fixes problems on its own,” says Matthew Dietz, Global AI Leader at Cisco. “That is exactly what self-healing networks are.”

These are “smart, proactive systems that continuously monitor their performance; swiftly detect disruptions or regularities; and immediately respond by dynamically rerouting traffic, adjusting configurations or isolating problematic components,” he says.

The Role of AI and Machine Learning in Self-Healing Networks

For state and local governments, AI and machine learning can play a key role in a self-configuring network, says Desai, who managed 200-plus servers in his previous role as CIO for Guilford County, N.C. “Imagine the amount of data,” he says. A human might spot an anomaly, “but not in real time, and not in a decent time frame.”

AI and machine learning are the engines behind self-healing networks, Dietz says. “These technologies will turn vast amounts of data into actionable insights, predicting network issues long before they become noticeable to users.”

AI-driven systems “rapidly pinpoint problems and automatically execute precise solutions,” he says. “This not only dramatically reduces downtime, but also continuously improves network performance, creating a smarter, more agile digital environment.”

Ciena’s Blue Planet platform, for instance, “uses AI-driven analytics to process vast amounts of network telemetry data, identifying anomalies like latency spikes or failing hardware before they cause outages,” Blair says.

Complementing this, digital twin networks — virtual replicas of physical networks — allow operators to simulate disasters such as hurricanes and damage to fiber routes, and to “test recovery strategies in a risk-free environment,” Blair says. “By continuously learning from past incidents, these systems refine their ability to predict and prevent failures, reducing downtime and improving reliability.”

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Benefits of Self-Healing Networks for State and Local Governments

With AI and other digital advances driving innovation, “self-healing networks empower state and local governments to deliver more reliable, efficient and responsive services to their communities,” Dietz says.

King County, Wash., for instance operates two network infrastructures: an internal LAN/WAN supporting 16,000 employees, and an institutional network for regional government and education organizations. Both utilize automated self-healing capabilities.

“These automations detect failures and route around by them utilizing redundant links, dynamic routing protocols, geographic isolation of physical paths and multiple service providers for direct peering,” says Mike McVey, a solutions architect for King County.

“Self-healing networks help services operate smoothly day to day,” McVey says. “In the event of a catastrophic failure such as a cyberattack or regional disaster, self-healing networks are crucial for quickly restoring business and life safety systems.”

Dietz, who previously served as CIO for Elkhart County, Ind., points to “the pressure that a lot of our government customers are under in terms of the amount of data that is being created and how to properly deploy networks to handle all of the data coming at them.”

In the age of AI and data-first thinking, “these networks now that are self-healing are vital to continuing the operations and making sure that they remain interrupted,” he says.

“The automated nature of self-healing networks reduces operational costs and allows state and local IT teams to shift their focus to reactive troubleshooting and proactive innovation,” he adds. “We’re going from reactive to more proactive mindsets.”

READ MORE: How State and local governments can best prepare for natural disasters.

How Self-Healing Networks Improve Resilience During Emergencies

“During emergencies, self-healing networks prioritize continuity by leveraging redundant mesh architectures and AI-driven prioritization,” Blair says.

Amid a natural disaster or other crisis, when resilient communications are essential, “real-time monitoring quickly isolates faults to prevent wider network failures,” he says. “This capability is especially important in regions prone to severe weather or natural disasters that can damage network equipment.”

In these types of situations, “every second counts, and connectivity becomes a lifeline,” Dietz says. “Self-healing networks are specifically designed to thrive under pressure, automatically adapting to maintain uninterrupted communications even when facing severe disruptions or, potentially, physical damage.”