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Article originally published on Forbes.com. Image courtesy of Getty.
AI and edge computing have catalyzed both tremendous growth and tremendous complexity in networking and infrastructure.
Businesses are now operating in a multi-cloud, multi-carrier, multi-continent, multi-SaaS environment. Zero downtime and global reach are becoming the default expectation for your leaders, board members and customers alike. Human workers are inherently limited in their ability to observe, analyze and manage data flows across global networks. As disruptions and threats move faster today than humans can respond, we can’t rely on manual processes alone to protect digital businesses.
Multi-cloud edge architectures are inherently distributed. AI augments unpredictability and risk. Complex risk factors, including increased volatility, threat surfaces and application demands, are a growing burden for business leaders to manage. According to data from a 2024 KPMG global survey, “CEOs view cybersecurity as the top threat to businesses over the last decade.”
I see an urgent need for organizations to build a more autonomous infrastructure at the edge, optimized for resilience, security and performance. It can act to solve a problem before humans have even seen that there is a problem. In my experience, successful autonomous edge systems are designed around three key pillars; they are self-healing, self-optimizing and self-securing.
An autonomous edge network should be self-healing, meaning that it automatically detects and resolves failures, such as carrier instability, link loss, hardware degradation or BGP route flaps, without human intervention. It also localizes and isolates failures to prevent cascade effects. For example, if you have a temporary network failure in Los Angeles, autonomous rerouting immediately shifts traffic from L.A. to Phoenix. Your customers have no idea that their data took a different path than usual, and your business has no interruption in traffic or sales.
An autonomous edge network must be self-optimizing, able to adapt automatically to changing conditions. It continuously monitors and adjusts routing paths based on real-time telemetry, making sure that traffic to your application or service is using the best interconnects.
Another important part of self-optimization is the ability to make changes based on cost-efficiency, performance and customer-specific profiles. Because my company works across so many different geographic regions, I see interesting data patterns on where costs are rising—and how they are affected by economic and geopolitical factors. Just in the last month, I’ve seen customers encounter last-minute additional fees in vendor contracts related to new tariffs and energy cost increases. I predict that a broader definition of self-optimization, focusing more heavily on cost-effectiveness, performance and personalization, will be increasingly important in the next year.
An autonomous edge network has self-security at its core, providing real-time threat detection of different flows, volumetric signatures and behavioral deviations and responding on the edge. It automatically identifies signs of an attack, shares necessary information with your applications and services and acts to minimize any negative impact.
For instance, if an autonomous network detects potential malicious traffic in your e-commerce store, it limits and quarantines that traffic while allowing legitimate customers (those with normal behavioral patterns) to shop without interruptions. The goal is to reduce reaction time from minutes to milliseconds.
When do you trust automation, and when should you require some sort of human oversight in a process? There is no simple answer to this question. It can change depending on market shifts or your business objectives, risk tolerance or industry compliance requirements.
Instead of looking for a hard-and-fast rule, learn to weigh the tradeoffs of autonomous versus manual systems. Make it part of your organizational culture to have an ongoing dialogue about governance and guardrails in autonomous systems. How much authority does the system have? When do you need a human in the loop? How can you use people as a force multiplier for technology? How do you manage compliance, auditability and explainability?
Leaders often wait too long to migrate from manual to autonomous systems, then risk getting left behind by their competitors. But you don't have to adopt an autonomous edge network overnight. Make small changes, then build gradually. I’ve found that the following six steps are critical to a successful migration.
Do a full audit of your business’ dashboarding and reporting tools to consolidate all of your data in a single source of truth. Assess the services you’re paying for and the partners you’re working with before making any changes. What is moving you toward your business goals, and what is not?
Use historical incidents and baselines to teach the system how to recognize normal and abnormal conditions. If a major cloud outage affected your business, for example, how can you use that information to train an autonomous network to prepare for future outages? What performance baseline do you need to maintain for your own services?
Categorize network actions on the spectrum of low to high risk—and start automating low-risk actions, such as automated failover, health checks, traffic shifting and basic edge security functions. Celebrate early wins to build trust on your team and show the value of your work so far.
Define the boundaries of what a system can and can't do. Implement approval workflows for higher impact decisions, and test full automation of lower impact decisions. If you can automate an action that optimizes latency without affecting the availability of your services, for instance, this is likely a low-risk, high-reward use case.
Autonomous networks aren’t self-governing; they still need to be supervised and refined over time. Build visibility and explainability into your ongoing monitoring policies, and treat them as living, breathing documents.
If you want to be competitive, treat autonomy as transformation. This is the future. We are in a transformative time, and technology will continue to play a bigger role in our lives. Some leaders I speak with are wary of this transformation, and their fear holds them back from acting. But you can be a leader who embraces transformative technology and finds ways to apply it to your business.
I believe that organizations will increasingly rely on self-healing, self-optimizing and self-securing autonomous edge networks in the next few years. And leaders and organizations that embrace that shift now will be in place to lead in the next decade of global digital experiences.
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