By: Teresa Monteiro, Walid Wakim

Demand for bandwidth has continued to surge with cloud-based applications and 5G; in tandem, optical services have become more dynamic and stringent in terms of required service levels.

The rise of AI creates a force multiplier, with network operators expecting it to drive significant traffic on their transport networks. But the high-throughput, low-latency, and reliability requirements of AI workloads are taking network scale and complexity to another level. Operators are now facing unprecedented pressure to deliver more, faster, and better.

On the one hand, they are expected to accelerate service turn-up and enhance end-customer experience; on the other, they must maximize returns on infrastructure investments and be ready to support emerging revenue-generating services.

Manual network management processes used for configuring and monitoring largely static optical networks are now insufficient to meet new, more dynamic connectivity challenges required in this AI era. Resulting in AI-ready optical networks requiring rapid and efficient service fulfillment and flexibility to offer different service types based on requirements, such as latency or resilience. In response, webscalers have led the network automation efforts, providing approaches that the broader industry can adopt.

The opportunity is clear — automation has the potential to reduce errors, simplify operations, accelerate response times, and unlock new efficiencies. Paired with mature enabling technologies, the benefits are there for those prepared to seize them.

The pressure to evolve

A 2024 Heavy Reading survey on “Open, Automated, and Programmable Transport Networks” highlights the growing importance of network automation. Increasing network complexity and scale drive the need for advanced automation techniques that abstract the underlying infrastructure details and simplify network operation.

Optical network automation is no longer a future goal but a present necessity.  According to the survey, only a minority of operators continue to operate in a fully manual fashion.  Instead, most describe their level of network automation as ranging from “assisted management” to “partial automation,” with systems that make meaningful recommendations using a wide range of real-time data and advanced analytics.

The organizations that have implemented transport network automation reported significant benefits, including reduced human error thanks to more consistent processes and simplified operations with fewer manual interventions. Additional benefits include faster service activation, accelerating time to revenue, and optimized infrastructure usage, with improved capacity utilization and a higher return on investment.

The industry is focused on advancing network automation, and, according to Heavy Reading, operators are planning to move toward highly autonomous networks over the next three years.

Ready to deliver real results

Technological advancements made over the last decade are enabling automation to fulfill its promise, making the goal of automating more achievable than ever. For years, network automation was held back by fragmented management systems, proprietary interfaces and workflows, as well as limited visibility into network performance. Today, those barriers are being rapidly reduced with the appropriate automation frameworks.

Automation frameworks provided by standardization bodies and industry initiatives, such as OpenConfig’s common data models and the Linux Foundation’s Transport API (TAPI), have matured after undergoing extensive development and testing. 

These frameworks enable uniform communication between network elements and controllers, as well as between different automation domains. Modern optical networking equipment supports vendor-agnostic data models and open APIs,