AIOps: Maximizing Optical Network Reliability, Availability, and Capability

Increased automation is an ongoing objective of virtually every network operator. According to a 2024 Analysys Mason research report, there are five key drivers for optical network automation.
• Rapidly scaling bandwidth
• Streamlining network operations
• End-to-end management and control
• Optimizing network resources and
• Enabling new revenue generating services
There has never been a better time for power utilities to automate their expanding optical networks. Modern optical infrastructure increasingly supports common standardized data models and open APIs. Modular software ensure consistency enabled by years of development and testing of interfaces by industry consortiums such as the Linux Foundation’s Transport API. With widespread support for streaming telemetry, we have better access to more data from more sources. This massive influx of data could potentially become overwhelming if not for the increasing use of AI to analyze. By deploying the proper network management infrastructure and a comprehensive AI-powered operations framework today, utilities can begin to address their highest priority challenges now, while laying the foundation to evolve their network over time. Automating demand planning, accelerating service delivery, localizing, and troubleshooting faults and failures, and optimizing underutilized spectrum are examples of use-cases that can be automated today with significant benefits.Utility Speaker: Dominion (Lynn Hunt) or Idaho Power (TBD). Exact individual to be identified mid-September.