As network services become increasingly commoditized, service providers are under significant pressure to introduce creative new services that will grow and diversify their revenues. In order to ensure customer satisfaction, these services must also meet performance and quality objectives. This requires the ability to provide real-time service assurance to customers—upholding end-to-end quality of experience spanning the entire service lifecycle.

A few weeks ago during Blue Planet’s Virtual Insider’s Forum (VIF), we had the privilege of hearing from Crown Castle, a leading communications infrastructure and service provider in North America, which has taken the initial step towards implementing artificial intelligence (AI) and machine learning to achieve this goal.

As a large service provider whose network is continuously growing, Crown Castle decided that conventional assurance tools were no longer sufficient to deliver consistent and positive results to customers that matched their SLAs.  With the increasingly dynamic nature of today’s services, Crown Castle is shifting from the reactive mode of operations that these conventional tools impose, to one that is proactive. Proactive network operations means being keenly aware of happenings in the network, and intelligently responding to events that may adversely impact services – and being able to do so in real-time.

With more than 40,000 cell towers, approximately 70,000 small cells and more than 80,000 route miles of fiber through which services are ultimately delivered to customers across the country, Crown Castle recognized that implementing scalable and intelligent operations is crucial.

Mark Smith, the Director of Network Services and Security at Crown Castle, who presented the case study, detailed the importance of being able to monitor and react quickly to changes observed in the network – specifically at the optical transport network layer where traffic traverses optical fibers via multiple channels to provide end-to-end connectivity. More specifically, Mark talked about how Blue Planet’s AI-enabled intelligent automation solution makes rapid response to issues possible. He emphasized these key capabilities:

  • Collecting alarm and performance data in real-time from the multiple optical nodes deployed throughout the network
  • Analyzing real-time and historical happenings in the network that are causing or have caused issues, such as fiber cuts, attenuation or even optical degradation
  • Creating a knowledge base of issues and successful remedies that can be used to predict and preemptively resolve anomalies that are likely to impact services. Mark described a part of this as developing unique “signatures” that run in real-time to ingest performance data and then dynamically triggering events and generating “predictive alarms”

Importantly, Mark described how these combined capabilities help to reduce service disruption and provide a consistent, reliable service quality of experience for Crown Castle’s customers.

Following Mark’s case study presentation at our VIF event, Anand Gonuguntla, Blue Planet’s Vice President of Portfolio Solutions and Engineering, drilled deeper into how Blue Planet’s solution supports use cases like Crown Castle’s. Anand also noted that transforming the network to one that is truly intelligent, “self-healing” and eventually “adaptive”, is an evolutionary journey. He highlighted that the proactive approach to identifying issues being implemented by Crown Castle is a significant first step toward intelligent automation.

Clearly, Blue Planet’s goal is to simplify this journey for service providers by providing proven solutions with quantifiable business outcomes. I invite you to watch Mark’s and Anand’s recorded video presentations at the links below and please comment if you have any questions on using AI and machine learning to provide real-time service assurance: