Press release

Blue Planet Prevents up to 95 Percent of Network Outages with New Proactive Network Operations Solution

Sponsored by Businesswire

As networks become more complex and software-driven due to the rise of
5G, IoT, and cloud-based services, service providers have an urgent need
to use more proactive methods for addressing service disruptions.

To address this challenge, Blue
, a division of Ciena (NYSE: CIEN), is harnessing the power of
automation and artificial intelligence (AI) to help providers not only
predict but to also proactively avoid outages. Blue Planet’s new Proactive
Network Operations (PNO)
solution enables AI-assisted operations to
significantly improve the trouble-to-resolve process, forging a path
toward a more adaptive network.

Key Facts:

  • According to Ovum, communications service providers (CSPs) indicate
    that their top priority use case for AI is network fault prediction,
    detection and correction, with over 40 percent prioritizing the
    implementation of this use case within the next 18 months1.
  • Colt Technology Services has seen the benefits of Blue Planet’s
    predictive capabilities that collect and process telemetry data from
    multiple sources across its global production network and identify
    faults with strong accuracy.
  • Using advanced machine learning algorithms, Blue Planet’s PNO can
    predict potential service disruptions with exceptional accuracy,
    foreseeing up to 95 percent of unplanned network outages based on
    analysis of Ethernet and optical loss of signal (LOS) anomalies. PNO
    can quickly pinpoint the root cause and then prescribe the best
    actions to preemptively resolve the issue.
  • Blue Planet has also created an OpEx savings calculator
    to estimate the potential savings by deploying PNO. According to Blue
    Planet’s estimates, providers on average can save up to 38 percent in
    trouble-to-resolve OpEx per year.
  • PNO can be integrated into existing provider environments regardless
    of which vendor systems and networking equipment are in place.
    Additionally, Blue Planet’s service professionals can help fine-tune
    and tailor PNO based on specific business objectives and network

Executive Quotes:

  • “AI works best when applied to real-world use cases that improve our
    network operations by eliminating time-consuming manual tasks. Blue
    Planet provides the capability to move beyond the hype to deliver real
    business benefits from predictive and eventually prescriptive
    analytics. This allows us to plan for the future, preparing our
    network for 5G, IoT, cloud and other emerging technologies.”
    Voltolini, Global Head of Network on Demand, Colt Technology Services
  • “One of the biggest challenges CSPs face is the ability to predict and
    proactively resolve network outages. Blue Planet’s PNO solution
    implements AI techniques such as machine and deep learning to predict
    and enable automatic resolution of network failures, allowing CSPs to
    drive efficient operations and improve the overall customer
    Adaora Okeleke, Senior Analyst, Telecoms
    Operations and IT, Ovum
  • “More providers are realizing that AI is key to facilitating a more
    automated way of running their business. Blue Planet’s goal is to
    enable customers to apply intelligent, closed-loop automation to all
    aspects of their operations with the goal of realizing Ciena’s vision
    of a fully adaptive network.”
    Kailem Anderson, Vice
    President of Portfolio and Engineering, Blue Planet, a division of

About Blue Planet

Blue Planet, a division of Ciena (NYSE: CIEN), provides market-leading
intelligent automation software and specialized professional services to
help clients modernize their IT and network operations. Driven by policy
and AI-based insights, Blue Planet delivers the closed-loop automation
tools needed to align IT and networking processes—critical to
facilitating digital transformation. For updates on Blue Planet, visit

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1 Ovum: “Artificial Intelligence: Impact and Opportunities”
by Tom Pringle, published March 27, 2019.