Publié le 8 novembre 2019
Network visibility: redefining operational simplicity
One of the most pressing challenges facing operators today is maintaining their multiple inventory management systems. A recent EXFO survey indicates that carriers have, on average, nine separate inventory solutions and that upwards of 16 percent of data in those inventories was inaccurate or incomplete. This means that the carrier no longer has a true picture of how the physical and/or virtual infrastructure is configured nor how the services are running on top of it. This same research showed that only 15 percent of communications service providers (CSPs) believe they have a fully integrated view of their network and service inventory. When networks and services are dynamic, through the adoption of SDN and NFV, the pace of change increases, making it even harder to keep up and extremely difficult to obtain an accurate and unified view of the network, services and subscribers. This lack of network visibility makes it challenging for operators to properly prioritize customer experience management actions to achieve and maintain a high quality of service for their subscribers.
The absence of network visibility further compounds the difficulty of diagnosing and troubleshooting faults in the network. Without up-to-date information available on demand, operations staff and customer service teams are forced to manually piece together network and service details from multiple, disparate systems to uncover the root cause behind debilitating network outages. And as we have seen, given the rate of change operators must keep pace with, it’s little wonder that critical outages have spiked by 40 percent over the past three years.
As operators look ahead for ways to achieve more efficient and effective network operations through the adoption of AI and machine learning, they need to bear in mind that the success of such endeavors rests entirely on whether the data used to train these algorithms is clean and accurate. Without that, their AI aspirations will fail.
Today, EXFO’s network visibility and monitoring solutions are helping the operations, customer care and planning teams of several major carriers worldwide get the network and service visibility and data accuracy they need to do their jobs effectively. If you would like to learn how EXFO can help you build a solid foundation for AI and machine learning, drop by our booth at this year’s DTW Asia event (November 12–14, Shangri-La Hotel, Kuala Lumpur), or contact your local EXFO sales representative.
Automation aided by reliably correlated topology
EXFO is working with a North European Tier 1 operator to roll out its real-time topology application to automate the identification of common causes behind network outages. Previously, large-scale outages and the protracted diagnosis of faults took days (sometimes weeks) to investigate. The manual methods used to address these outages typically involved gathering a group of valuable, highly in-demand subject matter experts (SMEs) in a war room to identify and resolve the issues. Human logic was used to determine which customers were affected by the outage, manually trace back from the customer location and locate the faulty network equipment. This resulted in slow response times and increased operational costs.
But today, real-time topology, an essential network visibility tool, allows us to track and understand the configuration of the entire network across all sources. To help identify the most likely common- cause customer issues, a “symptom set” is created from which it is possible to see common and shared performance issues that appear across a large set of endpoints. Common, repeated and simultaneous symptoms imply a common cause. This means that the symptom set can be used to automate a topological analysis algorithm called “common cause analysis,” by which a symptom set is created and fed to the EXFO topology engine. The system then uses its cross-domain topological model to find the unique set of network nodes that all entities in the symptom set share.
The results of the latest instalment of this project will be shared by Benedict Enweani (Director, Applications and Analytics at EXFO and co-founder of Ontology) at the DTW Asia 2019 show on November 13, at 2:25 p.m. in the Selangor Room.
Knowledge of end-to-end topology delivers value
EXFO knows that advanced knowledge of end-to-end infrastructure empowers CSPs to:
- Deliver a higher standard of service and support to customers
- Reduce customer churn
- Increase market share
- Increase efficiency of customer support, planning and provisioning processes
- Reduce operating expenses
- Embrace automation
You may also be interested in our new podcast, “Know your network,” featuring thought-provoking conversations around key management challenges facing today’s carriers.