Issue link: https://www.e-digitaleditions.com/i/1476549
22 I ICT TODAY IT IS NOT EASY BEING GREEN Power utilization is quickly becoming the next big challenge that CSPs and MNOs will need to address. 5G networks are expected to scale massively to address customer requirements, such as service innovation, IoT density, and line-of-sight mmWave radios for high-bandwidth applications, and this scaling will require a simultaneous need for additional power. The adoption of green policies and processes will not just be needed to address operational issues of power con- sumption and heat dissipation, they are now becoming a societal concern that could damage service providers' brand reputations if not managed responsibly. Consumers and enterprise customers are starting to demand highly visible green initiatives with tangible results. The chal- lenge to the CSP is that at the same time, they will not be willing to accept a loss of QoE, so power utilization becomes a narrow tightrope to walk—one that will need to be managed carefully. Many governments are considering green policies and initiatives that will strictly enforce power utilization and consumption. Having the tools to adhere to and prove regulatory compliance will be critical for long-term success. and then leverage open interfaces, such as the OpenTelemetry Project, to bring this infrastructure obser- vability together with network and service assurance data to provide a single view of network performance and the customer's experience—all the way from the CPU to the customer's QoE. In this way, advanced ML and AI algorithms can be leveraged to correlate faults and identify root cause issues in near real-time. As this 5G SA journey continues, more challenges will inevitably arise. Having an operations solution that democratizes all the relevant information and provides a single, consistent view of the customer's QoE will be essential. Instead of focusing on the tedious job of iden- tifying fault domains and root cause, operations teams can now work together to focus exclusively on solving these challenges, rather than finding them—ultimately leading to what the customer expects: a better 5G experience. AUTHOR BIOGRAPHY: Ken Gold, director of test, monitoring, and analytics solutions at EXFO has a diverse background in the telecommunications and ICT industries, spanning more than 30 years. He is currently focused on understanding how virtualization and 5G will change the way people and machines communicate and how operators will leverage automation, artificial intelligence, and machine learning to better manage the customer's QoE in this new reality. Prior to joining EXFO, Ken held leadership roles in solutions marketing and product line management with Nortel, Harris Broadcast, ADTRAN, and Accedian Networks, focusing on optical transport and carrier Ethernet service assurance and performance monitoring. Ken holds a bachelor of applied science degree in electrical engineering from Queen's University at Kingston Ontario. He can be reached at ken.gold@exfo.com. REFERENCES: 1. Discussions with Tier 1 North American Mobile Network Operator. 2. "5G Troubleshooting and Fault Detection Study, North America and Western Europe," Heavy Reading Survey, Q1 2022. IN SUMMARY The journey to 5G SA standalone is just beginning, and while there have been challenges and lessons learned along the way, there are likely many more to come. The value of abstracting the hardware infrastructure away from the software applications running in the cloud is a double-edged sword. On the one hand, it greatly simplifies the complexity for the application developer, leading to better solutions, faster. However, it also creates a visibility gap between the 5G SA network and service layers running in the cloud and the infrastructure that underpins them. This visibility gap impedes the ability of the various operations teams to have a unified view of customer impacting issues, leading to longer repair times and potential finger-pointing—none of which serves the customer well. The solution to this challenge is to contextualize and enhance the infrastructure observability data delivered by traditional tools (e.g., metrics, logs, traces)