Hyperscale data centres are continually being challenged by increasing bandwidth, storage, computing power and speed requirements. The rapid scalability that defines hyperscale computing can only be accomplished through a combination of new hardware (horizontal scaling) and the improved performance of existing data centres (vertical scaling). Gathering the resources needed to build or expand hyperscale data centres is a challenge that only grows stronger as the scale increases. This can lead to reduced fibre and system verification testing, exposing data centres to downstream failures and rework. Given the scale and energy requirements, internet content providers, big data storage and public cloud operators are facing growing pressure to improve efficiency and reduce emissions.
Hyperscale and 5G
5G changes the hyperscale definition
5G has entered the picture with a new blueprint for hyperscale computing. Core functions in the cloud continue to anchor the network architecture, but the need for distributed edge computing and disaggregation to support ultra-low latency 5G use cases pushes hyperscalers out of their proverbial box. In other words, 5G big data remains centralised while instant data is moving closer to the edge.
Intelligence and automation are needed to successfully create and test 5G network slices from end to end. A successful union between 5G and hyperscale will require artificial intelligence (AI), machine learning, and network function virtualisation in order to achieve performance.
5G hyperscale use cases
Advanced driver-assistance systems (ADAS)
ADAS have established a new transportation model, with 5G providing the requisite ultra-reliable low-latency communication. Edge computing power is the key to meeting ADAS latency requirements. Parameters such as vehicle spacing, traffic signal timing, pedestrian avoidance and augmented signage can be fully automated and optimised.
The benefits of factory automation backed by high-bandwidth, low-latency private 5G networks are seemingly limitless. Robots, vehicles, facilities and tools can become smarter, safer and more efficient, while maintenance and calibration can be scheduled based on feedback from millions of embedded sensors utilising hyperscale cloud computing.
Telemedicine can provide a path to routine care for isolated, immobile or symptomatic patients. The internet of things (IoT) wearable market is set to explode with the capacity boost and latency reduction provided by 5G. Hyperscale data centres that are in perfect sync with edge computing locations are the key to supporting these virtual healthcare applications securely and reliably.
Unmanned data centres
The use of IoT to monitor and control temperature, power and surveillance functions in real time is in line with the shift towards lights-out (unmanned) data centre operations, particularly at the edge. Removing manual operations also opens up new possibilities for hyperscale data centre locations, including frigid, inhospitable regions where land and natural cooling sources are inexpensive and plentiful.
Resolving the hyperscale challenges
Harnessing and embracing new technology (including 5G) to test, monitor and streamline data centre operations is the best way to turn the current challenges into opportunities. Despite the emphasis on 5G radio access networks (RANs) and device innovations, comprehensive testing of hyperscale data centres is also necessary to ensure the promise of 5G. A proactive approach to pre-deployment of fibre RAN and crosshaul testing would utilise a new standard of automated cloud-based testing and diagnostics tools that help rather than hinder construction timelines. Such a progressive approach to testing would also include live network traffic emulation and AI-powered “self-healing” capabilities to prevent outages, repairs and unplanned updates.