Addressing the challenges of the hyperscale ecosystem

Hyperscale data centers are constantly challenged by increasing bandwidth, storage, processing power and speed requirements. The rapid scalability that defines hyperscale computing can only be achieved through a combination of new hardware (scale-out) and improved performance of existing data centers (scale-out).

The resources to build or expand hyperscale data centers are a challenge that only gets bigger as you scale. This can result in fewer fiber and system verification tests and exposes data centers to downstream outages and rework. Given the scale and energy demands, internet content providers, big data storage, and public cloud operators face increasing 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 capabilities in the cloud continue to anchor the network architecture, but distributed edge computing and disaggregation to support ultra-low latency 5G use cases are pushing hyperscalers out of their proverbial box. In other words, 5G big data remains centralized while instant data moves closer to the edge.

Hyper-Intelligent Hyperscale

Intelligence and automation are required to successfully build, test and ensure 5G network slices are deployed end-to-end. A successful marriage between 5G and hyperscale requires AI, machine learning, and network function virtualization (NFV) to achieve performance.

5G hyperscale use cases

Advanced driver assistance systems (ADAS)

Advanced Driver-Assistance Systems establishes a new transport model with 5G that provides the required ultra-reliable, low-latency communications (URLLC). Edge computing performance is key to meet ADAS latency requirements. Parameters such as vehicle spacing, traffic light timing, pedestrian avoidance, and advanced signage can be fully automated and optimized.

factory automation

The benefits of factory automation, powered by high-bandwidth, low-latency private 5G networks, are seemingly limitless. Robots, vehicles, facilities and tools become smarter, safer and more efficient, while maintenance and calibration can be planned based on feedback from millions of embedded sensors using hyperscale cloud computing.

Connected Health

Telemedicine can pave a path to routine care for isolated, immobile, or symptomatic patients. The IoT wearables market will explode as 5G increases capacity and reduces latency. Hyperscale data centers in perfect synchronization with edge computing sites are key to safely and reliably support these virtual healthcare applications.

Unmanned Data Centers

Leveraging the IoT for real-time monitoring and control of temperature, power, and metering functions is consistent with a shift toward unmanned data center operations, particularly at the edge. The physical removal of people also opens up new opportunities for hyperscale data center locations, including cold, inhospitable regions where land and natural cooling sources are inexpensive and plentiful.

Solving the hyperscale challenges

Leveraging and adopting new technologies (including 5G) to test, monitor and optimize data center operations is the best way to turn today’s challenges into opportunities. Despite the emphasis on 5G RAN and device innovation, extensive testing from hyperscale data centers is also required to ensure the promise of 5G. A proactive approach to fiber RAN and Xhaul pre-deployment testing recognizes a new standard of automated cloud-based test and diagnostic tools that aid rather than hinder construction schedules. This advanced testing approach also includes live network traffic emulation and AI-assisted “self-healing” capabilities to prevent outages, repairs, and unplanned updates.

About the author:

Sameh Yamany – Chief Technology Officer, VIAVI Solutions

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