With the exponential boom of Internet of Things (IoT) technology, enterprise workloads are increasing significantly with the addition of high-performance workloads like artificial intelligence, machine learning and big data that needs to be processed and analysed in lightning-quick time to be truly useful.
Edge computing manages and processes these massive streams of data close to the source, which reduces latency and data transmission costs incurred by traditional cloud computing. While this may seem like the answer, it isn’t without its tradeoffs as it creates new pressures on infrastructures at the edge to be more powerful and efficient than ever.
The solution for many enterprises is a shift to Hyperconverged infrastructure (HCI), combining compute, storage, networking and management into a single virtualized system to reduce data centre complexity and increase its scalability.
This paper takes a closer look at how HCI works on the edge and the considerations needed to truly reap the rewards of hyperconvergence.