Intelligent Data Centres Issue 07 | Page 31

EDITOR’S QUESTION of raw data onsite before sending it, in a more refined state, efficiently to the central data centre. Edge Computing brings with it the need to deploy many micro data centres of varying sizes and a platform that can scale in both directions to accommodate businesses digitalisation needs. Essentially, a good Edge deployment can be looked at as a micro data centre combined with intelligent automation. Data centre functions such as compute, storage, backup, disaster recovery and application virtualisation can be consolidated into a single, integrated platform – this is a hyperconverged infrastructure. JEFF READY, CEO, SCALE COMPUTING ccording to a study from IDC, 45% of all data created by IoT devices will be stored, processed, analysed and acted upon close to, or at, the edge of a network by 2020. So, as IoT and the growing global network of sensors add more data than the average cloud has ever had to handle, Edge Computing will increasingly take on workloads that struggle on hosted cloud environments. It will move them towards more efficient technologies for local data storage and processing, like HCI platforms. A While the rolling out of new data centres will be partly driven by the uptake of Edge Computing, the very concept of the traditional data centre will likely also be re-written. This is because Edge Computing allows organisations to process large amounts www.intelligentdatacentres.com AS IOT AND THE GROWING GLOBAL NETWORK OF SENSORS ADD MORE DATA THAN THE AVERAGE CLOUD HAS EVER HAD TO HANDLE, EDGE COMPUTING WILL INCREASINGLY TAKE ON WORKLOADS THAT STRUGGLE ON HOSTED CLOUD ENVIRONMENTS. Infrastructure silos that are difficult to manage in a centralised data centre become unmanageable at the Edge and thus convergence of these into a single platform is both efficient and cost effective. It doesn’t always make sense to send data all the way back to the traditional central data centre only to be processed and sent back to the same site where it was generated. Unlike full data centre implementations, Edge Computing is small enough to not warrant dedicated IT staff. Due to this, the infrastructure needs to be easy to implement and manage, and easily connected back to the primary data centre or even the cloud as needed. There are exceptions to this, such as automated video surveillance use-cases. A network of surveillance cameras will create a massive volume of valuable and sensitive data every second. To action intelligent automation in real-time, Edge Computing devices can harness the data collected from the cameras remotely. But, in order to store this data long-term, traditional data centres still remain a big part of the picture, as the data is fed back to the data centre from the Edge device. Issue 07 31