CIO

CIO upfront: Edge computing - when cloud is not enough

Edge computing frees up the real time data processing and then the enterprise can use the cloud to handle heavier lifting, such as combining and analysing data from multiple devices, writes Raghavan Srinivasan of Seagate

Cloud’s agility, scale and accessibility are well understood by the enterprise market and for the most part well loved. 

Indeed according to a 2017 McAfee report, the central cloud model will remain at the core of an enterprise’s network structure with 93 per cent of companies currently using cloud services and cloud spending set to make up 80 per cent of IT budgets by the end of 2018. However an increasing number of CIOs are discovering that their existing network bandwidth and processing capabilities can’t support the demands from the operations side of their enterprise for real-time data processing and instant insights.

Perhaps that doesn’t come as a surprise given the volume of data to be processed for some organisations has increased by orders of magnitude, fuelled by an ever growing number of devices and data sources requiring real-time processing.

Enter edge computing, offering organisations the ability to monitor, handle and store data closer to the data source (i.e. at the edge) with processing happening in the edge connected device itself.  Edge computing extends cloud computing and storage to the edge of the organisation, reducing the reliance on network bandwidth and supporting the need for real-time processing. On first looks it offers organisations the option to maintain the cloud’s simplicity and economics but to also build a robust infrastructure for future demands.

Edge is on the rise

Driven by the rise in real-time intelligent applications, widespread IoT adoption, the increase in high bandwidth requirements, and this intensifying load on cloud computing, the edge computing market is set to reach US$6.72 billion by 2022. But the question for CIOs is when to invest in edge and where does it fit into their data management and multi-cloud strategy?

If the business wants to implement a truly smart logistics system or drive efficiencies from real-time data generated by connected devices, they will need instant machine intelligence. Edge computing makes that possible

Raghavan Srinivasan, Seagate

We know from our own research that data generation is pushing network capacity to its limits across industries. Today, enterprises carry the management burden of more than 97 per cent of the datasphere and will create 60 per cent of all data by 2025, according to the Seagate Data Age 2025 study. So it comes as no surprise that Gartner says edge is one of the 10 strategic technology trends for 2018. It is clear that organisations need real-time insights, reduced latency and rapid data processing.

Because edge computing means data is processed closer to the device itself, the end user can benefit from real-time insights and the load on network resources is reduced.

The possibilities this opens up are exciting – we can see a whole new generation of applications rising from this opportunity to innovate.

Edge computing frees up the real time data processing and then the enterprise can use the cloud to handle heavier lifting, such as combining and analysing data from multiple edge devices. To support such benefits an organisation must have intelligent data storage, curation and management at the edge – building in security, rather than bolting it on.

Deciding if edge is right for your business

A CIO’s decision-making around edge computing must be driven by his or her company’s particular business needs. It may be essentially driven by how many IoT enabled devices an enterprise uses or plans to use. For example, if the business wants to implement a truly smart logistics system or drive efficiencies from real-time data generated by connected devices, they will need instant machine intelligence. Edge computing makes that possible now rather than relying on the processing power of the network bandwidth communicating with the cloud.

There is potential to reduce latency from around 150 to 200 milliseconds (the time it takes for data to travel from the source to the cloud provider and back) to between two and five milliseconds thanks to edge servers or gateways close to the data source. This can drive boosts in production in the manufacturing sector, for example, where image-recognition systems are in use to automate quality assurance checks on parts and products.

Organisations operating in remote locations, or businesses that experience limited or intermittent internet service, can use edge computing to guarantee always-on functionality for essential services. This extends the power of the cloud to business-critical operations no matter where they are, and helps reduce costly downtimes while improving staff productivity and operational efficiency.

The edge acts as an addition and extension to what cloud already offers and develops as our need for real-time intelligence increases – freeing up cloud to take on new functions, enable innovation and drive growth, too.

Edge investment in the right areas, can help an organisation commit to enterprise IoT and realise the value of real-time insights for their business. Investment in the right set-up to withstand and harness huge increases in data volume can allow enterprises to bring true real-time analytics into their business, boosting efficiency and – ultimately – the bottom line in the process.

Raghavan Srinivasan is senior director, enterprise data solutions at Seagate Technology.