As the world becomes ever more connected and consumers get used to accessing continuous on-demand services, organizations are increasingly relying on centralized computing capabilities to power their businesses.The adoption of the cloud infrastructure across the enterprise landscape,thus,has been witnessing a steady rate of growth over the last few years. In fact, Gartner predicts that the public cloud market alone will grow to an estimated size of $411.4bn by 20201. With such potential, the momentum of cloud adoption will onlyget larger,and most companies are expected to commit 80% of their IT budgets to a cloud-first strategy within the next two years2.
Even as cloud computing increasingly enables large-scale transformationsin provisioning of both industrial and consumer services, organizations, though,will need to exercise some restraint before fully migrating to the cloud. Adopting a cloud-first strategy will, of course, yield multiple benefits such as increased agility, flexibility and cost optimization. However, a standard cloud implementation could potentially introduce more inefficiencies into the system, overshadowing the advantagesenvisaged. This scenario is particularly plausible for use cases where latency plays a key role in determining the quality of services rendered.
Take for instance, the case of a streaming video service where end customers are widely dispersed across multiple geographies. The quality of the streaming content at each of theseend nodes can be highly variable and subject to many factors, including the Internet connection at the user’s end and the distance over which data packets are transmitted. While the former is not something most providers can have an influence on, companies can definitely consider decreasing the distance of data transit to improve latency. That is, however, easier said than done.
For organizationsoffering services to customers across multiple countries worldwide, it would be practically unfeasible and cost-prohibitiveto establish dedicated content servers and network connections close to each of their end-customer points. Even if such initiatives are rolled out, a seamless provision of services across all customer groups will stillbe a challenging task.
With the Internet of Things (IoT) going from hype to reality faster than expected, and with the number of sensor-embedded devices across the IoT ecosystem tipped to skyrocket to 34 billion3, the demand for network services will only go up multifold. The Smart City revolution, where about 40 global cities are soon expected to become automated and hyper connected by 2020, will further drive up the need for instantaneous, high quality connections.Tragically, even a millisecond’sdelay in data transit can significantly hamper the operations of automated devices.
How do companies then address their need for cost and effort optimizations, while still preparing to meet suchhigh demands of the future? The answer lies in taking advantage of edge computing and the next-generation cloud services facilitated through high-density data centers.
Under this innovative business model, companies rely on multiplesmallercolocation data centers that are situated as close to their usersas possible, instead of centralizing all of their infrastructure and storage requirements in a lesser number of data centers. Each of these mini data centers is equipped withdedicated individual computing power and service provisioning capabilities that cater to localized demand, vis-à-vis addressing traffic that originates from a geographically distant location. The mini data centers are, in turn, connected to each other, to a parent center, and to the cloud wherever required,in order to provide a uniform service.
By increasing the number of provisioning points that can act independent of a central server, this model lets companies effortlessly deliver high-speed and reliable services to their customers. By distributing the computing power to multiple, smaller data centers, processing can happen closer to the edge of networks, guaranteeing response times that are as near to realtime as possible. The risk of dependence on one or two central infrastructure units will also go down drastically as the mini-centers will be capable of operating independently.
In addition, such a model will also help companies efficiently manage the explosion in data that is expected to come with the growth of IoT where connected devicesare projected to generate data of the magnitude of 600zettabytes or more4. It is impractical, for both latency and economic feasibility reasons, to capture, transport, process and store all this data in a centralized cloud location, especially since some of this data may not be reused later. A smaller data center located closer to the point of data generation can instead handle all the processing requests, sending only the most important portions of data to a central storage, thusreducing data traffic substantially.
Leveraging edge computing alongside high-density data centers provides businesses with a sustainable option to manage their infrastructure requirements, while still fulfilling their customer requirements for high quality and low latency services. Greater operational efficiency, better capacity management, and lower energy consumption resulting from more computing powers packed into lesser space are some of thebenefits companies will accrue automatically using this approach.
The resulting decrease in the total cost of ownership (TCO) and the ensuing capability to still provide world-class services to end customers will ultimately make this a compelling proposition for organizations that consider customer experience their top priority. The question now is, are you one of them?
For consultation and successful transition into the world of cloud and data centres, contact us at Nxtra Data.
Call: 1800 102 9635 | Visit: http://www.nxtradata.com