Pay For The Exact Amount Of Technology You Use!
It was a long time coming, but it was inevitable – the shared nature of cloud computing had to lead to flexible resource usage on account of its distribution amongst disparate entities. Moving on from the dated concept of owning and operating your own computer system, the future is set to utilize the obvious advantages of elastic computing.
The underlying principle of elastic computing makes it dependent on the load that is present on your system at any given time, irrespective of its region or time zone.
In fixed bandwidth systems that are slowly giving way to this new approach to shared computing, the price you pay to access the resources on the shared server remain constant even if there is no load on your specific website or application, meaning you are running up your bills by consuming higher utilities than required.
By bringing Alibaba elastic computing into our fold, we aim to pass on the decrease in running business costs on to you. Just as it is easier to share the overheads incurred in business activities with other people while using a co-working space which is all the rage these days, a similar option exists in the cloud computing world. Instead of leasing out a dedicated part of servers and the requisite processor power, Go4hosting and Alibaba have combined to give you unprecedented control over the resources you dedicate to handling your system.
If you know the peaks and troughs of the incoming traffic to your website, for instance, you can limit the resources usage at other times, which means you take care of the unpredictable surges of traffic associated with distributed denial of service and other malicious attacks at the same time!
Consider a simple case of seasonal traffic to tourism websites, which experience a huge inflow during vacation dates but stay stagnant for most of the year, but the host server remains on the same power modes and consumes the same amount of energy without the corresponding revenue flowing in from the business. Is it not sensible to make the resource consumption shrink and grow according to the incoming traffic? Reducing the running costs of the system when it is not being fully used makes even more sense when you consider the much, much smaller timescale of computing processes.
That is why pushing down the seconds and milliseconds it takes for online information to traverse the globe, called latency or server response time depending upon the context, is a prime objective for programmers of websites and developers of applications.
Additionally, elastic computing reduces overall energy consumption, making technology based businesses become more profitable by reducing costs of running their hardware. When shared resources are called upon to handle ‘instances’ of computing power requirements, you are expected to pay only for the quantum of services consumed. This seemingly simple factor of resource consumption in an instance involves many factors, including but not at all limited to throughput (of both network and disk/storage, the amount of data being transferred, stored or manipulated, and the processing power required to efficiently provide the feedback in the form required by the user. When high end processors like Graphical Processing Units (GPUs), Field Programmable Gate Arrays (FPGAs) or Application Specific Integrated Circuits (ASICs) are involved, it becomes even more efficient to subscribe to elastic computing plans, so that the costs of running these power-hungry hardware components does not outweigh the expected profits.
In essence, the processing time and the memory space define instances, along with defining attributes like network requirement and the space created to process the instance, typically called an image (due to the fact that it stores information temporarily for the computational purposes of the instance).
Riding on the shared synergy of each other, we have no doubt about the effectiveness of this collaboration.
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