DCN October 2017 - Page 33

hyperconvergence hinges upon the maturity of software to take upon itself the intelligence to perform the functions of the whole infrastructure stack, all the way from storage, compute, networking and virtualisation to operations management, in a fault tolerant fashion.” He adds, “So, it is fundamentally about intelligent software enabling data centre infrastructure to be invisible. This allows companies to operate their environments with the same efficiency and simplicity of a cloud provider. Hyperconvergence then becomes strategic, as it can stitch together the public cloud and on- premise software-defined cloud, making the customer agile and well-positioned to select multiple consumption models.” Cost-benefit analysis David nevertheless believes that it’s important to consider the short-term and long-term costs of moving to the cloud. You have to consider whether this is going to be a long-term or short-term process. This is about whether it is cheaper to rent or buy, and about which option is most beneficial. The problem is that although the cloud is often touted as being cheaper than a traditional in-house infrastructure, its utility rental model could make it far more expensive in the long-term: More than any the capital expenditure of owning and running your own systems. “Sometimes, for example, it is cheaper to buy a car than to rent one”, he explains. The same principle applies to the cloud model. For this reason, it isn’t always the perfect solution. Done correctly, hyperconvergence enables the data centre to build an IT infrastructure capable of matching public cloud services in terms of elements like on-demand scalability and ease of provisioning and management”, comments Anjan. “Compared to public cloud services, it can also provide a much more secure platform for business-critical applications, as well as address the issues of data sovereignty and compliance. A hyperconverged platform can also work out more economical than the cloud, especially for predictable workloads running over a period.” Silver linings “Believing the hype about the cloud isn’t necessarily the way to go.” “Not every cloud has a silver lining”, says David. He argues that believing the hype about the cloud isn’t necessarily the way to go. “You have to consider a number of factors such as hybrid cloud, keeping your databases locally, the effect of latency and how you control and administer the systems.” He believes that there is much uncertainty to face, since the cloud computing industry expects the market to consolidate over the forthcoming years. This means there will be very few cloud players in the future. If this happens, cloud prices will rise and requests to cheapen the technology will be lost. There are also issues to address, such as remote latency and the interaction of databases with other applications. Impact of latency David explains, “If your application is in the cloud and you are accessing it constantly, then you must take into account the effect of latency on the users’ productivity. If most of your users are within HQ, this will affect it. With geographically dispersed users you don’t have to take this into account. “If you have a database in the cloud and you are accessing it a lot, the latency will add up. It is sometimes better to hold your databases locally, while putting other applications into the cloud. “Databases tend to access other databases, and so you have to look at the whole picture to take it all into account – including your network bandwidth to the cloud.” Your existing infrastructure, within your data centre and outside of it, therefore must be part of this ‘bigger picture’. So, with regards to whether hyperconvergence and whether it’s the way to go, David advises you to analyse whether you’re still able to gain a return on investment (ROI) from your existing infrastructure. “Think about whether it has a role in your cloud strategy”, he advises before addin q]Ѡ)ɥՐɅѕ䁍)ݹͥ锁ȁфɔͅ٥)ѕɝ́ѽ%)ɔѼɍٕɝ)ѡͽɅݥɕեɕ)%ԁɔѼ͔ȁѥ)ɅՍɔѡԁݥɕ)ٔͽ͕ͭ́ͥєt)фɽѕѥ)1ЁЁЁаѡɔ)ѥѼͥȁф)ɽѕѥݡѕ́)ѡиQՐ)ٕѡ͕́ȁ )̵͕٥ ULͅѕȴ)Iٕ䵅̵M٥IL)ЁɥͽѥMѥ)ɕ͕́ѡЁԁ͡ձeЁ)ͽ䁽ѡՐɕ)ѽɥфձѥ̸)Qٕ́ݥѠ)ͽѥ̰Ս)A=IQɽ%Pq%ԁѼ)ٕȁѼѡՐ)ѼѼٔȁф)ɽչѱ䁅Ё)ݕ́ɕѽɔфɕեɕe)ѼЁչѼɽѕ)ȁͥ́Ʌѥ̻t) ͥȁѡɔɔѡ)ѥ́ݡЁ͕ٔ)фɔ́ѕȸQӊe)͔ͽѡͭѥʹ)́ѡɥЁݕ)ͽѥ̸)=ѽȀ܁