Cloud Computing is the spanking new paradigm in the world of computing. The key differentiator in this technology is that the enterprise only pays for the amount of resources used – be it CPUs, memory or databases. While it does away with Capital Expenditure for organizations by providing a utility model of pricing it results in recurring Operating Expenses for the organization. However the important thing is that the cloud grows and shrinks according to demand and hence the cost to the organization is dependent on the traffic it generates. While web based applications are prime candidates for the cloud other equally eligible candidates are batch processing jobs, nightly builds or CPU intensive analytics. Except for the case of web application, for other types of applications, a reasonable estimate can be made on the resources needed and appropriate choice be made on the cloud.
This article looks at web applications where the traffic on the site can be seasonal and can vary during periods of the day. Besides web sites should be capable of handling bursty traffic with enormous loads at particular intervals.
The important consideration for web sites is to ensure that the application is truly optimized and exhibits the property of scaling horizontally. While it appears that scaling out will occur for any reasonably designed application the issue is that as the number of hits increase on the web site the response time increases steeply but the number of transactions per second plateaus at some particular load level and does not increase after that. It can be said that for a certain CPU instance configuration the peak transaction per second will reach a particular limit and cannot be increased any further. However the cloud also provides a key component namely the load balancer along with auto scaling which create a new instances when this threshold is reached.
What are the business considerations that need to be taken while designing for the cloud?
One needs to be conservative in choosing the instance type. While larger instances will provide a better performance they also cost more. Hence the instance type should be large enough and no larger. It would be wasteful of using extremely large instances where the last instance only uses a part of the total traffic while costing a lot more.
The analogy is that if 16 units if task have to be performed it is better to have a small CPU instance capable of handling 3 units of task requiring a total of 6 CPUs (6 * 3 = 18 > 16) rather than having a large CPU instance capable of handling 5 units of task requiring a total of 4 large CPUs (5 * 4= 20> 16). The second option would result in a waste processing power.
Assuming that the upfront cost to the organization for hosting the website in-house is ‘P’ and the cost amortized over a period of 1 years is ‘p’ per hour. Further if the instance cost is ‘c’ and ‘n’ is number of instances needed to support the projected demand and the revenue to the organization hosting the website is ‘r’ per 1000 hits then a cloud deployment will make business sense when
(rh– n * ch) – ph > 0 where h is the hour
As long as the right hand side is positive the organization will profit. However as the traffic increases and the throughput of website plateaus the enterprise will hit a ‘window of diminishing returns’.
However if the performance of the application is poor and the number of instances needed to support the traffic is disproportionately large then the above equation will be negative and will result in loss to the organization.
(rh – n * ch) – ph < 0
Hence deployment to the cloud besides requiring a strong technical background also needs a sound business sense in order to reap the benefits of the cloud.