White Paper: Efficient Management of Cloud Resources

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1 White Paper: 215, Cloud Point ltd. All rights reserved. INTELLECTUAL PROPERTY DISCLAIMER This white paper is for informational purposes only and is provided as is with no warranties whatsoever including any warranty of merchantability, fitness for any particular purpose, or any warranty otherwise arising out of any proposal, specification, or sample. No license, express or implied, to any intellectual property rights is granted or intended hereby. Cloud Point Ltd disclaim all liability, including liability for infringement of proprietary rights, relating to implementation of information in this specification. Igroup Ltd do not warrant or represent that such implementation(s) will not infringe such rights. Product or company names mentioned herein may be the trademarks of their respective owners.

2 The cloud has opened up a range of new opportunities for business to expand in new ways. Technology has enabled large scale change in the way infrastructure is used and the way in which cost is incurred by a business. In this white paper, we looked at the way in which cloud resources are consumed by businesses, and the way in which Cloud Point are using technology to make the cloud more efficient and more accessible. Our unique approach to cloud resource management and the way in which we use data to help planning and automate maintenance enables us to reduce the cost of the cloud for our clients while maintaining class leading SLAs across service availability. 2

3 Cloud Point is part of igroup; an ISO 91 certified organisation and a Microsoft Gold Certified Partner with our specialist competency in SharePoint. We specialise in providing Microsoft Cloud Services to our clients with a full range of services including development, hosting, consultancy, support and training. Our Managing Director, Steve Rastall has been named in Insider Magazine s Top 25 Up & Coming Entrepreneurs and we have also won a HOT 1 Fastest Growing Companies award. Since we were setup, we have at least doubled sales revenue every year via organic growth. For more information about the products and services offered by Cloud Point, please visit our website: Or contact us using the following address and telephone number:

4 The nature of true cloud solutions means that users are not tied to a physical upgrade cycle as they are with conventional server technology, nor are they tied to any system limitations aside from what their agreement with the provider are. Ultimately, the amount of disk space, compute cycles and memory are elastic and can be configured to customer needs. For the most part, during the process of defining their cloud requirements, an organisation will approach the process in the same way as they would when setting the specifications for a standard server. This approach can lead to a number of negative outcomes: Under Spec -> Insufficient Capacity for peak demand Over Spec -> Higher Cost for redundant hardware Designing a server that is tailored to anything less than peak demand will result in a lower cost to an organisation, however it will also mean that performance suffers when demand exceeds the design limits that have been set. This can result in connectivity problems and slow connections when users are requesting information. Designing a server that is designed for the maximum loads encountered will generally result in better performance at most times, but the costs of equipment and compute will be much higher than necessary. A cloud solution offers far more flexibility to an organisation in terms of balancing both demand and budgets. A true cloud server is not restricted to the capacity of a single device, instead the load is spread across multiple hardware units that are connected using software such as Azure. This allows for the capacity to be changed to reflect the demand that is placed on the server at different times. A managed cloud solution is able to respond to the demands placed on it, and scale up resource as required. This means that at times when the demand is low, the server can be placed into a minimal state. When demand is at its peak, the amount of bandwidth, processors, and memory can be increased to reflect demand and provide a smoother experience for users. This provides the benefit to businesses of only paying for the resource that they need at a particular time. In some cases, the resource level is managed by system managers who deploy resource based on customer requests. More advanced cloud solutions use automated monitoring to respond to changes in demand and deploy more resource as appropriate. Both of these methods rely on intervention whether manual or automatic, but there can be a delay in the level of resource being deployed which can lead to connectivity issues for users. Predictive technology can be added which is able to use historic data to ramp up resources automatically at times when it is needed while scaling back outside peak times. This has the advantage of removing most of the latency in the system and providing a better experience for end users. 4

5 The following chart shows the hourly bandwidth requirements for an online retail website on a Sunday and a Wednesday: Hourly Bandwidth Sunday Wednesday Here we can see that while there are similarities in the overall trend across the day, the demand on the Wednesday is generally higher and there are some peaks in demand that do not appear on the Sunday. By analysing this type of data over longer periods, it is possible to scale demand programmatically and predict the level of demand on a particular date based on historic trends. Data can be seasonally corrected based on data for the following periods: Monthly Daily Hourly As an illustration, the following chart shows the bandwidth for the 11am on the first Thursday of each month throughout the year: 5

6 Bandwidth 11am, 1st Thursday Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec The levels of demand seen follow a very close pattern which can be used to when planning requirements across the year. Most periods of high demand can be foreseen based on past behaviour, however it is also important to be able to augment the data based on changes in behaviour. An extreme example of this would be Black Friday: 6

7 Historically the biggest days in the US retail calendar is Black Friday following Thanksgiving. Historically the day has marked the start of the Christmas Retail season, and is noted for the high reductions on prices offered by stores to encourage consumers to buy. Though the tradition is tied to the US calendar, recent years have seen it imported into the UK with aggressive discounting from retailers. Search interest in these 3 major retailers increased by up to 1x the usual levels during the peak demand period of Black Friday, and the companies were forced to implement online queuing systems in order to manage the levels of traffic that they were experiencing. Shoppers vented their frustration with the website issues on Social Media leading to a degree of brand damage for the stores: 7

8 Given the levels of demand that were seen on Black Friday, the 2 hour down time Argos experienced resulted in several million pounds in lost sales. Black Friday 214 was an extreme example of changing demand, and the levels of online demand were an order of magnitude larger than seen in previous years. While there would be historic information available that there would be a peak in demand on Black Friday, past behaviour did not point to the level of change seen in 214. Under these type of circumstances, the scale of the cloud deployment would not have been algorithmically set to deliver the amount of resource required, however by having a dynamic system in place as back up that could be responsive to changes in demand, any downtime would be minimal. 8

9 Windows Azure provides a flexible platform for cloud infrastructure as a service. It has been designed to underpin enterprise class applications for both web access and internal information sources for large organisations. Azure was developed in order to enable the widest possible range of uses, and as such was designed to be highly flexible depending on the requirements of customers. A variety of operating systems and software can be hosted within the environment. This flexibility and range of uses can lead to some issues arising. As numerous different software packages compete for resources, there can be conflicts in how memory is apportioned and how the foundations are able to handle requirements. A fault monitoring solution is essential as part of a cloud system to ensure that things run smoothly. Application failures can cause far more severe issues for a business than a lack of computing resource, and as such should be prioritised as part of the specification of any cloud based infrastructure. 9

10 Sunday : Sunday 5: Sunday 1: Sunday 15: Sunday 2: Monday 1: Monday 6: Monday 11: Monday 16: Monday 21: Tuesday 2: Tuesday 7: Tuesday 12: Tuesday 17: Tuesday 22: Wednesday Wednesday Wednesday Wednesday Wednesday Thursday 4: Thursday 9: Thursday 14: Thursday 19: Friday : Friday 5: Friday 1: Friday 15: Friday 2: Saturday 1: Saturday 6: Saturday 11: Saturday 16: Saturday 21: Computing requirements for enterprise businesses are rarely consistent. Even on private networks, resource demand varies over time. Depending on the nature of an organisation, levels of demand can vary substantially over time. Historically the process of building a web server has focused on ensuring that the infrastructure is capable of managing the periods of peak demand. This results in equipment that is generally over specified for general use, and a large amount of spare capacity which is only required for short periods. The following chart shows the hourly bandwidth for a typical online retailer s website over the course of a week Retail Website Bandwidth (1 Week) In this chart we can see that while the general bandwidth required is quite low, there are regular surges in demand where the amount of usage increases by up to 8x the lowest levels. It is similarly possible to see trends within an individual day of trading: Average Hourly Bandwidth (B2C) Average In this chart we can see that levels of demand are low throughout the night before rising during the working hours and peaking in the early evening. This pattern is typical for retail and B2C websites when research occurs during the day and conversion happens in the evening. The usage patterns in a B2B environment are significantly shifted as shown in the following chart: 1

11 Average Hourly Bandwidth (B2B) Average In this chart we see peaks in demand during working hours which and lower demand during the same period when the B2C retail website is at its peak. The data from the two charts can be overlaid as follows: Hourly Bandwidth Comparison B2C B2B Similar patterns can be seen over the course of a week in terms of when different types of business have peak data usage: 11

12 Day to Day Comparison Sunday Monday Tuesday Wednesday Thursday Friday Saturday B2B B2C Here we see that the demand for the B2C organisation is much higher at the weekend whereas the peak in demand for B2B is in the middle of the week. The difference in these trends leads to a more stable overall pattern. As more services use the resource, their differing patterns of demand leads to a much smoother overall demand curve which can be leveraged by a cloud provider to ensure maximum usage of available resources through careful planning of deployments. 12

13 In recognising that the two key factors in ensuring a smoothly running cloud environment, Cloud Point have developed an Azure Toolkit that enhances the features available within the platform and provides a cost effective cloud management solution that automates many functions in order to provide a consistent experience for end users. Providing our customers with a flexible cloud is essential. By using big data analysis techniques, we are able to proactively manage the level of resource deployed to a customer within agreed limits. This means that at times of high demand the amount of memory, server space and bandwidth are scaled higher, while at times of low usage the resources are minimised. This means that clients are able to benefit from an environment that runs at the most cost effective levels at all times, which provides a substantial cost saving over a fixed environment. We have developed our smart cloud software to provide self-healing functionality within Azure. We use a proprietary set of algorithms to monitor system performance across all installed applications, and automatically apply fixes as required. Around 8% of common issues can now be solved without direct involvement from technical support staff, further reducing the overall cost of the solution while also providing improvements to up-time. As previously noted, the peaks in demand for different types of business vary. This means that through intelligent planning of our deployment we are able to run systems in a very lean way. Spreading the types of business we work with across the cloud means that we can plan around the various peaks in demand that are seen in different areas and deliver a more efficient whole cloud solution to our clients who benefit from lower costs due to better utilisation of available resources within the wider network. For more information about how Cloud Point can help your organisation to implement cloud solutions using Azure and other Microsoft Products, please contact us on: Alternatively, for more information about our services, please visit our website: 13

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