Tuesday, 19 January 2010

Cloud Overbooking - Part 1

Now for something cloud related as I haven't waffled on about cloud for a while. This Two part series (it got too long for one post) is based upon oversubscribing or over allocating strategy within public cloud world. Within this first part I will use the current Airline reservation overbooking strategy and use this as an example to potentially see where similar algorithms may start to be needed to calculate workload allocation in a typical open Public Cloud provider. This post was also super charged by this excellent post on what the blogosphere classes as the difference between capacity oversubscription and over capacity models within the Amazon EC2 service.

So ever been bumped up or bumped off?

No this isn't a question about your mafia status, I am talking about flight bookings. As you may have noticed from the "about me section" I currently work for an Airline, with this in mind I will use some of the (small) knowledge I have gained on how the oversubscription model works in our world. It is a well known fact that the Airline industry falls into a number of industries that "overbook" on certain flights, see this definition for full gory detail on how this whole process works behind the scenes but in a nutshell it is an algorithm used by the travel industry to work towards achieving full capacity on certain flights by taking more upfront purchases than is available in the reservation system. Overbooking tends to affect the lower entry level economy passenger who is paying less for his seat and is likely to be less of a regular customer, lastly overbooked passengers are all covered for compensation in many shapes and forms such as being offered either a seat on the next available flight or a volume of cash that makes them happy.

So hopefully after reading the brief detail on how the overbooking model I am beginning to think we are going to see a overbooking or oversubscribed type strategy needing to be adopted within Public Clouds. To justify my comparison, simplistic marketing from Public cloud companies state that you can buy a workload in EC2 from the Cloud provider and assume it will be able to provide you with the compute and networking requirements that you would get if hosting on premise. Based on this comparison in a shared multi tenant public cloud do you think the same rules could apply to allocation models of cloud workloads?

Rate of change of public cloud a problem?

Public Cloud adoption is happening at a very fast rate, in future I assume public cloud providers such as EC2 are going to start to hit massive problems with not being able to facilitate large volumes of customer requirements and I also predict that public cloud is certainly not capable of facilitating concurrently every single customer that has ever laid eyes on a public cloud Virtual Machine in such providers. Therefore I believe that to succeed, Public Cloud providers are going to seriously need to look at the level of service they can potentially offer and design an algorithm similar to what Airlines have developed within the Overbooking model. Remember you are not always guaranteed to get the seat on a plane that you always want but most customers are happy to take compensation in return. Interestingly the likely compensation from a public cloud provider is not likely to be high if you fail to get what workload you require....


I admit that using this comparison between Cloud providers and Airline reservations is quite a cynical view, but putting this into perspective my view is that EC2 and any other public cloud provider that is struggling to control who is able to buy a workload and who wants to use a workload is going to hit massive PR and Customer relation problems just like you get when an airline unfortunately overbooks a flight with 20-30 economy passengers.

In Part Two I delve into various areas and technologies that exist today in the Airline reservation world and align these to how they may emerge within the world of cloud as potential problems or answers to common problems.


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