Last month the UC Berkeley Reliable Adaptive Distributed Systems Laboratory (aka RAD Lab) published Above the Clouds: A Berkeley View of Cloud Computing.
The report is an excellent overview of the move to cloud computing. It identifies some key trends, addresses the top obstacles to cloud use, and makes some excellent points about cloud economics. It also, in my view, understates a few aspects of cloud computing as well, primarily as a result of addressing the topic with an academic detachment.
Overall, it’s well worth tracking down and giving a read.
RAD defines cloud computing as having the following three characteristics:
1. The illusion of infinite computing resources available on demand, thereby eliminating the need for Cloud Computing users to plan far ahead for provisioning.
2.The elimination of an up-front commitment by Cloud users, thereby allowing companies to start small and increase hardware resources only when there is an increase in their needs. .
3. The ability to pay for use of computing resources on a short-term basis as needed (e.g., processors by the hour and storage by the day) and release them as needed, thereby rewarding conservation by letting machines and storage go when they are no longer useful.
From RAD’s point of view, an underlying requirement for these capabilities to be considered as cloud, they have to be available publicly, i.e., externally.
Therefore, by definition, what is often referred to as “internal clouds” is not part of the RAD discussion. This is an interesting perspective on the part of RAD. Certainly a significant part of the vendor community (e.g., IBM et al) are trumpeting the transformation of internal data centers into cloud environments, and therefore RAD is standing apart from that trend.
From a definition perspective, it would be easy to dismiss internal clouds due to requirement #1; however, RAD does not identify the lack of infinite resource illusion as the reason to exclude internal clouds from the cloud computing discussion. Instead, it defines external availability as the key condition, thereby excluding internal clouds altogether.
I will have more to say about internal clouds in the near future, but I believe the key issues involving them relate more to the characteristics listed above, rather than whether or not any Tom, Dick, or Harry can access them.
Canadian firms lead in adopting cloud computing RAD goes on to list ten objections (or impediments) to cloud computing:
1. Availability of Service Use Multiple Cloud Providers .
2. Data Lock-In.
3. Data Confidentiality and Auditability.
4. Data Transfer Bottlenecks .
5.Performance Unpredictability.
6. Scalable Storage .
7. Bugs in Large Distributed Systems .
8. Scaling Quickly .
9. Reputation Fate Sharing .
10.Software Licensing Pay-for-use licenses.
The report also offers ways to mitigate each of the impediments, some of which make sense, and some of them which don’t. For example, impediment #4: data transfer roadblocks refers to the fact that if you have large amounts of data to process, your Internet connection can effectively throttle the speed at which you can upload it and delay starting work on the data. Animation rendering is a good poster child for this; the average animated movie is an ideal candidate for cloud computing as the task can be spread across many machines and the load is transient, since there is a finite amount of time rendering goes on: at some point the movie must be released, ending the need for rendering until the next movie comes down the pike.
RAD recommends exploring “fedexing” entire disks to the cloud provider to overcome bandwidth limitations. They quote calculations that show that this option is 75 times as fast as using the network.
My reaction is that Pixar can probably get special handling for its situation, but that a typical medium-sized IT shop is unlikely to get Amazon’s attention, so the attractiveness of this option will remain theoretical for most users.
Overall, their list of impediments is not incorrect; however, they are presented as if they are all of equal weight, whereas some of them will have more impact on cloud adoptions than others. I will discuss the most important impediments in this list later in this post.
The next part of the series contains RAD Lab’s key cloud computing recommendations.
Read: Cloud computing lessons from UC Berkeley – Part 2