May 21
Considering the fact, that only 30-40% of the energy consumed by a data center is used by the actual computational equipment and considering that another 30%-40% of the energy consumed by the IT equipment is converted to heat, only 21%-24% of the energy eaten up in data center is actually converted into computing power. Looking at these numbers from the other side means for each Euro spent on “computational energy” 4,76 Euro are spent on “overhead”. This ration can be improved by optimizing air conditioning, getting rid of heat hot spots or generally using energy efficient and modern equipment. Still it seems unlikely that this will help to get anywhere below 3 Euros of “overhead” for each Euro spent on “computational energy”. These numbers are taken out of the keynote presentation given by Steven Sams at IBM PULSE 2008 (Also check out the “Raised Floor Blog”, where Steven Sams is one of the authors)
On the other hand this means that reducing the energy needed for computational equipment will in absolute numbers decrease the excess energy consumption by a factor of more than 4. So improving the facility is a good start, but reducing the energy actually needed by computational equipment is the real price. The way to reduce energy needed is a direct result from capacity management. Generally speaking this means – in the best case – turning off as many components as possible – or if that is not possible, at least cutting their energy usage by slowing the CPUs or putting virtual instances into suspend mode until their service is really required. Does this sound easy? Well it does, but how does it work? Virtualization certainly is the key technology, but what good would virtual machines be, if their resources could not be allocated automatically depending o their actual use or – if you want to be cautious – by their predicted load and therefore by their predicted usage. A specialized set of rules is put behind process and operational automation, to perform the scale-down and scale-up of the virtual machine resources. This automation can even decide to turn off hardware, that is currently not needed or at least to slow the CPUs of hardware that cannot be turned off, but is in little use.
Modern “or very green systems” come along with special agent to detect energy consumption and usage deriving possible executions. But how about all the legacy applications – the applications that are running on more than 95% of all the components, using up energy in our data centers today? An automation engine that actually acts like an operator (someone who could manually cut down on power use) could examine the equipment in the IT landscape it is acting upon and execute general rules to reduce energy usage. By combining both technologies – the more effective combination of modern hardware and specialized software for new applications and a general automation engine for all the legacy applications – the power of virtualized components can actually be converted to green power. This is not just a fabulous business case, but it also is a good thing for the environment and hence for all of us.
May 21
Yesterday I had the chance to get a feeling for one of the hottest topics in IT infrastructure. A panel session at IBM PULSE 2008 was dedicated to the topic of Cloud Computing (even though IBM marketing people don´t seem to like the term and have come up with quite some innovative words – words no one uses, so let us stick with the cloud). The panel was buzzing with intelligence, unfortunately we as the audience could not really match up. So we listened to a pretty much directed discussion on how cloud computing would replace today´s approach to hardware and infrastructure in general. Well I do agree, no one needs dedicated servers when resources can be allocated dynamically and come preconfigured and interconnected. Kristin Hansen stripped the key features of a cloud down to simplicity (users do not care how their resources are set up, they just use them), mobility (obviously use is possible from anywhere and even a large computing cluster could be controlled from a phone like device) and elasticity (you only setup or pay what you really need). Sounds fine to everyone and Google and Amazon have definitely shown to the world that this concept works in a closed shop environment. According to Dave Lindquist IBM is working on a methodology and technology to make most applications “cloudable”. The most interesting remark I heard during the discussion was the “Cloud Computing is the combination of technology (virtualization and automation) and discipline (a stringent way of breaking down the offered services into small blocks in order to recombine them quickly and automatically upon the user´s request as well as defining standards or service catalogues to be offered)”. I guess the discipline part will put forth a great deal of discussions between process consultants and methodology consultants and in the end there will certainly be a couple of good ways to set things up. Just as certainly there will be the need to standardize these processes and methodologies in the end, so clouds are not proprietary but keep mobile even between cloud providers.
Naturally I am more interested in the technology part, that is needed behind cloud computing. Technology - in this case - not referring to the cloud management servers and agents themselves, but the technology surrounding them. The first technology that comes to mind is virtualization as without this core there will be no cloud, at least no cloud that can integrate legacy applications rather than working in a very tightly closed universe like Google does. There are quite some good approaches to virtualization – commercially as well as open source – and the approach taken should really depend on the needs of the applications to be run on a specific part of the cloud. It does probably make sense to even merge the available virtualization technologies within one cloud. It might make sense to use containers build into the operating system or complete hardware virtualization depending on the kind of application to be run and therefore a cloud manager will have to deal with all kinds of virtualization technology.
More on my focus is the service management side of cloud computing and I strongly believe that automated operating is a key component of a good cloud infrastructure. Definitely the cloud infrastructure and management components will take care auf automatic provisioning and resource management, but as soon as legacy applications – that do not really know that they are running on a beautifully scalable environment – are involved manual administration of these applications would mean chasing an ever changing rabbit across a chameleon planet – an image most amusing to bystanders but neither funny to administrators nor to the ones paying them. So in my opinion an automation engine could be fed IT model data and monitoring feeds directly from the cloud manager and could thus deal with the ever changing environment and keep the application automation rules up to date with the cloud components currently in use. This automation engine cannot use a drill down approach, because the infrastructure might not even support drill downs and can change ever so often. The automation engine assuring a good foundation for quality service a professional service management will have to use a more human “circle in” or divide and conquer approach.
Does this sound familiar? By the way, check out the articles on the “Blue Cloud”; technical pioneers at work (other bloggers also think about the blue cloud)…. Also interesting is the cooperation between Google and IBM on producing cloud standards
