Founding principles
- Article 1 of 1
- Turning IT into a dynamic optimised resource, March 2003
Over-complex. Under-utilised. Today's IT architectures are a mess. What technologies will underpin the move to a more efficient model?
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Web services will also fit into another aspect of utility computing that some vendors favour: grid computing. While the utility computing vision of a single IT resource is shared by many vendors, there is no consensus over the degree of granularity into which workloads should be split. While some favour the redeployment of applications from overtaxed to under-used servers as the lowest level of resource reallocation, grid computing allows an appropriately written application to offload some of the processes involved in the application to other machines on the network; these can then hand the results back to the original machine when complete. Grid proponents argue that this takes fuller advantage of under-used machines than application redeployment and prevents a single machine from becoming overloaded if there are no free servers to come to its assistance.
Although the complexities of creating a working, secure grid are great, the Globus project and vendors such as Platform Computing have been working for the best part of a decade to develop and deploy grid technology. IBM and others use Globus' open source toolkit to incorporate grid computing capabilities into their own software, but grid only works when it is possible to break an application down into many parallel tasks.
Limited grid
Jonathan Eunice, an analyst at industry research group Illuminata, says the much higher input-output and application performance requirements of commercial data processing environments will limit business users' enthusiasm for grid computing. “We need to stop talking as though the traditional database application is going to be distributed over a grid,” he argues. The performance overheads of dividing up the database processing tasks and then reassembling them would make that totally unpractical, he says.
Nevertheless, analyst group Gartner predicts that grid computing will become a mainstream business technology by 2008.
Some utility proponents argue that in certain cases, rather than trying to manage a large number of servers that can be re-tasked according to changes in demand, it is easier, from a systems management point of view, to have a small number of powerful servers that can be 'partitioned' into smaller virtual servers. It also means that applications that cannot be split over servers can have a highly powerful server to run on and can swap partitions if their virtual server collapses. “There are some things you'd want to use lots of small servers for, but for some applications you need 'big iron' [centralised mainframes],” says IBM's Jean Lorrain.
This partitioning is available both in hardware and software, depending on the vendor. Sun, notably, claims that Solaris 9 on its servers is the first operating system to provide both.
Sun also offers dynamic partitioning so partitioned servers can 'grow' their resources when needed to meet particular demand-peaks. This dynamic partitioning can even be arranged according to rules so that an SAP system's virtual server automatically has more resources during the day, while an email server gets more resources first thing in the morning.
Healing power
By putting all the applications on one server, however, organisations are at risk if the server collapses for whatever reason.
Hardware monitoring, hot-swappable memory and processors, redundant fans, power supplies and other components are all designed to provide the reliability needed in such situations. IBM is going one step further with its 'autonomic computing' initiative, designed to provide self-healing, self-protecting, self-optimising and self-regulating computers that are able to ward off attacks and fix their own system faults.
But autonomic computing is still a work-in-progress. Self-optimising databases, for instance, are a nice idea, but “it is a black art how databases are tuned,” says Surajit Chaudhuri, head of data management and exploration at Microsoft. “It is tough to ship a tuning guru with every database.”
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