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Grid in the Enterprise
Enterprises have their own complex applications and huge repositories of data which also require high if not mammoth (as is the case with scientific data) computational power to analyze. And not surprisingly, vendors like Sun Microsystems, Oracle, Fujitsu, and Informatica as well as others have started utilizing and implementing grid based solutions to tackle diverse issues. For example, Sun and Informatica are providing grid computing based solutions for data centric needs of organizations. They also provide data integration using a grid. By using a grid for data centric needs brings with it major advantages such as high availability, automatic recovery, adaptive load balancing where-in load balancing works on the basis of situation at hand, and also sessions on Grid. Similarly Oracle's grid implementations cover a wide range of services for the enterprise.
The most interesting one from these is the grid solution for SOA runtime governance and SOA infrastructure monitoring. Now this is really interesting because as you would know and as we have gone on record saying that SOA implementations more often than not bring together a variety of systems, components, and applications under one roof. Implementing a grid control for SOA runtime governance would make runtime recording of service requests, monitoring the complex process flows and similar tasks easier and more manageable due to the high grade computation power that grid provides. Other than this their grid solution also supports identity management, and the other wise cumbersome task of application server cluster deployment.
With the grid making a steady progress into enterprises, for primarily smoothing out management or deployment of very large implementations, these technologies can surely address a lot more pain areas if carefully matured over time. After all, who would not want their processes, analytics or even data needs to be not limited by computational power or storage considerations.
Emerging trends
Let's now consider some of the latest trends in this sphere.
P2P Grid: One of the newest technologies in grid computing is P2P grids. We talked about it in the December issue of PCQuest in detail and also showed how to implement it. P-Grid is essentially a grid that runs over P2P connections. Both the data transfer and the CPU cycle migration are done over P2P. Currently, the framework being used runs on Gnutella network.
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| Between Nov 97 and Feb 06, PrimeNet Grid has handled 11,579,649,914 P90 machine-hours. Its throughput rate can be characterized by a fitted, exponential trend line |
Although, there is no full-fledged application available which can leverage such a concept, you can use an application called GPU (downloadable from http://gpu.sf. net). This application is still an alpha and can only run some test applications such as Image Rendering, Net Crawling, etc.
But imagine what will happen when this technology matures. Any one with a machine and an Internet connection can become a part of a public Grid and share processing power the same way as we share MP3 and music files today. So, in that case we will truly be able to achieve Internet computing or rather Internet Super Computing.
Grid management: You must have heard about many types of grids and clusters and read about them in PCQuest, such as heterogeneous Grid Platform called Condor, or Globus or some simple clustering middleware such as SSI-based like OpenMosix and MPI-based ones like Oscar and Flash Mob etc. If you search over the Net, you will find there are quite a few different kinds of grid products available. Some have a graphical front end to monitor the nodes and some even don't have one. Let's take a classic example, OpenMosix.
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| In a matter of 5 mins, we were able to connect to a P2P grid with 10 GB of RAM and 10 GFlops of processing power using GPU |
This one has a graphical monitoring application called OpenMosixView, but have you ever noticed that if the number grows to something around a hundred nodes, then how difficult it becomes to monitor? Plus, it only shows you the current RAM and CPU utilization of the nodes. What about the disk usage? Or if in case, you want to see what the CPU utilization was in the last one hour or day, then?
These are things which are very difficult to monitor in case of large grids or clusters. To make things worse, let's say you have multiple grids, one based on Condor and the other one on Globas. Another one could just be a cluster using Oscar or ROCKS with MPI support. And you want to monitor both of them from one place. Then, what will you do?
Let's take a case of a cluster or a grid with hundreds and thousands of nodes over a wide geographical distribution. Managing them all from one place can be really difficult. So, this is one area that is picking up on the Grid technology front. The most common and popular tool out there which solves this purpose is Ganglia. We have talked about this in detail in our June 2006 issue. And this is the one being used by most of the biggies using Grid technologies such as NASA, CRAY, SUN, Boeing, US Air Force and Microsoft.
| Glossary |
| Cluster Interconnect: A very high speed connection allowing computers in a cluster to interconnect. Enterprise Grid Alliance: A vendor-neutral, open and independent organization that works as a consortium for focusing on obstacles enterprises face in grid implementations, and promoting open and interoperable solutions for problems.
Enterprise Grid: A collection of networked components including systems, applications like CRM, ERP etc. usually managed by a distinct business entity providing a set of services and assignment of resources to these services for accomplishing business goals.
N1: Sun's architecture for next-generation data-center that makes the entire data center work as one single, unified system. It reduces management and costs, increases the data-center resource utilization, infrastructure responsiveness, and agility.
Utility Computing: 'PAY-AS-YOU-GO' model of computing analogous electricity usage. Instead of paying for computing resources to handle peak load all the time it requires paying only for the computing used.
Utility Data-Center: An infrastructure solution proposed by HP that allows virtualization of computing resources for the data center. The Utility Data Center includes servers, storage, and networking products that are integrated and deployed by intelligent management software that allows them to be shared and dynamically re-provisioned to accommodate changing workloads.
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Source: PC Quest
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