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Orchestrating Grid Workloads w/ Tivoli

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What's the biggest roadblock to acceptance of an On Demand Business environment? It isn't technology. The e-business world provides many examples of technology evolving quickly to support new needs. The biggest roadblock is politics. By itself, On Demand Business is an apolitical model: it looks at what's needed to ensure that all resources are used to the best benefit of the enterprise. But the enterprise is extremely political. Since these two models -- the apolitical On Demand Business environment and the political enterprise -- are diametrically opposed, we need technology that encourages enterprise "kingdoms" to share their resources. As grid computing moves from purely scientific and mathematical use to a more utility-based model, the technology to leverage the proper use of servers in this environment must be in place.

In this article, I'll draw examples from some work we did in the IBM Design Center for On Demand Business for a financial institution. The models used were based on grid workloads that followed trading examples, but they're representative of basic grid workload models we've seen for a number of different business clients.

For the financial institution, we used IBM TivoliĀ® Intelligent Orchestrator (TIO) software because it enables an organization to add and remove servers from a processing environment based on the needs of that environment. Traditionally, TIO has been deployed in Web-based environments to ensure the best use of servers throughout multiple tiers. This has been accomplished by analyzing the CPU use of the server and the rate of work to the server from the network. If TIO can be adapted to serve the grids as well, it would be a powerful tool for managing servers across multiple heterogeneous environments. Suddenly, servers become commodities to share across departments -- hoarding of departmental server resources can become a thing of the past. This article defines the methodology used to transform the TIO product in its traditional Web-based world into one of looking across multiple worlds.

The business problem
Enterprises constantly struggle to find the best way to manage their hardware, software, and management resources. Often new applications drag with them a new set of servers. To ensure servers will handle expected demand, capacity planners frequently overestimate the load to ensure there is enough room for growth as the application usage rises. If the estimate is too low, performance suffers. If the estimate is too high, resources are wasted. Since the typical political climate discourages sharing of resources, the wasted resources are never used. The disturbing thing to CIO and IT organizations is that such wasted resources can never be brought to bear on resource-starved applications. Some users can be stuck with poorly performing applications while perfectly useful resources lie idle.

The solution
Several technologies are coming together now to solve this problem. The advent of efficient Web services, the proliferation of J2EE underpinnings for those Web services, and the power of grid computing allow application components to be efficiently deployed within a heterogeneous environment. Applications have become less platform- and infrastructure-dependent and more focused on solving business problems. This paves the way for using grids in a utility model. In environments where multiple grids must contend for the same resources or must share resources with non-grid environments, we need something outside the grid to ensure proper deployment of servers. In our work with the financial institution, we used IBM Tivoli Intelligent Orchestrator (TIO) to fill this need. TIO also provides the ability to track deployments of server environments, which allows a person to keep track of how and for whom a server deployment is carried out. Simply put, TIO provides the framework for removing the political as well as technical barriers that might stand in the way of an enterprise becoming more of an On Demand Business.

In our work with the financial institution, we combined Tivoli Intelligent Orchestrator with DataSynapse GridServer. Let's look briefly at these products so you can get an idea of how they work together.

Grid resource managers manage workload from requesters to the available grid engines. What happens when there's more work than available engines can handle? Traditionally, this condition causes queuing and additional wait times for the user community. This article discusses how resources can be managed into and out of a grid environment using an example infrastructure.
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