SLA Focused Financial Grids
The financial sector depends heavily on process and data intensive computations to deliver competitive advantage. Financial applications are particularly suited to grid-based experimentation and research. A Financial Live Trading System is used an exemplar in this article. The emerging growth of worldwide trading and the reliance on automated processing has increased the complexity and volatility of the computational demand which generally exceeds the resource available at the financial customer site. SOA-based grid infrastructure has emerged as a viable commercial alternatives to meet this demand. However, grid infrastructures can only become viable solution to the financial sector if they can provide stable service level assurance.
The scenario that presented in this article assumes that a client company has a contract with a financial service provider to provide processed market data for the company’s internal use; this may be in the provision of additional services to other users.
In the Financial Live Trading System scenario there are five actors:
- the Financial Service Customer who is the consumer of the processed market data;
- the Financial Service Provider who sells processed financial or market data to a collection of customers;
- the Software Provider that provides software via a licensing agreement to business organisations;
- the Compute Provider that provides hosting and compute capabilities to customers; and
- the Data Provider that provides a feed of up-to-date market data and financial information.
A Live Trading System processes live market data from the Data Provider using compute resources hosted by the Compute Provider, running software from the Software Provider to supply processed data to the customer. A Trading System demands a high availability of resources. Non-availability of resources means an absence in market trading which, in turn, can lead to missed opportunities. Security is of paramount importance. In addition, regulatory issues exist within institutions that place restrictions on the accessibility of spatial information across their distributed enterprises.
As described in the above figure, Financial Service Provider supplies the trade data from the Live Trading System to the Financial Service Customer. The business SLA is agreed offline between the Financial Service Customer and Financial Service Provider. In order to meet the business SLA requirements, the Financial Service Provider need to establish separate SLAs with the Software Provider, Compute Provider and Data Provider. These SLAs need to be monitored and observed carefully.
Two of the critical customer requirements in the above scenario are the high availability of compute resource and legislation compliances. If one of the compute resources provided by the Compute Provider fails, the Financial Service Provider has to switch to a backup resource or look for another computer provider which must also satisfy other regulatory requirements in a fast, efficient and accurate manner.
In the current implementation, this usually means a significant down time and potentially a breach of the SLA agreements with the Financial Service Customer. In our proposed SLA-focus solution, the failure of the compute resource will be detected and the discovery of new compute resource that satisfy the regulatory requirements will be performed automatically. A new SLA with the new Computer Provider is established and the software is deployed in a very fast and automated manner. The data feed or necessary calculation may then be restarted at the new compute resource. From the SLA point of view, this would only affect the customers in terms of a very short delay. Potential penalties due to the violation or breaching of SLA are reduced significantly.
Tags: advantage, availability, competitive advantage, financial, Financial applications, Financial Grids, Financial Live Trading System, financial service provider, grid infrastructure, grids, sla, SOA, trading
