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An extensible Java tool utilising a spreadsheet for managing complex system configuration parameters.

IP.com Disclosure Number: IPCOM000232277D
Publication Date: 2013-Oct-30
Document File: 6 page(s) / 275K

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Abstract

An extensible Java tool utilising a spreadsheet for managing complex system configuration parameters.

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An extensible Java tool utilising a spreadsheet for managing complex system configuration parameters

An extensible Java tool utilising a spreadsheet for managing complex system configuration parameters.

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In a typical enterprise installation, the management of configuration data for an integration platform is a complex task. Even the most basic of installations tend to require a large number of 'variables' to be set, examples may include
resource names (e.g. JMS queues), locations (such as file systems) and quantitive values (such as queue depths, port numbers or thread pool sizes). In a typical Customer scenario, the management of these settings exists across multiple environments, ranging from Development environments, through to multiple Test environments and ultimately, Production environments. Not only does each environment require its own configuration data, but as the number of environments increases, so to does the task of ensuring that resources are allocated to each environment correctly, and that inadvertent sharing of resources, such as wrongly assigning the same IP port to 2 different systems, does not occur. In all but the smallest of installations, the task of correctly assigning configuration details to servers, and providing ongoing maintenance of the configuration, is a significant burden on the System Admin staff. Of course, even larger scale Enterprise deployments prove even more difficult to configure effectively.

In all of the installations I have been involved with, I have seen a variety of home-grown tools, mainly based around definition files, used to manage the system configuration. I have not seen a formal tool designed to address this problem.

The problem with the solutions I have witnessed to date is that they tend to rely on someone making changes to multiple configuration files, and then manually checking each file to ensure that values entered do not conflict with existing entries. The approach is inherently flawed due to the increase risk of error as the number of systems (and configuration files) grows. It is also highly susceptible to mistakes being made due to typos as values are entered. Very often, the first indication of a configuration error is when
a new or changes system fails to initialise, or worse still, fails some time later when the incorrect dependency is encountered. Arguably the worst effect of a configuration error is when the problem only comes to light long after the system has been deployed , and odd behaviours are noticed due to inadvertent sharing of resources between affected systems.

My approach utilises patterns and the power of the human eye to spot these as a way of simplifying the task of managing middleware configuration values. It is based on 2 fundamental premises:


1. The overwhelming majority of server installations within a customer location use naming conventions (or recognised patterns) to name and identify resources. Furthermore, resources that are related will g...