This is the eighth installment in our weekly technical blog series about Enterprise Content Transformation: What Enterprises Need. The series kicked off with an overview of the reasons your organization needs linear scalability, high availability, easy integration with existing systems, a highly configurable platform, built-in monitoring and alerting, and system reporting.
How often are your business requirements changing? How quickly can you adapt your business systems and applications to meet these changes? Having a platform that is highly configurable and that can be managed centrally simplifies meeting your evolving business needs.
The following are some of the main Enterprise Content Transformation (ECT) characteristics encountered in enterprises:
- ECT job processing requirements can vary significantly throughout the enterprise.
- ECT can be CPU intensive and often requires multiple servers to meet the enterprise throughput needs.
- ECT is often part of mission-critical applications and is architected for high availability (HA).
Because of these reasons, the new Adlib Platform incorporates a rules engine to define conditions to resolve how the ECT system components are configured, and how content transformation jobs are processed. This enables a high degree of settings re-use, thereby reducing system configuration and testing effort.
For example, relating to content transformation job configuration, let’s say that you want to add a footer on your documents, and in some cases you want the footer font to be 10 points, and in other cases you want it to be 15 points. This can be triggered from any job metadata such as the document status (e.g. draft). This scenario requires two rules; the first default rule would define all footer settings having the text font size set to 10 points. The second rule condition would specify a condition to make the footer text size 15 points. In this case, the only footer settings defined is the text font size setting as 15. Having the ability to define settings under different conditions can significantly reduce the number of settings, which makes it easier to change them when needed.
Another example, this time relating to the platform component configuration: You have deployed the Adlib Platform and you need to add an additional transformation engine to meet increased demand. The only thing the IT administrator must do is add it to the environment.
Similarly, let’s say that you need to add a connector to provide architecture with HA. The only thing the IT administrator must do is add the connector identifier to the rule condition that is used for the redundant connector. This eliminates the need to redefine all settings for the new connector and guarantees that both connectors are configured the same. Minimizing the number of repeated settings make it very easy to change the component configurations.