Business Process Logging Granularity Assignment
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Solution Overview
Problem
Current business process logging systems face performance issues due to a single, uniform logging granularity, which leads to excessive database space consumption and reduced process execution speed, as all entities within a business process are logged at a fine granularity, increasing the total cost of ownership without meeting actual requirements.
Innovation Solution
The system automatically assigns different logging granularities to various entities within a business process instance based on design-time and runtime determinations, using a combination of rules and meta-model entity assignments, allowing for manual modifications and dynamic adjustments at runtime, thereby reducing the amount of logged information and improving performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If uniform fine granularity logging is applied to all business process entities, then complete process information is captured, but database space consumption increases excessively
Solution Approach 1:
The patent applies different logging granularities to different business process entities based on their specific requirements. Critical entities receive fine granularity logging while less critical entities receive coarser logging, thereby reducing overall data volume while maintaining necessary information completeness for key process elements.
Solution Approach 2:
The system dynamically adjusts the logging granularity parameter based on entity properties, execution context, and configurable rules. This allows the logging system to adapt the level of detail captured for each entity type, balancing information completeness with storage efficiency.
2Loss of information
If uniform fine granularity logging is applied to all business process entities, then complete process information is captured, but process execution speed decreases
Solution Approach 1:
By applying fine granularity logging only to critical entities and coarser logging to less critical entities, the system reduces the overall logging overhead during execution, thereby improving process execution speed while maintaining complete information capture where necessary.
Solution Approach 2:
The system applies logging at the minimum necessary granularity for each entity type rather than uniformly applying maximum granularity to all entities. This partial application of fine-grained logging reduces unnecessary processing overhead while ensuring sufficient information capture for process monitoring and analysis.
3Stability of the object's composition
If uniform logging granularity is used, then consistent logging behavior is achieved, but the total cost of ownership increases
Solution Approach 1:
The patent implements differentiated logging strategies for different entity types and contexts, reducing the volume of logged data and associated costs while maintaining consistent and predictable logging behavior through structured rules and policies.
Data Source
AI summary
The present disclosure involves systems, software, and computer implemented methods for assigning business process logging granularities. One process includes identifying a business process model where the business process model defines a set of business process entities operable when executed to perform a defined business process, identifying a logging granularity rule set associated with the identified business process model, determining at least one entity property associated with at least one business process entity in the identified business process model, and automatically assigning the at least one business process entity in the identified business process model with a logging granularity level associated with the at least one determined entity property based at least in part on the identified logging granularity rule set. The logging granularity levels can correspond to an amount of logging-related information to be collected at runtime for a particular business process entity.