Bulk SLT Tracking for ITSM Record Aggregation
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Solution Overview
Problem
The event-based calculation method for Service Level Target (SLT) tracking in ITSM systems incurs significant computational overhead, limiting system performance and the number of records that can be supported, which restricts the number of customers that can be committed to.
Innovation Solution
A bulk-based SLT tracking mechanism is introduced, which aggregates and compresses multiple actions performed on ITSM records within a predetermined time frame, reducing computational strain by translating actions into aggregate types and applying them in a single operation to the SLT database table.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If event-based calculation method is used for SLT tracking, then SLT tracking accuracy is improved, but computational overhead increases significantly
Solution Approach 1:
The patent implements periodic action by updating SLT database tables at predetermined time intervals rather than continuously. The system aggregates actions occurring between updates and applies them in bulk operations, reducing computational frequency while maintaining tracking accuracy. This periodic approach resolves the contradiction by decoupling continuous monitoring requirements from computational execution frequency.
Solution Approach 2:
The patent applies preliminary action by pre-defining action types and their corresponding database table updates before they occur. Action types are categorized in advance (e.g., start, stop, suspend, unsuspend), and their impact on SLT records is pre-determined. This allows the system to process actions efficiently by matching them to predefined patterns rather than evaluating each action's impact in real-time, significantly reducing computational overhead while maintaining accuracy.
2Measurement precision
If event-based calculation method is used for SLT tracking, then SLT tracking accuracy is improved, but system performance deteriorates
Solution Approach 1:
The patent merges multiple individual action processing operations into a single bulk operation. Instead of processing each action separately against the SLT database tables, the system aggregates all actions occurring within a time period and applies them simultaneously through unified database operations. This merging approach maintains tracking accuracy while dramatically improving system performance by reducing the number of individual processing cycles.
Solution Approach 2:
The system pre-establishes action type mappings and their corresponding database update logic before runtime. When actions occur, they are immediately classified into predefined action types, and their effects are pre-calculated. This preliminary preparation eliminates complex real-time decision-making during action processing, maintaining measurement precision while boosting system performance through simplified, pre-determined processing paths.
3Measurement precision
If event-based calculation method is used for SLT tracking, then SLT tracking accuracy is improved, but the number of supported records decreases
Solution Approach 1:
The patent uses periodic action to batch process multiple records together. By updating SLT database tables at predetermined intervals rather than continuously for each record, the system can handle larger quantities of records without proportionally increasing computational load. The periodic aggregation of actions across multiple records maintains tracking accuracy while enabling support for greater record volumes.
Solution Approach 2:
The system pre-categorizes actions into action types that map to standardized database update patterns. This preliminary classification allows the system to process records in bulk using template-based operations rather than custom processing for each record type. The pre-defined action type to table mapping enables efficient handling of large record sets while maintaining precise tracking through consistent, pre-determined update logic.
Data Source
AI summary
Information technology service management records in a service level target database table may include aggregating, at a predetermined elapsed time, a plurality of actions performed on each of a plurality of ITSM records since a prior update of an SLT database. Service level target tracking may further include identifying a portion of the plurality of aggregated actions that are applicable to an SLT database table entry corresponding to an ITSM record of the plurality of ITSM records. Service level target tracking may also include compressing, in a single operation, the portion of the plurality of aggregated actions.