Partial Configuration Item Reconciliation With Streaming Processing
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Solution Overview
Problem
Existing discovery processes often fail to fully identify computer hardware and software components, resulting in partial configuration items with missing attributes, which are inefficient and ineffective, and techniques for disambiguating these items are memory-intensive.
Innovation Solution
Perform secondary reconciliation on partial configuration items using a different discovery data source or a trained machine learning model to predict missing attributes, and implement an efficient streaming or pipelined fashion for reconciliation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If discovery operations are performed to identify configuration items, then identification completeness improves, but memory consumption increases
Solution Approach 1:
The patent segments the discovery and reconciliation process into multiple passes or stages. Configuration items are processed in batches rather than all at once, allowing the system to maintain only a manageable subset of configuration items in memory at any given time. This segmentation enables complete identification of all configuration items across the network while keeping peak memory consumption within acceptable limits.
Solution Approach 2:
The patent performs preliminary filtering and prioritization of configuration items before the main discovery process. By identifying and separating configuration items that are likely to be fully discoverable from those that may be partial, the system can allocate memory resources more efficiently and focus intensive discovery operations on items that require them.
2Measurement precision
If techniques are used to disambiguate partial configuration items, then identification accuracy improves, but processing efficiency deteriorates
Solution Approach 1:
The patent implements self-service mechanisms where the discovery system automatically detects partial configuration items and triggers targeted reconciliation operations without requiring manual intervention. The system autonomously determines which configuration items need disambiguation and applies appropriate resolution techniques, thereby maintaining high identification accuracy while minimizing the overhead associated with manual processing.
Solution Approach 2:
The patent incorporates feedback loops where the results of discovery operations are continuously analyzed to identify partial configuration items. This feedback drives iterative refinement of the configuration item database, with each pass improving identification accuracy based on lessons learned from previous passes. The feedback mechanism allows the system to adapt its disambiguation strategies dynamically.
3Reliability
If secondary reconciliation is performed on all partial configuration items, then data quality improves, but processing time increases
Solution Approach 1:
The patent applies partial action by performing secondary reconciliation selectively on only those configuration items that are identified as partial or incomplete. Rather than universally reconciling all configuration items, the system uses heuristics and analysis of discovery results to identify the subset of items that actually require secondary reconciliation. This approach maintains high data quality for the critical subset while avoiding the time penalty of processing all items uniformly.
Solution Approach 2:
The patent dynamically adjusts reconciliation parameters such as the threshold for what constitutes a partial configuration item, the aggressiveness of reconciliation operations, and the batching size for processing. By changing these parameters based on system workload, data characteristics, and quality requirements, the system can optimize the balance between data quality improvement and processing time consumption.
Data Source
AI summary
An example embodiment may involve determining that a configuration item has failed identification, wherein the configuration item represents computing hardware or software associated with a network; based on the configuration item failing identification, performing a reconciliation procedure, wherein the reconciliation procedure modifies an attribute of the configuration item; determining that the configuration item as modified passes identification; and writing, to a database, the configuration item as modified.