Profile Store Synchronization via Dynamic Catch-Up Service
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Solution Overview
Problem
Real-time synchronization of data between a profile store and a source of truth is disrupted due to faulty configurations, network outages, manual modifications, software bugs, or bulk data extractions, leading to mismatches and inaccuracies in the profile store.
Innovation Solution
A catch-up service is implemented to detect and correct mismatches by comparing attributes from the profile store with those from the source of truth, using separate network connections and a mapping to update the profile store with accurate values, while varying the comparison rate based on execution conditions such as load and service-level agreements to minimize interference with other services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time synchronization is implemented between profile store and source of truth, then data accuracy is improved, but system reliability deteriorates due to synchronization disruptions from network outages, configuration errors, and manual modifications
Solution Approach 1:
The catch-up service continuously monitors the synchronization status between the profile store and source of truth, detecting mismatches and triggering corrective actions. This feedback mechanism ensures that synchronization issues are identified and resolved automatically, maintaining data accuracy while improving reliability through continuous verification and correction.
Solution Approach 2:
The system implements proactive synchronization checks and error handling mechanisms that prevent synchronization failures from affecting overall system reliability. By preparing cushioning measures such as error detection, automatic correction, and fallback mechanisms, the system can withstand network outages, configuration errors, and manual modifications without compromising data integrity.
2Measurement precision
If frequent synchronization checks are performed to maintain data accuracy, then measurement precision is improved, but device complexity increases due to multiple network connections and comparison mechanisms
Solution Approach 1:
The catch-up service is designed as a multi-functional component that handles multiple tasks: monitoring synchronization status, detecting mismatches, comparing attributes, and executing corrections. By consolidating these functions into a single service, the system achieves high data accuracy through frequent checks while avoiding the complexity increase that would result from separate dedicated components for each function.
3Measurement precision
If synchronization comparisons are performed at high rate to ensure data accuracy, then measurement precision is improved, but loss of time increases due to interference with other services and bulk data extraction operations
Solution Approach 1:
The catch-up service dynamically adjusts its operation rate based on system conditions, switching between high-frequency comparisons during normal operation and low-frequency checks during bulk data extraction or high-load periods. This dynamic rate adjustment ensures data accuracy is maintained during normal conditions while minimizing time loss and interference with other critical services during peak demand periods.
Solution Approach 2:
The system implements periodic synchronization checks with variable intervals, performing frequent comparisons during normal operation and reducing frequency during bulk data extraction or high-load periods. This periodic action pattern ensures data accuracy is maintained through regular verification while managing time loss by avoiding continuous high-frequency checks that would interfere with other services.
Data Source
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AI summary
The disclosed embodiments provide a system that manages synchronization between a profile store and a source of truth that is used to update the profile store via a real-time link. During operation, the system obtains a first set of attributes from a profile for an entity in the profile store. Next, the system obtains a second set of attributes for the entity from the source of truth. The system then compares the first and second sets of attributes to detect and correct mismatches between the first and second sets of attributes, wherein the corrected mismatches improve subsequent use of the profile in the profile store by the set of remote offerings. Finally, the system varies a rate of comparing the first and second sets of attributes for the mismatches based on one or more execution conditions associated with the source of truth.