Regional Knowledge Base Sharding for Data Sovereignty
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Solution Overview
Problem
Modern enterprises face challenges in maintaining and disseminating knowledge across globally distributed data sources while adhering to data sovereignty principles, as existing technologies struggle to efficiently extract and surface relevant information from regionally separated data stores.
Innovation Solution
The implementation of a clustering service that creates and manages knowledge base shards across multiple geographic regions, allowing for geographically specific data storage while enabling geographically agnostic topic surfacing, by analyzing and sharding data extracts from various regions and reconstituting them at query time to present consistent information to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in regionally separated data stores to comply with data sovereignty principles, then data sovereignty compliance is improved, but information accessibility and unity across the enterprise deteriorates
Solution Approach 1:
The knowledge base is segmented into multiple shards distributed across different geographic regions. Each shard contains a portion of the knowledge base data and is stored in a specific region to comply with data sovereignty requirements. The system maintains multiple shards (first shard, second shard, etc.) that collectively represent the complete knowledge base while being geographically distributed.
Solution Approach 2:
A clustering service acts as an intermediary between users and the distributed knowledge base shards. The clustering service receives queries, determines which shards are relevant, retrieves data from multiple shards across different regions, and synthesizes the results into a unified response. This intermediary layer abstracts the complexity of data distribution from users while maintaining data sovereignty compliance.
2Reliability
If data is extracted and stored in multiple geographic regions, then data sovereignty compliance is improved, but system complexity increases
Solution Approach 1:
The clustering service automatically performs shard identification, data retrieval, and result synthesis without requiring manual intervention. The system self-manages the complexity of coordinating multiple regional data stores by implementing automated processes for determining relevant shards, extracting data, and combining results into unified knowledge base entries.
Solution Approach 2:
The clustering service performs multiple functions: it acts as a query router, data extractor, result synthesizer, and knowledge base maintainer. This multi-functional component handles various aspects of managing the distributed knowledge base, reducing the need for separate specialized systems for each function.
3Reliability
If knowledge base shards are distributed across regions, then data sovereignty compliance is improved, but query processing time increases
Solution Approach 1:
The system pre-identifies and pre-organizes knowledge base entries into appropriate shards based on their regional associations. The clustering service maintains knowledge about which entries belong to which shards and regions in advance, so when a query is received, it can immediately retrieve the relevant shard information without performing complex real-time analysis or data movement.
Data Source
AI summary
Extracting and surfacing information corresponding to individual logical topics from enterprise data stores that are separated across multiple geographic regions. A clustering service creates, by utilizing machine learning toolkits that are agnostic to the region in which data is stored, individual topics that have references to multiple shards of data that are stored in different geographic regions. The clustering service also shards the knowledge base state according to the regions from which pieces of data for the particular logical topic was extracted. For example, a first shard containing information extracted from a first document may be stored in a first region whereas a second shard containing information extracted from a second document may be stored in a second region. Responsive to user activity associated with the topic, a serving platform may identify and reconstitute these shards that are stored in different regions so as to surface the regionally extracted and sharded information on that topic to a user.