Multi-Zone Data Routing for Compliant Low-Latency Access
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Solution Overview
Problem
Centralized storage of user data for SaaS applications in a single physical location poses challenges such as non-compliance with data export regulations, increased network congestion, and single points of failure, leading to undesirable user experiences.
Innovation Solution
A multi-zone computing platform distributes user data across multiple physically and logically separated zones, maintaining a global representation of data objects and relationships, enabling zones to route access requests efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If user data is stored in a centralized manner at a single physical location, then data management and access control are simplified, but compliance with data export regulations becomes difficult and single points of failure increase
Solution Approach 1:
The system segments user data into multiple data objects distributed across different physical zones (first zone, second zone, etc.). Each zone stores a portion of the data objects, eliminating the single point of failure and enabling compliance with data export regulations by keeping data closer to users in different geographic regions while maintaining simplified access through the global representation.
2Device complexity
If user data is stored in a centralized manner, then storage infrastructure is simplified, but network congestion and access delays increase for users in different locations
Solution Approach 1:
The system introduces a new dimension of data organization through the global representation, which provides a unified view of distributed data objects across multiple zones. This allows users to access data from the nearest zone without increasing storage infrastructure complexity, as the global representation efficiently routes requests to the appropriate zone based on user location and data object placement.
3Reliability
If user data is distributed across multiple physical locations, then compliance with data export regulations and reduction of network delays are improved, but data access and retrieval complexity increases
Solution Approach 1:
The global representation acts as an intermediary between users and the distributed data objects. It maintains metadata about the location and status of data objects across different zones, enabling the system to resolve data access requests without requiring users or applications to understand the underlying distribution complexity. The global representation translates high-level data access requests into zone-specific operations.
Data Source
AI summary
A computing system that defines a first zone of a multi-zone computing platform is configured to (1) receive a request to access at least one given data object that is stored within the multi-zone computing platform, (2) obtain, from a global representation of available data that is stored within the multi-zone computing platform, a routing address that includes information indicating where the at least one given data object is stored, (3) validate the request to access the at least one given data object, (4) determine that the request is valid and should be allowed, (5) determine whether the at least one given data object is stored at the first zone, and (6) based on the determination, either retrieve the at least one given data object from the first zone or issue a request to retrieve the at least one given data object from a second zone.