Privacy Choreographer with Distributed Agents for Serverless Compliance
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Solution Overview
Problem
Current fully managed serverless application platforms lack infrastructure to automatically manage privacy controls, generate reports, and adjust settings to comply with various privacy requirements, making it impossible to obtain a risk profile in near real-time.
Innovation Solution
A privacy choreographer is introduced to embed privacy controls, deploying privacy agents across nodes to log data, aggregate and consolidate privacy compliance information, generate reports, and adjust system settings to ensure compliance with regulatory requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If privacy controls are manually managed in fully managed serverless platforms, then compliance with privacy requirements can be maintained, but the system lacks automatic management capability and near real-time risk profiling
Solution Approach 1:
The patent segments the privacy management function into distributed privacy agents deployed across individual compute resources, each agent independently monitoring and reporting privacy state. This segmentation enables automatic management without requiring a centralized complex system, as each agent operates autonomously while contributing to overall compliance monitoring.
Solution Approach 2:
The privacy agents automatically monitor their own compute resources, generate risk profiles, and trigger compliance actions without human intervention. The system performs self-diagnosis and self-correction by automatically adjusting privacy settings when non-compliance is detected, eliminating the need for manual privacy management while maintaining compliance.
2Reliability
If privacy agents are deployed across all compute resources to enable near real-time monitoring, then system-wide visibility and compliance management improve, but the complexity of the platform increases
Solution Approach 1:
The privacy agents are designed as universal components that can be deployed across any compute resource in the serverless platform. Each agent performs multiple functions including monitoring privacy settings, generating risk profiles, and triggering compliance actions, making the system reliable without requiring specialized complex infrastructure for each function.
Solution Approach 2:
The privacy agents act as intermediaries between the compute resources and the compliance management system. These agents simplify the platform architecture by providing a standardized interface for privacy monitoring and compliance reporting, reducing the complexity of direct platform-level compliance management.
3Productivity
If manual compliance checking is performed, then privacy requirements can be reviewed, but the process is time-consuming and cannot provide near real-time updates
Solution Approach 1:
The privacy agents continuously monitor privacy settings and automatically generate risk profiles in near real-time as compute resources operate. This continuous monitoring eliminates the need for periodic manual compliance checking, providing ongoing compliance assurance without interrupting system operations or requiring significant time investment.
Solution Approach 2:
The system implements continuous feedback loops where privacy agents monitor compliance status, generate risk profiles, and automatically trigger corrective actions when non-compliance is detected. This feedback mechanism ensures rapid response to privacy issues without requiring manual review, significantly improving compliance review speed while minimizing time loss.
Data Source
AI summary
Example embodiments of the present disclosure provide for an example method including receiving, from privacy agents deployed by an agent deployment engine, system metric data. The system metric data can include signals associated with compute resources based on settings or functions of a respective compute resource of the compute resources. The method can include generating a risk profile by comparing the received system metric data to current privacy state requirements. The method can include, based on the risk profile, performing an action such as (i) updating a user interface to display a notification relating to the risk profile or (ii) generating and initiating a configuration file to adjust compute resource settings.