Representative System File for REST API Dead Letter Queue Data Loss
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Solution Overview
Problem
Conventional dead letter queues in RESTful APIs are prone to data loss due to system failures, especially in cloud-based environments, where messages may be corrupted or lost, failing to ensure a 100% response rate required by regulatory and system compliance.
Innovation Solution
A new system component creates a representative system file upon detecting a message failure, storing it in dedicated memory to prevent data loss, allowing for independent processing and resolution of failures without relying on conventional dead letter queues, ensuring all failures are responded to and processed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional dead letter queues are used in RESTful APIs, then no additional software or libraries are needed, but data loss occurs due to system failures in cloud-based environments
Solution Approach 1:
The patent creates a representative system file that copies essential information from the failed REST call (endpoint, method, headers, body, error details) and stores it in dedicated memory. This copy serves as a persistent record that survives system failures, eliminating data loss while maintaining RESTful architecture constraints.
Solution Approach 2:
The system performs preliminary action by creating and storing the representative system file immediately when a failure is detected, before any potential system failure can occur. This ensures data is preserved in dedicated memory rather than relying on transient dead letter queue storage.
2Reliability
If messages are stored in transitory dead letter queues, then storage requirements are reduced, but messages may be lost due to system failures
Solution Approach 1:
Instead of storing complete messages in dedicated memory, the system creates a representative system file that contains only essential information (endpoint, method, headers, body, error details). This copy approach preserves message persistence while minimizing memory allocation requirements.
Solution Approach 2:
The system extracts only the critical elements needed for failure analysis and persistence (endpoint, method, headers, body, error details) from the complete REST call, storing only these extracted components in the representative system file in dedicated memory.
3Reliability
If conventional dead letter queues are used, then implementation is simple, but 100% response rate compliance cannot be ensured
Solution Approach 1:
The system implements feedback by continuously monitoring for failures, creating representative system files, storing them in dedicated memory, and processing them until resolution. This closed-loop approach ensures 100% response rate compliance by guaranteeing that every failure is captured and addressed.
Solution Approach 2:
The system performs self-service by automatically detecting failures, creating representative system files, storing them in dedicated memory, and processing them without external intervention. This automated failure processing ensures compliance while maintaining operational simplicity.
Data Source
AI summary
Systems and methods are provided for processing of messages subject to dead letter queues in representational state transfer (“REST”) architectures to prevent data loss in cloud-based environments. For example, as opposed to conventional RESTful application programming interface (“API”) approaches to handling message failures, the systems and methods provide a new system component to handle these failures. Specifically, instead of relying on a conventional dead letter queue (e.g., requiring a system to read the queue via lambda functions), the systems and methods create a representative system file based on any REST call in which a failure is detected.