Priority Queue Architecture for SLA-Driven Transaction Processing
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Solution Overview
Problem
Conventional transaction processing systems use a single, monolithic messaging bus that processes transactions sequentially, leading to delays in handling time-sensitive transactions and affecting service level agreements and overall system efficiency.
Innovation Solution
A transaction exchange platform utilizing a streaming data platform (SDP) and microservices, with configurable priority queues and consumption models, ensures timely processing of transactions by placing them in associated priority queues and allowing microservices to interact based on configured workflows.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single, monolithic messaging bus is used to process transactions sequentially, then system simplicity is maintained, but processing speed and time sensitivity handling deteriorate
Solution Approach 1:
The patent segments the monolithic messaging bus into multiple independent priority queues (e.g., high-priority queue, low-priority queue, real-time queue). Each queue operates independently to handle specific transaction types or urgency levels, enabling parallel processing while maintaining overall system simplicity through modular architecture.
Solution Approach 2:
The system dynamically assigns transactions to different priority queues based on their characteristics (e.g., transaction type, urgency, value). The messaging bus adapts its behavior by routing transactions to appropriate queues rather than processing them sequentially, enabling flexible and dynamic processing speeds.
2Ease of operation
If all transactions are queued on a first-in, first-out basis, then queue management simplicity is maintained, but time-sensitive transaction handling deteriorates
Solution Approach 1:
Different quality levels of service are provided to different transaction groups. High-priority and real-time queues implement stricter processing guarantees for time-sensitive transactions, while standard queues maintain simpler FIFO behavior for less urgent transactions. Each queue has customized processing characteristics matched to its transaction type.
Solution Approach 2:
The system changes the queueing parameter from uniform FIFO to priority-based ordering. Transactions are assigned priority levels (e.g., high, medium, low) or real-time flags that alter their position in the queue, ensuring time-sensitive transactions are processed before less urgent ones while maintaining manageable complexity through configured priority rules.
3Device complexity
If a monolithic messaging bus is used, then system structure is simple, but service level agreement compliance deteriorates
Solution Approach 1:
The messaging bus is segmented into dedicated queues that can be independently configured to meet specific service level agreements. Each queue can have customized processing guarantees, monitoring, and resource allocation to ensure compliance with SLAs for different transaction types without affecting other parts of the system.
Solution Approach 2:
The system implements feedback mechanisms that monitor transaction processing metrics (e.g., processing time, success rate) for each priority queue and adjust resource allocation or routing decisions accordingly. This enables continuous improvement of SLA compliance while maintaining a relatively simple overall system structure.
Data Source
AI summary
Aspects described herein may relate to a transaction exchange platform using a streaming data platform (SDP) and microservices to process transactions according to review and approval workflows. The transaction exchange platform may comprise a plurality of configurable priority queues. Each of the microservices may retrieve data from each of the plurality queues in accordance with a consumption model equitable and prioritized processing. The architecture described herein provides a scalable, resilient, and efficient solution for modern event-driven transaction processing environments to handle the processing of data in accordance with time constraints and/or service-level agreements.