Messaging Overflow Service for Latency Reduction
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Solution Overview
Problem
Messaging systems face latency issues during heavy loads, leading to unprocessed messages in the message queue, which can result in outdated query results due to the slow and expensive process of scaling the data store to handle increased capacity.
Innovation Solution
A messaging overflow service is introduced that dynamically launches to consume unprocessed messages from the message queue, processing them and storing results in a cache, allowing query processes to retrieve updated values by checking both the data store and cache, thus alleviating the load on the data store and message queue.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the data store capacity is increased to handle heavy messaging load, then the messaging service can process more messages, but the scaling process is slow and expensive
Solution Approach 1:
The system segments the messaging workload by introducing a separate overflow service that handles excess messages independently from the main data store. This segmentation allows the overflow service to process messages in parallel without requiring scaling of the primary data store infrastructure.
Solution Approach 2:
The overflow service acts as an intermediary component between the message queue and the data store. It receives overflow messages, processes them independently, and stores results in a cache, thereby mediating the load between the queue and the primary data store without requiring data store scaling.
2Productivity
If the data store capacity is increased to handle heavy messaging load, then the messaging service can process more messages, but scaling is expensive
Solution Approach 1:
The overflow service uses a cache with temporary storage that is cheaper than persistent data store infrastructure. This cache provides short-term storage for processed messages, reducing the need for expensive data store scaling while maintaining message processing capability.
Solution Approach 2:
The overflow service serves as a cost-effective intermediary that handles overflow traffic using less expensive caching infrastructure rather than requiring proportional scaling of the expensive primary data store capacity.
3Productivity
If message handlers process messages from the message queue, then messages are handled, but during heavy load latency increases causing outdated query results
Solution Approach 1:
The system segments the message processing workload by routing overflow messages to a dedicated overflow service, separating them from the main message handler workflow. This segmentation prevents latency in the primary processing path while maintaining overall throughput.
Solution Approach 2:
The overflow service performs preliminary processing of overflow messages independently, so when queries need results, the data is already processed and available in the cache, eliminating waiting time for query operations.
4Speed
If a cache is introduced to store processed values, then query speed improves, but system complexity increases
Solution Approach 1:
The overflow service's cache serves multiple functions: it stores processed overflow message results, provides fast query responses, and reduces load on the primary data store. This multi-functionality justifies the added complexity by delivering multiple benefits from a single component.
Data Source
AI summary
A technology is provided for reducing latency in a messaging system. Unprocessed messages in a message queue are consumed via a messaging overflow service launched in response to an alarm triggered by a monitoring service that indicates the message queue has reached a predetermined threshold. The unprocessed messages are processed via the messaging overflow service to generate a processed data store values. The processed data store values are stored in a cache associated with the messaging overflow service.