Poisoned Message Detection via Consumer Validation
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Solution Overview
Problem
Current messaging systems face challenges in identifying and handling poison messages, especially when multiple producers send data, as determining the source of a poison message is difficult, and consumers may hang or fail due to design issues rather than the message itself.
Innovation Solution
A computer system that receives messages from producers, monitors consumers for adverse conditions, and sends the message to additional consumers to verify if it's a poison message by marking it with a unique identifier, allowing for identification of the producer and taking appropriate actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a message is sent to a consumer in a messaging system, then the consumer can process the message and produce output, but the consumer may hang or crash due to poison messages causing service disruption
Solution Approach 1:
The system performs preliminary validation by sending the suspected poison message to a set of test consumers before allowing it to reach the main consumer. This advance testing identifies problematic messages before they can cause service disruption, preventing the consumer from hanging or crashing while maintaining the ability to process valid messages efficiently
Solution Approach 2:
The system introduces an intermediary validation layer between the message queue and the consumer. This intermediary component acts as a buffer that intercepts messages, performs stability testing on a subset of consumers, and only allows messages that pass the validation to reach the main consumer, thus isolating the consumer from poison messages while preserving message flow for valid inputs
2Measurement precision
If schema validation is used to identify poison messages, then messages can be validated against known formats, but prior knowledge about messages must be present which may not be available in all messaging systems
Solution Approach 1:
Instead of requiring prior schema knowledge, the system performs preliminary empirical validation by actually attempting to process the message through test consumers. This runtime validation approach adapts to any message type without requiring predefined schemas, making the system versatile while maintaining accurate detection of poison messages through real-world processing attempts
Solution Approach 2:
The system uses the consumers themselves to validate messages rather than relying on external schema validation. The consumers perform self-testing by attempting to process messages and reporting back whether they succeeded or caused adverse conditions. This self-service validation mechanism eliminates the need for prior knowledge about message formats while maintaining high detection accuracy through actual processing attempts
3Reliability
If a consumer hangs or crashes due to a poison message, then the message is identified as problematic, but determining the source of the poison message is difficult when multiple producers send data
Solution Approach 1:
The system segments the validation process by testing messages with individual consumers in isolation rather than with all consumers simultaneously. Each consumer processes messages independently and reports results separately, allowing the system to trace which specific consumer failed on which specific message. This segmentation preserves producer identification information by maintaining clear one-to-one correspondence between messages and consumer responses
Solution Approach 2:
The system implements a feedback mechanism where each consumer reports back to the messaging system whether it successfully processed a message or encountered an adverse condition. This structured feedback loop preserves information about which consumer failed and on which message, enabling the system to trace the failure back to the originating producer while maintaining reliable poison message detection
Data Source
AI summary
A method, apparatus, system, and computer program product for processing messages. A message is received from a producer by a computer system. The message is sent to a consumer by the computer system. The message is sent to a set of consumers in addition to the consumer by the computer system in response to an adverse condition being present for the consumer after sending the message the consumer. A set of actions is performed in response to the adverse condition being present in the set of consumers receiving the message.