Source URL: https://blog.sequinstream.com/at-most-once-at-least-once-and-exactly-once-delivery/
Source: Hacker News
Title: No such thing as exactly-once delivery
Feedly Summary: Comments
AI Summary and Description: Yes
Summary: The text discusses messaging systems and their delivery guarantees, distinguishing between concepts like at-most-once, at-least-once, and exactly-once processing. It provides insights on how to design systems to handle messaging issues, particularly focusing on the two-phase commit problem, redelivery scenarios, and system design strategies for ensuring reliability in message processing.
Detailed Description: The text offers a technical examination of message delivery systems, focusing on several key concepts in information systems and messaging architecture:
* **Delivery Types and Guarantees**:
– **At-Most-Once Delivery**: Messages may be lost if a subscriber isn’t reachable or due to network issues. Example given is Postgres’ LISTEN/NOTIFY.
– **At-Least-Once Delivery**: Guarantees that messages are delivered but may lead to duplicates due to the possibility of redelivery.
– **Exactly-Once Processing**: Refers to a system’s ability to ensure that messages are processed exactly once, which involves both delivery assurance and acknowledgment from the receiver.
* **Two-Phase Commit Problem**: A critical issue in distributed systems where a system must confirm a message’s delivery both to the database and the receiver. Challenges arise if either acknowledgment fails post-commit or the connection drops.
* **Practical Solutions and Design Strategies**:
– Accepting potential issues from redeliveries versus making systems idempotent to handle duplicates efficiently.
– Breaking messages into smaller units of work to minimize the impact of failures during processing.
– Configuring visibility timeouts in systems like SQS and Sequin to allow for timely message redelivery in the event of a worker crash.
* **Recommendations for System Design**:
– Choose the delivery type based on business needs (e.g., banks requiring idempotence for transactions).
– Establish clear processing workflows and monitor message acknowledgments to prevent inconsistencies.
This detailed examination is crucial for professionals in AI, cloud, and infrastructure security as it builds a solid understanding of message processing systems, their vulnerabilities, and design considerations for creating robust, fault-tolerant applications in distributed environments. The insights provided underscore the importance of addressing edge cases and designing systems capable of handling potential reprocessing complications efficiently.