Unmasking the Silent Failures of Distributed Transactions: Detecting In-Doubt States and Validating Compensations with Python

说明与用途

该方案通过使用 Python、orjson 和 Pydantic 解析日志，检测分布式事务中的“In‑Doubt”状态并生成不一致报告。

问题

Silent data inconsistency in microservices caused by network timeouts leaves distributed state in an "In-Doubt" state without explicit errors.

结果

The tool processes millions of log lines, normalizes timestamps, validates schema, and flags transactions stuck in an indeterminate state, enabling operators to investigate and remediate silent failures.

工作流

• Collect log entries from all services
• Parse each log line with orjson for speed
• Validate ISO 8601 timestamps via Pydantic field validator
• Group entries by correlation_id
• Detect state mismatches (COMMITTED vs IN_DOUBT/STARTED)
• Generate DiscrepancyReport JSON
• Output report for manual review or alerting

证据

Network timeouts cause transactions to enter an "In-Doubt" state across service boundaries

来源

The following tool processes multi-service log entries, groups states by transaction identifier (correlation_id), validates ISO 8601 timestamps, and identifies transactions trapped in incomplete or indeterminate states.

来源