Real-time Traffic Comparison Platform for Enhancing Code Quality
The proposed real‑time traffic comparison platform samples production traffic, replays mock requests, and checks database records, MQ messages, API parameters, and responses against a reference version, enabling near‑instant detection of regressions during refactoring, reducing test effort and release cycles while requiring instrumentation and configuration but no dedicated comparison database.
Background
During code refactoring and iterative development, multiple test rounds are required before release. Complex business scenarios cause long test cycles, incomplete test coverage, delayed issue detection, reduced release frequency, and heavy manual code review effort.
Comparison with Existing Traffic Replay Platforms
Typical replay tools record traffic and replay it in a test environment, which only frees regression resources but cannot expose issues before testing begins. Our goal is a real‑time comparison that reveals problems as soon as production traffic is generated, even without test involvement.
Proposed Traffic Comparison Scheme
We compare four dimensions: persisted database records, MQ messages, API request parameters, and response data. By sampling roughly 50% of production traffic, we achieve near‑100% consistency on these dimensions, ensuring that new releases do not affect existing business.
The workflow is:
Production services emit data (ES logs, MQ messages) for each request.
A comparison tool consumes the MQ message, fetches the corresponding production order, and creates a mock request for the comparison service.
The comparison service processes the mock request, compares results, and writes consistency metrics back to ES.
Mock data are stored in Redis; the comparison service never accesses the real database or downstream systems.
Configuration & Data Comparison
Comparison rules are managed in a configuration center, allowing field‑level ignore settings (e.g., timestamps, order IDs) for both API and MQ payloads.
Result Consistency Analysis
Consistency rates and mismatch reasons are queried from ES using the recorded action types.
Pros
Early detection of issues during code refactoring or version iteration.
Reduces regression testing effort.
Improves overall development quality and release frequency.
No dedicated comparison database required, lowering cost.
Flexible deployment of comparison services.
Configurable comparison content.
Cons
Requires instrumentation and MQ messages, adding some intrusion.
Incremental features lacking a reference baseline still rely on unit tests and code review.
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