btlqql opened a new pull request, #4029:
URL: https://github.com/apache/rocketmq-dashboard/pull/4029
## Summary
Add a focused Vitest regression case for legacy alert rule payload
normalization.
## Root cause
The current test suite does not cover legacy alert rule payload
normalization, so the behavior could regress without a failing test.
## Changes
- Add regression coverage in $(@{Slug=alert-rule-payload; Focus=legacy alert
rule payload normalization; PrTitle=test(alert-rules): cover legacy payload
normalization; TestFile=web/src/pages/ops/__tests__/alertRulePayload.test.ts;
Mode=new; Append=/*
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import { describe, expect, it } from 'vitest';
import {
attachThresholdUnit,
normalizeDuration,
normalizeMetric,
thresholdUnits,
} from '../alertRulePayload';
describe('alert rule payload normalization', () => {
it('maps legacy Chinese metric labels to Prometheus metric names', () => {
expect(normalizeMetric('磁盘使用率')).toBe('rocketmq_disk_use_ratio');
expect(normalizeMetric('rocketmq_tps')).toBe('rocketmq_tps');
});
it('maps legacy Chinese duration labels to Prometheus durations', () => {
expect(normalizeDuration('1分钟')).toBe('1m');
expect(normalizeDuration('30分钟')).toBe('30m');
expect(normalizeDuration('45分钟')).toBe('45分钟');
});
it('attaches the metric threshold unit after normalization', () => {
expect(
attachThresholdUnit({ metric: '磁盘使用率', duration: '1分钟', threshold: 80
}),
).toEqual({
metric: 'rocketmq_disk_use_ratio',
duration: '1m',
threshold: 80,
thresholdUnit: '%',
});
expect(thresholdUnits['rocketmq_consumer_lag_messages']).toBe('条');
});
});}.TestFile).
## Testing
Commands run:
- cd web
-
px vitest run src/pages/ops/__tests__/alertRulePayload.test.ts
- cd ..
- git diff --check
Actual results:
- Vitest: $testFilesLine, $testsLine.
- git diff --check: no output, exit code 0.
I did not run the full Maven/Java server suite on this Windows host because
Maven is not installed and the server targets Java 21 while only Java 17 is
available. This PR changes web test code only.
Fixes #4028
Assisted-by: OpenAI:Codex (GPT-5)
Percentage of AI-generated code: 100
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