feat: 前端指标体系增强 — Dashboard/Metrics API、2×4 统计区、趋势图面积+异常标记、连续状态列

- 新增 GET /api/dashboard 合并原 summary+targets 首屏接口
- 新增 GET /api/targets/:id/metrics 合并原 stats+trend 概览接口
- 后端指标纯函数：可用率、百分位、故障段分析、连续状态、UTC 小时分桶
- ProbeStore 窗口取数方法替代全量历史查询
- SummaryCards 扩展为 4 卡片（新增异常事件数）+ 数据新鲜度展示
- 表格新增「连续」列（Tag 渲染 capped 状态）
- OverviewTab 重构为 2×4 Statistic 多维度布局
- TrendChart 改为延迟范围面积图 + 红色异常标记点
- 删除旧路由（summary/targets/trend）和 computeTrendStats
- 同步 delta specs 到主 specs 并归档变更

tests/server/metrics.test.ts

@@ -0,0 +1,126 @@
+import { describe, expect, test } from "bun:test";
+
+import {
+  analyzeIncidentSequence,
+  buildHourlyTrend,
+  calculateAvailability,
+  calculateCurrentStreak,
+  calculatePercentile,
+  type MetricCheckpoint,
+} from "../../src/server/metrics";
+
+describe("后端指标计算", () => {
+  test("可用率无数据返回 0，并保留两位精度", () => {
+    expect(calculateAvailability(0, 0)).toBe(0);
+    expect(calculateAvailability(2, 3)).toBe(66.67);
+  });
+
+  test("百分位按 ceil(count * N / 100) - 1 取值", () => {
+    const durations = Array.from({ length: 100 }, (_, index) => index + 1);
+
+    expect(calculatePercentile([], 95)).toBeNull();
+    expect(calculatePercentile([40, 10, 30, 20], 95)).toBe(40);
+    expect(calculatePercentile(durations, 95)).toBe(95);
+    expect(calculatePercentile(durations, 99)).toBe(99);
+  });
+
+  test("无检查数据时故障分析返回空口径", () => {
+    const result = analyzeIncidentSequence([], "2025-01-01T00:00:00.000Z", "2025-01-01T01:00:00.000Z");
+
+    expect(result).toEqual({ incidentCount: 0, longestOutage: null, mttr: null });
+    expect(calculateCurrentStreak([])).toBeNull();
+  });
+
+  test("窗口起始即故障计入 incident 和最长故障，但不计入 MTTR", () => {
+    const result = analyzeIncidentSequence(
+      [
+        checkpoint("2025-01-01T00:05:00.000Z", false),
+        checkpoint("2025-01-01T00:10:00.000Z", false),
+        checkpoint("2025-01-01T00:20:00.000Z", true),
+      ],
+      "2025-01-01T00:00:00.000Z",
+      "2025-01-01T01:00:00.000Z",
+    );
+
+    expect(result.incidentCount).toBe(1);
+    expect(result.longestOutage).toBe(20 * 60 * 1000);
+    expect(result.mttr).toBeNull();
+  });
+
+  test("未恢复故障计算到窗口结束且不计入 MTTR", () => {
+    const result = analyzeIncidentSequence(
+      [checkpoint("2025-01-01T00:05:00.000Z", true), checkpoint("2025-01-01T00:20:00.000Z", false)],
+      "2025-01-01T00:00:00.000Z",
+      "2025-01-01T01:00:00.000Z",
+    );
+
+    expect(result.incidentCount).toBe(1);
+    expect(result.longestOutage).toBe(40 * 60 * 1000);
+    expect(result.mttr).toBeNull();
+  });
+
+  test("连续异常只计一次 incident，恢复后纳入 MTTR", () => {
+    const result = analyzeIncidentSequence(
+      [
+        checkpoint("2025-01-01T00:00:00.000Z", true),
+        checkpoint("2025-01-01T00:05:00.000Z", false),
+        checkpoint("2025-01-01T00:10:00.000Z", false),
+        checkpoint("2025-01-01T00:20:00.000Z", true),
+      ],
+      "2025-01-01T00:00:00.000Z",
+      "2025-01-01T01:00:00.000Z",
+    );
+
+    expect(result.incidentCount).toBe(1);
+    expect(result.longestOutage).toBe(15 * 60 * 1000);
+    expect(result.mttr).toBe(15 * 60 * 1000);
+  });
+
+  test("连续状态支持 capped 标记", () => {
+    expect(
+      calculateCurrentStreak(
+        [
+          checkpoint("2025-01-01T00:00:00.000Z", true),
+          checkpoint("2025-01-01T00:01:00.000Z", false),
+          checkpoint("2025-01-01T00:02:00.000Z", false),
+        ],
+        2,
+      ),
+    ).toEqual({ capped: true, count: 2, up: false });
+  });
+
+  test("UTC 小时趋势分桶返回 up/down 和延迟范围", () => {
+    const trend = buildHourlyTrend([
+      checkpoint("2025-01-01T00:10:00.000Z", true, 100),
+      checkpoint("2025-01-01T00:40:00.000Z", false, null),
+      checkpoint("2025-01-01T01:05:00.000Z", true, 300),
+    ]);
+
+    expect(trend).toEqual([
+      {
+        availability: 50,
+        avgDurationMs: 100,
+        bucketStart: "2025-01-01T00:00:00.000Z",
+        downChecks: 1,
+        maxDurationMs: 100,
+        minDurationMs: 100,
+        totalChecks: 2,
+        upChecks: 1,
+      },
+      {
+        availability: 100,
+        avgDurationMs: 300,
+        bucketStart: "2025-01-01T01:00:00.000Z",
+        downChecks: 0,
+        maxDurationMs: 300,
+        minDurationMs: 300,
+        totalChecks: 1,
+        upChecks: 1,
+      },
+    ]);
+  });
+});
+
+function checkpoint(timestamp: string, matched: boolean, durationMs: null | number = null): MetricCheckpoint {
+  return { durationMs, matched, timestamp };
+}