┌─────────────────────────────────────────────────────────────┐
│                    业务场景层（Test Cases）                    │
│  入会流程 | 共享屏幕 | 录制回放 | 断网重连 | 多人混流 | 权限控制  │
├─────────────────────────────────────────────────────────────┤
│                    业务动作层（Page Object / Action）          │
│  登录入会 | 设备选择 | 媒体协商 | 布局切换 | 统计上报 | 退出清理  │
├─────────────────────────────────────────────────────────────┤
│                    协议与媒体能力层（Core Library）            │
│  WebRTC Signaling | SDP 解析 | ICE Candidate | RTP/RTCP 统计  │
│  音视频采集注入 | 码率控制 | 丢包模拟 | 质量评价（VMAF/MOS）   │
├─────────────────────────────────────────────────────────────┤
│                    基础设施层（Infrastructure）                │
│  设备农场管理 | 网络模拟器 | 容器编排 | 监控告警 | 报告归档     │
└─────────────────────────────────────────────────────────────┘
                    ▲                    ▲
            ┌───────┴───────┐      ┌─────┴─────┐
            │  测试数据中台  │      │  环境配置中台 │
            │  (账号/房间/媒体)│      │  (网络/设备/版本)│
            └───────────────┘      └───────────┘

# 典型 Pod 模板：单实例包含 1 个 Chrome Headless + 1 个虚拟音频设备
apiVersion: v1
kind: Pod
metadata:
  name: conf-test-agent-{{.Index}}
spec:
  containers:
  - name: chrome
    image: registry.internal/conf-test-chrome:v1.2.3
    env:
    - NAME: DISPLAY
      VALUE: ":99"
    - NAME: PULSE_SERVER
      VALUE: "unix:/run/pulse/native"
    resources:
      limits:
        cpu: "2000m"
        memory: "4Gi"
        nvidia.com/gpu: 1  # 可选：硬件编解码加速
  - name: pulseaudio
    image: registry.internal/pulseaudio-virtual:v1.0
    volumeMounts:
    - name: pulse-socket
      mountPath: /run/pulse
  volumes:
  - name: pulse-socket
    emptyDir: {}

# 典型弱网模板：模拟 4G/公共 Wi-Fi/跨国专线
tc qdisc add dev eth0 root netem 
  loss 2% 
  delay 80ms 20ms distribution normal 
  duplicate 0.5% 
  corrupt 0.1% 
  rate 2mbit

@network_profile("cross_border_4g")  # 预定义：丢包 3%、延迟 150ms、抖动 40ms
@retry_on_flaky(max_attempts=2)
def test_cross_border_meeting_quality():
    ...

quality_gate:
  stage: gate
  script:
    - |
      python scripts/check_quality_gate.py 
        --report allure-results/ 
        --thresholds '{
          "join_success_rate": 0.99,
          "avg_join_time_ms": 3000,
          "vmaf_p50": 85,
          "audio_mos_p50": 4.0,
          "reconnect_success_rate": 0.95
        }'
  allow_failure: false  # 失败即阻断合并/发布

# tests/factories/meeting_factory.py
class MeetingFactory:
    @staticmethod
    def create_standard_meeting(owner: Account, profile: NetworkProfile) -> MeetingContext:
        room_id = f"auto_{uuid.uuid4().hex[:8]}"
        # 1. 通过 OpenAPI 创建房间，携带网络画像标签
        room = MeetingOpenAPI.create_room(
            owner.token, 
            room_id, 
            template="standard_1080p",
            network_tags=profile.tags  # 弱网标签透传给媒体节点调度
        )
        # 2. 预置媒体文件到媒体节点缓存（加速首帧渲染）
        MediaNodeAPI.warmup_cache(room.media_node_id, profile.test_clip_id)
        # 3. 返回上下文对象，自带清理器
        return MeetingContext(room, owner, cleanup=lambda: MeetingOpenAPI.delete_room(owner.token, room_id))

    @staticmethod
    def create_breakout_rooms(parent: MeetingContext, count: int) -> List[MeetingContext]:
        # 批量创建分组讨论室，自动关联父会议生命周期
        ...

# compat_matrix_policy.yml
platforms:
  - name: "Windows Desktop (Electron)"
    weight: 1.0      # 用户量最大
    capabilities: [h264, vp8, vp9, av1, simulcast, svc]
    ci_agent_label: "win10-gpu"
  - name: "macOS Desktop (Native)"
    weight: 0.9
    capabilities: [h264, vp8, vp9, hw_h264_enc]  # 硬编能力差异
    ci_agent_label: "macos-m1"
  - name: "iOS Safari (WebRTC)"
    weight: 0.85
    constraints: [no_vp9_enc, no_simulcast_recv, audio_context_policy]
    ci_agent_label: "ios-device-farm"  # 必须真机
  - name: "Android Chrome (M80+)"
    weight: 0.8
    capabilities: [vp9, av1_dec]
    ci_agent_label: "android-emulator-farm"

# 变更影响分析：仅变更「屏幕共享编码器」时，自动筛选支持 simulcast/hw_enc 的平台
change_impact_rules:
  - files: ["src/media/encoder/**", "src/media/screen/**"]
    required_capabilities: ["simulcast", "hw_h264_enc", "vp9"]
    min_weight: 0.7

# tests/security/test_local_ai_privacy.py
@pytest.mark.privacy
def test_virtual_background_no_upload(mitmproxy_capture, meeting_session):
    """
    验证虚拟背景推理过程无网络请求
    """
    with mitmproxy_capture.filter(domain="api.company.com") as capture:
        meeting_session.enable_virtual_background("blur")
        wait_for_effect_ready()
        meeting_session.disable_virtual_background()
    
    # 断言：除信令/媒体必要域名外，无新增 AI 推理相关请求
    ai_related_domains = ["ai.bgremoval.com", "ml.inference.cloud"]
    assert not any(d in capture.request_hosts for d in ai_related_domains), 
        "虚拟背景检测到疑似上传推理数据的网络请求"

// 信令网关中间件示例
func TestTraceMiddleware() gin.HandlerFunc {
    return func(c *gin.Context) {
        runID := c.GetHeader("x-test-run-id")
        if runID != "" {
            // 注入到 Context，下游 gRPC/HTTP 自动透传
            ctx := metadata.AppendToOutgoingContext(c.Request.Context(),
                "x-test-run-id", runID,
                "x-test-scenario", c.GetHeader("x-test-scenario"),
            )
            c.Request = c.Request.WithContext(ctx)
            // 响应头回传，便于客户端对账
            c.Header("x-test-trace-id", trace.SpanFromContext(ctx).SpanContext().TraceID().String())
        }
        c.Next()
    }
}

# scripts/capacity_estimator.py
def estimate_capacity(metrics: LoadTestMetrics, sla: SLAConfig) -> CapacityReport:
    # 1. 识别瓶颈资源：CPU / 内存 / 网络带宽 / 文件描述符 / GPU 显存
    bottleneck = identify_bottleneck(metrics.node_metrics)
    
    # 2. 基于 Little's Law 与安全冗余系数 (1.3~1.5) 计算单节点极限并发
    max_concurrency_per_node = bottleneck.safe_limit * sla.redundancy_factor
    
    # 3. 结合当前集群节点数、自动扩缩容策略，推算集群支撑上限
    cluster_capacity = max_concurrency_per_node * cluster.current_nodes * (1 - sla.headroom_ratio)
    
    # 4. 输出扩容建议：若预估峰值 > 容量 * 0.7，触发扩容工单
    return CapacityReport(
        bottleneck=bottleneck,
        single_node_limit=max_concurrency_per_node,
        cluster_limit=cluster_capacity,
        scale_recommendation=generate_scale_advice(cluster_capacity, sla.peak_forecast)
    )

graph LR
    A[CI 失败 / 线上工单] --> B{自动/手动触发}
    B --> C[下载录制包: PCAP + RRWeb + Media + TraceID]
    C --> D[启动复现环境: K8s Job + 网络命名空间]
    D --> E[注入网络流量: tcpreplay --mbps=10 --loop=1]
    E --> F[回放客户端行为: RRWeb Player / Playwright Script]
    F --> G[对比媒体指标: VMAF/MOS/首帧时延]
    G --> H{指标回归?}
    H -- Yes --> I[定位代码变更: Git Bisect + Trace 火焰图]
    H -- No --> J[标记为环境抖动/数据问题]
    I --> K[生成复现报告 & 关联 Commit]

-- 月度测试成本分析视图
SELECT 
    date_trunc('month', pipeline_start) AS month,
    SUM(cloud_cost_usd) AS total_cost,
    COUNT(DISTINCT CASE WHEN status='failed' THEN defect_id END) AS defects_found,
    SUM(cloud_cost_usd) / NULLIF(COUNT(DISTINCT CASE WHEN status='failed' THEN defect_id END), 0) AS cost_per_defect,
    -- 置信度：核心流程通过率 * 覆盖平台权重和
    AVG(core_pass_rate * platform_weight_sum) AS confidence_score,
    SUM(cloud_cost_usd) / NULLIF(AVG(core_pass_rate * platform_weight_sum), 0) AS cost_per_confidence
FROM ci_pipeline_runs
JOIN cloud_billing ON ci_pipeline_runs.run_id = cloud_billing.run_id
GROUP BY 1
ORDER BY 1 DESC;

# 开发本地一键跑核心入会冒烟（含弱网模拟）
npx @company/conf-test-kit run smoke 
  --env local 
  --network-profile "weak_wifi" 
  --headless 
  --reporter allure