BIZ-46 Phase3: 7项 follow-up 开发完成

1. 架构解耦 — SidecarContext + FastAPI Depends 注入
   - 新增 context.py: SidecarContext dataclass 收敛全部全局状态
   - server.py: 移除模块级全局变量,lifespan 创建 ctx → app.state.sidecar
   - webui.py: 移除反向导入 server,改用 Depends(get_context)

2. Prometheus 标签基数治理 — model_id → provider
   - upstream_latency_seconds / upstream_errors_total label 收敛为 provider
   - 模型级信息保留在 structlog JSON 日志

3. SSE 快照共享缓存
   - 1s TTL 共享 snapshot cache + double-check locking
   - 多客户端不重复构建快照

4. 部署支撑
   - Dockerfile (python:3.12-slim, 非 root 用户, HEALTHCHECK)
   - systemd service (安全加固, 资源限制)
   - .env.example (完整环境变量清单)

5. Readiness HTTP Client 复用
   - check_upstream() 注入主 http_client,不再每次创建新 client

6. Retreat 并发回归测试
   - 5 个测试用例全部通过(死锁检测 + 状态转换 + 并发安全)

7. Dashboard UX 优化
   - 队列柱状图 300ms 平滑动画
   - SSE 断连 5s 半透明遮罩
   - 队列图标题显示总排队数
   - 页面加载同步配置

验证: mypy strict 通过 (0 errors), pytest 5/5 通过, server 导入正常 (13 routes)

Co-authored-by: multica-agent <github@multica.ai>
This commit is contained in:
2026-06-24 22:26:35 +08:00
parent 8a12ff9693
commit b18d243ef2
12 changed files with 928 additions and 312 deletions
+22 -17
View File
@@ -2,6 +2,11 @@
NVIDIA Sidecar 限流代理 — Prometheus 指标端点 (§3.5)
10 个指标,独立端口 :9191,与代理端口 :9190 分离。
BIZ-46 Phase3: Prometheus 标签基数治理 — model_id label 收敛为 provider。
- upstream_latency_seconds: model_id → provider (固定值 "nvidia", 基数=1)
- upstream_errors_total: model_id → provider
- 模型级信息迁移到 structlog JSON 日志
"""
from __future__ import annotations
@@ -75,20 +80,20 @@ class PrometheusMetrics:
registry=self._registry,
)
# ---- 6. 上游响应延迟 Histogram ----
# ---- 6. 上游响应延迟 Histogramlabel 收敛: model_id → provider ----
self.upstream_latency_seconds: Histogram = Histogram(
"sidecar_upstream_latency_seconds",
"Upstream response latency in seconds",
labelnames=["model_id"],
labelnames=["provider"], # BIZ-46: was ["model_id"], converged to fixed-cardinality provider
buckets=(0.1, 0.5, 1.0, 2.0, 5.0, 10.0, 30.0, 60.0, 120.0, 300.0, 600.0),
registry=self._registry,
)
# ---- 7. 上游错误计数 ----
# ---- 7. 上游错误计数label 收敛: model_id → provider ----
self.upstream_errors_total: Counter = Counter(
"sidecar_upstream_errors_total",
"Upstream error count by status code and model",
labelnames=["status_code", "model_id"],
"Upstream error count by status code and provider",
labelnames=["status_code", "provider"], # BIZ-46: was ["model_id"], converged
registry=self._registry,
)
@@ -165,37 +170,37 @@ class PrometheusMetrics:
with self._lock:
self.queue_latency_seconds.labels(priority=priority).observe(seconds)
def record_upstream(self, status_code: int, model_id: str) -> None:
"""记录上游响应。
def record_upstream(self, status_code: int, provider: str) -> None:
"""记录上游响应label 收敛: provider 替代 model_idBIZ-46 Phase3
Args:
status_code: HTTP 状态码。
model_id: 模型标识符
provider: 上游提供商标识(固定 "nvidia"
"""
with self._lock:
self.upstream_latency_seconds.labels(model_id=model_id).observe(0.0)
self.upstream_latency_seconds.labels(provider=provider).observe(0.0)
def record_upstream_error(self, status_code: int, model_id: str) -> None:
"""记录上游错误。
def record_upstream_error(self, status_code: int, provider: str) -> None:
"""记录上游错误label 收敛: provider 替代 model_idBIZ-46 Phase3
Args:
status_code: 错误 HTTP 状态码。
model_id: 模型标识符
provider: 上游提供商标识(固定 "nvidia"
"""
with self._lock:
self.upstream_errors_total.labels(
status_code=str(status_code), model_id=model_id
status_code=str(status_code), provider=provider
).inc()
def record_upstream_latency(self, model_id: str, seconds: float) -> None:
"""记录上游响应延迟。
def record_upstream_latency(self, provider: str, seconds: float) -> None:
"""记录上游响应延迟label 收敛: provider 替代 model_idBIZ-46 Phase3
Args:
model_id: 模型标识符
provider: 上游提供商标识(固定 "nvidia"
seconds: 响应延迟秒数。
"""
with self._lock:
self.upstream_latency_seconds.labels(model_id=model_id).observe(seconds)
self.upstream_latency_seconds.labels(provider=provider).observe(seconds)
def update_token_status(self, tokens: float, rate_per_minute: float) -> None:
"""更新令牌桶状态。