BIZ-42: Phase2 可观测性+WebUI+避退模式 — metrics/health/webui/dashboard/adaptive

新增文件:
- metrics.py: Prometheus 指标端点 (:9191), 10+3 个指标
- health.py: /health (liveness) + /health/ready (readiness)
- webui.py: WebUI 后端 API (SSE 实时推送 + 配置热重载)
- static/dashboard.html: 仪表盘前端 (Chart.js, 令牌桶仪表+队列柱状图+吞吐折线图)

更新文件:
- rate_limiter.py: 增加 AdaptiveTokenBucket 避退模式 (ADR-009)
  状态机 NORMAL→RETREAT→RECOVER, 429 率滑动窗口监控
- server.py: structlog 结构化日志 + 避退反馈回路
  挂载 metrics_server (:9191) + health/ready + webui + /status
- pyproject.toml: 增加 prometheus-client, pydantic, types-PyYAML 依赖

验证:
- mypy --strict: 0 issues in 7 source files
- AdaptiveTokenBucket 运行时测试通过
- 所有语法检查通过

Co-authored-by: multica-agent <github@multica.ai>
This commit is contained in:
2026-06-24 11:54:02 +08:00
parent 205381c4ff
commit e829a4060b
8 changed files with 1235 additions and 19 deletions
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"""
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。
"""
from __future__ import annotations
import time
import threading
from typing import Any
from prometheus_client import (
CollectorRegistry,
Counter,
Gauge,
Histogram,
generate_latest,
make_asgi_app,
)
class PrometheusMetrics:
"""Sidecar Prometheus 指标收集器。
线程安全,所有公开方法通过 ``threading.Lock`` 保护。
"""
def __init__(self, registry: CollectorRegistry | None = None) -> None:
"""初始化所有 10 个 Prometheus 指标。
Args:
registry: 可选自定义 RegistryNone 则使用默认全局 registry。
"""
self._registry: CollectorRegistry = registry or CollectorRegistry()
self._lock: threading.Lock = threading.Lock()
self._start_time: float = time.time()
# ---- 1. 总请求数(按优先级 + 状态分组) ----
self.requests_total: Counter = Counter(
"sidecar_requests_total",
"Total requests processed by priority and status",
labelnames=["priority", "status"],
registry=self._registry,
)
# ---- 2. 可用令牌数 ----
self.tokens_available: Gauge = Gauge(
"sidecar_tokens_available",
"Current number of available tokens",
registry=self._registry,
)
# ---- 3. 令牌生成速率 ----
self.tokens_rate: Gauge = Gauge(
"sidecar_tokens_rate",
"Current token generation rate (tokens per minute)",
registry=self._registry,
)
# ---- 4. 各优先级队列深度 ----
self.queue_depth: Gauge = Gauge(
"sidecar_queue_depth",
"Queue depth by priority",
labelnames=["priority"],
registry=self._registry,
)
# ---- 5. 队列等待时间 Histogram ----
self.queue_latency_seconds: Histogram = Histogram(
"sidecar_queue_latency_seconds",
"Request wait time in queue in seconds",
labelnames=["priority"],
buckets=(0.01, 0.05, 0.1, 0.5, 1.0, 2.0, 5.0, 10.0, 30.0, 60.0, 120.0),
registry=self._registry,
)
# ---- 6. 上游响应延迟 Histogram ----
self.upstream_latency_seconds: Histogram = Histogram(
"sidecar_upstream_latency_seconds",
"Upstream response latency in seconds",
labelnames=["model_id"],
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 ----
self.upstream_errors_total: Counter = Counter(
"sidecar_upstream_errors_total",
"Upstream error count by status code and model",
labelnames=["status_code", "model_id"],
registry=self._registry,
)
# ---- 8. 降级直通次数 ----
self.fallback_passthrough_total: Counter = Counter(
"sidecar_fallback_passthrough_total",
"Total fallback / passthrough events (queue full or sidecar unavailable)",
registry=self._registry,
)
# ---- 9. 健康状态 ----
self.health_status: Gauge = Gauge(
"sidecar_health_status",
"Sidecar health: 0=unhealthy, 1=healthy",
registry=self._registry,
)
# ---- 10. 运行时长 ----
self.uptime_seconds: Gauge = Gauge(
"sidecar_uptime_seconds",
"Process uptime in seconds",
registry=self._registry,
)
# 避退模式指标(附加,不计入基础 10 个)
self.retreat_state: Gauge = Gauge(
"sidecar_retreat_state",
"Adaptive retreat state: 0=NORMAL, 1=RETREAT, 2=RECOVER",
registry=self._registry,
)
self.effective_rate_rpm: Gauge = Gauge(
"sidecar_effective_rate_rpm",
"Current effective rate in RPM (after retreat adjustments)",
registry=self._registry,
)
self.upstream_429_rate: Gauge = Gauge(
"sidecar_upstream_429_rate",
"Upstream 429 rate over the retreat observation window (0.0-1.0)",
registry=self._registry,
)
# 初始化
self.health_status.set(1)
# ---- ASGI app 生成 ----
def build_asgi_app(self) -> Any:
"""生成 Prometheus ASGI 应用,挂载到独立端口。
Returns:
可传给 uvicorn 的 ASGI app。
"""
return make_asgi_app(registry=self._registry)
# ---- 指标记录方法 ----
def record_request(self, priority: str, status: str) -> None:
"""记录一次请求。
Args:
priority: 优先级名(URGENT / HIGH / NORMAL / LOW)。
status: 状态(success / ratelimited / error)。
"""
with self._lock:
self.requests_total.labels(priority=priority, status=status).inc()
def record_queue_latency(self, priority: str, seconds: float) -> None:
"""记录排队延迟。
Args:
priority: 优先级名。
seconds: 排队等待秒数。
"""
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。
Args:
status_code: HTTP 状态码。
model_id: 模型标识符。
"""
with self._lock:
self.upstream_latency_seconds.labels(model_id=model_id).observe(0.0)
def record_upstream_error(self, status_code: int, model_id: str) -> None:
"""记录上游错误。
Args:
status_code: 错误 HTTP 状态码。
model_id: 模型标识符。
"""
with self._lock:
self.upstream_errors_total.labels(
status_code=str(status_code), model_id=model_id
).inc()
def record_upstream_latency(self, model_id: str, seconds: float) -> None:
"""记录上游响应延迟。
Args:
model_id: 模型标识符。
seconds: 响应延迟秒数。
"""
with self._lock:
self.upstream_latency_seconds.labels(model_id=model_id).observe(seconds)
def update_token_status(self, tokens: float, rate_per_minute: float) -> None:
"""更新令牌桶状态。
Args:
tokens: 当前可用令牌数。
rate_per_minute: 每分钟速率。
"""
with self._lock:
self.tokens_available.set(tokens)
self.tokens_rate.set(rate_per_minute)
def update_queue_depth(self, depths: dict[str, int]) -> None:
"""更新各优先级队列深度。
Args:
depths: {priority_name: count} 映射。
"""
with self._lock:
# 先清零所有已知标签再设置,避免残留旧值
for pri in ("URGENT", "HIGH", "NORMAL", "LOW"):
self.queue_depth.labels(priority=pri).set(depths.get(pri, 0))
def increment_fallback(self) -> None:
"""降级直通计数 +1。"""
with self._lock:
self.fallback_passthrough_total.inc()
def set_health(self, healthy: bool) -> None:
"""设置健康状态。
Args:
healthy: True=健康, False=不健康。
"""
with self._lock:
self.health_status.set(1 if healthy else 0)
def update_uptime(self) -> None:
"""更新运行时长。"""
with self._lock:
self.uptime_seconds.set(time.time() - self._start_time)
# ---- 避退模式指标 ----
def update_retreat_metrics(
self,
retreat_state: str,
effective_rate_rpm: float,
upstream_429_rate: float,
) -> None:
"""更新避退模式指标。
Args:
retreat_state: "normal" / "retreat" / "recover".
effective_rate_rpm: 当前实际速率 (RPM)。
upstream_429_rate: 上游 429 率 (0.0-1.0)。
"""
state_map: dict[str, int] = {"normal": 0, "retreat": 1, "recover": 2}
with self._lock:
self.retreat_state.set(state_map.get(retreat_state, 0))
self.effective_rate_rpm.set(effective_rate_rpm)
self.upstream_429_rate.set(upstream_429_rate)
# ---- 导出 ----
def generate_latest(self) -> bytes:
"""生成 Prometheus 文本格式的指标数据。
Returns:
Prometheus 文本格式 bytes。
"""
with self._lock:
self.update_uptime()
return generate_latest(self._registry)