forked from xiaohei/taiji-AI-PAD
141 lines
4.2 KiB
Batchfile
141 lines
4.2 KiB
Batchfile
@echo off
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REM Taiji AI-PAD AKS 部署脚本 (生产环境) - Windows 版本
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REM 部署到 taiji-ai-pda AKS 集群
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setlocal enabledelayedexpansion
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REM 配置变量 - 生产环境
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set ACR_NAME=taiji
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set ACR_LOGIN_SERVER=%ACR_NAME%.azurecr.io
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set RESOURCE_GROUP=taiji-ai-pda
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set AKS_NAME=taiji-ai-pda
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set NAMESPACE=taiji-ai
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echo === Taiji AI-PAD AKS 部署脚本 (生产环境) ===
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echo 警告: 您正在部署到生产环境!
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echo 目标集群: %AKS_NAME%
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echo 命名空间: %NAMESPACE%
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echo.
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REM 确认生产环境部署
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set /p confirm=确认部署到生产环境? (输入 'yes' 继续):
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if not "%confirm%"=="yes" (
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echo 部署已取消
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exit /b 0
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)
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REM 检查 Azure CLI 登录状态
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echo 检查 Azure 登录状态...
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az account show >nul 2>&1
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if errorlevel 1 (
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echo 请先运行 'az login' 登录 Azure
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exit /b 1
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)
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echo Azure 已登录
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REM 登录 ACR
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echo 登录 Azure Container Registry...
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az acr login --name %ACR_NAME%
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REM 获取 AKS 凭据
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echo 获取 AKS 集群凭据 (%AKS_NAME%)...
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az aks get-credentials --resource-group %RESOURCE_GROUP% --name %AKS_NAME% --overwrite-existing
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REM 构建并推送 Docker 镜像
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echo 构建并推送 Docker 镜像到 ACR...
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REM 构建 Data Ingestion
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REM --platform linux/amd64: 显式锁定架构，与 AKS 标准节点 (amd64) 匹配，避免在 arm64 Mac 上误构建为 arm64
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echo [1/2] 构建 Data Ingestion 镜像...
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docker build --platform linux/amd64 -t %ACR_LOGIN_SERVER%/data-ingestion:latest ./services/data-ingestion/
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docker push %ACR_LOGIN_SERVER%/data-ingestion:latest
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REM 构建 MCP Server
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echo [2/2] 构建 MCP Server 镜像...
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docker build --platform linux/amd64 -t %ACR_LOGIN_SERVER%/mcp-server:latest ./services/mcp-server/
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docker push %ACR_LOGIN_SERVER%/mcp-server:latest
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echo 所有镜像构建并推送完成!
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REM 部署到 AKS
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echo 部署到 AKS (生产环境)...
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REM 创建命名空间
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echo 创建命名空间...
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kubectl apply -f k8s/prod/namespace.yaml
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REM 部署 Secrets 和 ConfigMap
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echo 部署 Secrets 和 ConfigMap...
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kubectl apply -f k8s/prod/secrets.yaml
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kubectl apply -f k8s/prod/configmap.yaml
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REM 部署 NATS
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echo 部署 NATS 消息队列...
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kubectl apply -f k8s/prod/nats.yaml
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REM 等待 NATS 就绪
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echo 等待 NATS 就绪...
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kubectl wait --for=condition=ready pod -l app=nats -n %NAMESPACE% --timeout=120s
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REM 部署 Data Ingestion
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echo 部署 Data Ingestion...
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kubectl apply -f k8s/prod/data-ingestion.yaml
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REM 部署 MCP Server
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echo 部署 MCP Server...
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kubectl apply -f k8s/prod/mcp-server.yaml
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REM 部署 API Gateway
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echo 部署 API Gateway...
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kubectl apply -f k8s/prod/api-gateway.yaml
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REM 部署 Ingress
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echo 部署 Ingress...
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kubectl apply -f k8s/prod/ingress.yaml
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REM 部署 Prometheus 监控
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echo 部署 Prometheus 监控...
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kubectl apply -f k8s/prod/monitoring.yaml
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REM 等待所有服务就绪
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echo 等待所有服务就绪...
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kubectl wait --for=condition=ready pod -l app=data-ingestion -n %NAMESPACE% --timeout=180s
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kubectl wait --for=condition=ready pod -l app=mcp-server -n %NAMESPACE% --timeout=180s
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kubectl wait --for=condition=ready pod -l app=api-gateway -n %NAMESPACE% --timeout=180s
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kubectl wait --for=condition=ready pod -l app=prometheus -n %NAMESPACE% --timeout=180s
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REM 获取 API Gateway 外部 IP
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echo 获取 API Gateway 外部 IP...
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for /f "tokens=*" %%a in ('kubectl get svc api-gateway -n %NAMESPACE% -o jsonpath^="{.status.loadBalancer.ingress[0].ip}"') do set EXTERNAL_IP=%%a
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echo.
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echo === 生产环境部署完成! ===
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echo.
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echo 查看所有 Pod 状态:
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kubectl get pods -n %NAMESPACE%
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echo.
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echo 查看所有 Service:
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kubectl get svc -n %NAMESPACE%
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echo.
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echo 查看 Ingress:
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kubectl get ingress -n %NAMESPACE%
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echo.
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echo 生产环境配置信息:
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echo - 数据库: taiji_prod (生产库)
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echo - Redis: taiji2026.southeastasia.redis.azure.net
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echo - 命名空间: %NAMESPACE%
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if defined EXTERNAL_IP (
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echo.
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echo API Gateway 外部访问地址: http://%EXTERNAL_IP%
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echo - 健康检查: http://%EXTERNAL_IP%/health
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echo - MCP Server: http://%EXTERNAL_IP%/api/mcp/
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echo - Data Ingestion: http://%EXTERNAL_IP%/api/data/
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) else (
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echo.
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echo LoadBalancer IP 尚未分配，请稍后运行以下命令查看:
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echo kubectl get svc api-gateway -n %NAMESPACE%
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)
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endlocal
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