云端部署指南

本指南将详细介绍如何在各种云平台上部署AnythingLLM，包括容器化部署、无服务器部署和托管服务部署等多种方案。

部署架构概览

基础架构组件

mermaid

graph TB
    A[负载均衡器] --> B[AnythingLLM 实例]
    B --> C[数据库]
    B --> D[向量数据库]
    B --> E[文件存储]
    B --> F[缓存层]
    
    G[CDN] --> A
    H[监控系统] --> B
    I[日志系统] --> B

部署模式选择

单实例部署

适合小型团队和开发环境：

成本低
配置简单
适合轻量级使用

高可用部署

适合生产环境：

多实例负载均衡
数据库集群
自动故障转移

微服务架构

适合大规模企业部署：

服务解耦
独立扩展
容错能力强

AWS 部署

Amazon ECS 部署

基础配置

yaml

# ecs-task-definition.json
{
  "family": "anythingllm",
  "networkMode": "awsvpc",
  "requiresCompatibilities": ["FARGATE"],
  "cpu": "1024",
  "memory": "2048",
  "executionRoleArn": "arn:aws:iam::account:role/ecsTaskExecutionRole",
  "taskRoleArn": "arn:aws:iam::account:role/ecsTaskRole",
  "containerDefinitions": [
    {
      "name": "anythingllm",
      "image": "mintplexlabs/anythingllm:latest",
      "portMappings": [
        {
          "containerPort": 3001,
          "protocol": "tcp"
        }
      ],
      "environment": [
        {
          "name": "NODE_ENV",
          "value": "production"
        },
        {
          "name": "DATABASE_URL",
          "value": "postgresql://user:pass@rds-endpoint:5432/anythingllm"
        }
      ],
      "secrets": [
        {
          "name": "OPENAI_API_KEY",
          "valueFrom": "arn:aws:secretsmanager:region:account:secret:openai-key"
        }
      ],
      "logConfiguration": {
        "logDriver": "awslogs",
        "options": {
          "awslogs-group": "/ecs/anythingllm",
          "awslogs-region": "us-east-1",
          "awslogs-stream-prefix": "ecs"
        }
      }
    }
  ]
}

ECS 服务配置

yaml

# ecs-service.yaml
apiVersion: v1
kind: Service
metadata:
  name: anythingllm-service
spec:
  serviceName: anythingllm
  cluster: production-cluster
  taskDefinition: anythingllm:1
  desiredCount: 2
  launchType: FARGATE
  networkConfiguration:
    awsvpcConfiguration:
      subnets:
        - subnet-12345678
        - subnet-87654321
      securityGroups:
        - sg-anythingllm
      assignPublicIp: ENABLED
  loadBalancers:
    - targetGroupArn: arn:aws:elasticloadbalancing:region:account:targetgroup/anythingllm
      containerName: anythingllm
      containerPort: 3001

Amazon EKS 部署

Kubernetes 部署文件

yaml

# k8s-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: anythingllm
  namespace: production
spec:
  replicas: 3
  selector:
    matchLabels:
      app: anythingllm
  template:
    metadata:
      labels:
        app: anythingllm
    spec:
      containers:
      - name: anythingllm
        image: mintplexlabs/anythingllm:latest
        ports:
        - containerPort: 3001
        env:
        - name: NODE_ENV
          value: "production"
        - name: DATABASE_URL
          valueFrom:
            secretKeyRef:
              name: anythingllm-secrets
              key: database-url
        - name: OPENAI_API_KEY
          valueFrom:
            secretKeyRef:
              name: anythingllm-secrets
              key: openai-api-key
        resources:
          requests:
            memory: "1Gi"
            cpu: "500m"
          limits:
            memory: "2Gi"
            cpu: "1000m"
        livenessProbe:
          httpGet:
            path: /api/health
            port: 3001
          initialDelaySeconds: 30
          periodSeconds: 10
        readinessProbe:
          httpGet:
            path: /api/ready
            port: 3001
          initialDelaySeconds: 5
          periodSeconds: 5
---
apiVersion: v1
kind: Service
metadata:
  name: anythingllm-service
  namespace: production
spec:
  selector:
    app: anythingllm
  ports:
  - protocol: TCP
    port: 80
    targetPort: 3001
  type: LoadBalancer

Ingress 配置

yaml

# ingress.yaml
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: anythingllm-ingress
  namespace: production
  annotations:
    kubernetes.io/ingress.class: "nginx"
    cert-manager.io/cluster-issuer: "letsencrypt-prod"
    nginx.ingress.kubernetes.io/ssl-redirect: "true"
spec:
  tls:
  - hosts:
    - anythingllm.yourdomain.com
    secretName: anythingllm-tls
  rules:
  - host: anythingllm.yourdomain.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: anythingllm-service
            port:
              number: 80

AWS App Runner 部署

App Runner 配置

yaml

# apprunner.yaml
version: 1.0
runtime: docker
build:
  commands:
    build:
      - echo "Building AnythingLLM"
run:
  runtime-version: latest
  command: npm start
  network:
    port: 3001
    env: PORT
  env:
    - name: NODE_ENV
      value: production
    - name: DATABASE_URL
      value: postgresql://user:pass@rds-endpoint:5432/anythingllm

RDS 数据库配置

PostgreSQL 配置

bash

# 创建 RDS 实例
aws rds create-db-instance \
  --db-instance-identifier anythingllm-db \
  --db-instance-class db.t3.medium \
  --engine postgres \
  --engine-version 14.9 \
  --master-username anythingllm \
  --master-user-password your-secure-password \
  --allocated-storage 100 \
  --storage-type gp2 \
  --vpc-security-group-ids sg-12345678 \
  --db-subnet-group-name anythingllm-subnet-group \
  --backup-retention-period 7 \
  --multi-az \
  --storage-encrypted

Google Cloud Platform 部署

Cloud Run 部署

基础部署

bash

# 构建并推送镜像
gcloud builds submit --tag gcr.io/PROJECT_ID/anythingllm

# 部署到 Cloud Run
gcloud run deploy anythingllm \
  --image gcr.io/PROJECT_ID/anythingllm \
  --platform managed \
  --region us-central1 \
  --allow-unauthenticated \
  --memory 2Gi \
  --cpu 2 \
  --max-instances 10 \
  --set-env-vars NODE_ENV=production \
  --set-env-vars DATABASE_URL=postgresql://user:pass@db-host:5432/anythingllm

Cloud Run 配置文件

yaml

# cloudrun.yaml
apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: anythingllm
  annotations:
    run.googleapis.com/ingress: all
spec:
  template:
    metadata:
      annotations:
        autoscaling.knative.dev/maxScale: "10"
        run.googleapis.com/cpu-throttling: "false"
        run.googleapis.com/memory: "2Gi"
        run.googleapis.com/cpu: "2"
    spec:
      containerConcurrency: 100
      containers:
      - image: gcr.io/PROJECT_ID/anythingllm
        ports:
        - containerPort: 3001
        env:
        - name: NODE_ENV
          value: production
        - name: DATABASE_URL
          valueFrom:
            secretKeyRef:
              name: anythingllm-secrets
              key: database-url
        resources:
          limits:
            memory: 2Gi
            cpu: 2000m

GKE 部署

集群创建

bash

# 创建 GKE 集群
gcloud container clusters create anythingllm-cluster \
  --zone us-central1-a \
  --num-nodes 3 \
  --machine-type e2-standard-4 \
  --enable-autoscaling \
  --min-nodes 1 \
  --max-nodes 10 \
  --enable-autorepair \
  --enable-autoupgrade

Helm Chart 部署

yaml

# values.yaml
replicaCount: 3

image:
  repository: gcr.io/PROJECT_ID/anythingllm
  tag: latest
  pullPolicy: Always

service:
  type: LoadBalancer
  port: 80
  targetPort: 3001

ingress:
  enabled: true
  annotations:
    kubernetes.io/ingress.global-static-ip-name: anythingllm-ip
    networking.gke.io/managed-certificates: anythingllm-ssl-cert
  hosts:
    - host: anythingllm.yourdomain.com
      paths:
        - path: /
          pathType: Prefix

resources:
  limits:
    cpu: 1000m
    memory: 2Gi
  requests:
    cpu: 500m
    memory: 1Gi

autoscaling:
  enabled: true
  minReplicas: 2
  maxReplicas: 10
  targetCPUUtilizationPercentage: 70

env:
  - name: NODE_ENV
    value: production
  - name: DATABASE_URL
    valueFrom:
      secretKeyRef:
        name: anythingllm-secrets
        key: database-url

Cloud SQL 配置

bash

# 创建 Cloud SQL 实例
gcloud sql instances create anythingllm-db \
  --database-version POSTGRES_14 \
  --tier db-custom-2-4096 \
  --region us-central1 \
  --backup-start-time 02:00 \
  --enable-bin-log \
  --storage-auto-increase

# 创建数据库
gcloud sql databases create anythingllm --instance anythingllm-db

# 创建用户
gcloud sql users create anythingllm \
  --instance anythingllm-db \
  --password your-secure-password

Microsoft Azure 部署

Azure Container Instances

基础部署

bash

# 创建资源组
az group create --name anythingllm-rg --location eastus

# 部署容器实例
az container create \
  --resource-group anythingllm-rg \
  --name anythingllm \
  --image mintplexlabs/anythingllm:latest \
  --cpu 2 \
  --memory 4 \
  --ports 3001 \
  --dns-name-label anythingllm-unique \
  --environment-variables \
    NODE_ENV=production \
    DATABASE_URL=postgresql://user:pass@db-host:5432/anythingllm \
  --secure-environment-variables \
    OPENAI_API_KEY=your-openai-key

ARM 模板部署

json

{
  "$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#",
  "contentVersion": "1.0.0.0",
  "parameters": {
    "containerName": {
      "type": "string",
      "defaultValue": "anythingllm"
    },
    "databaseUrl": {
      "type": "securestring"
    },
    "openaiApiKey": {
      "type": "securestring"
    }
  },
  "resources": [
    {
      "type": "Microsoft.ContainerInstance/containerGroups",
      "apiVersion": "2021-03-01",
      "name": "[parameters('containerName')]",
      "location": "[resourceGroup().location]",
      "properties": {
        "containers": [
          {
            "name": "anythingllm",
            "properties": {
              "image": "mintplexlabs/anythingllm:latest",
              "ports": [
                {
                  "port": 3001,
                  "protocol": "TCP"
                }
              ],
              "environmentVariables": [
                {
                  "name": "NODE_ENV",
                  "value": "production"
                },
                {
                  "name": "DATABASE_URL",
                  "secureValue": "[parameters('databaseUrl')]"
                },
                {
                  "name": "OPENAI_API_KEY",
                  "secureValue": "[parameters('openaiApiKey')]"
                }
              ],
              "resources": {
                "requests": {
                  "cpu": 2,
                  "memoryInGB": 4
                }
              }
            }
          }
        ],
        "osType": "Linux",
        "ipAddress": {
          "type": "Public",
          "ports": [
            {
              "port": 3001,
              "protocol": "TCP"
            }
          ],
          "dnsNameLabel": "anythingllm-unique"
        }
      }
    }
  ]
}

Azure Kubernetes Service (AKS)

集群创建

bash

# 创建 AKS 集群
az aks create \
  --resource-group anythingllm-rg \
  --name anythingllm-aks \
  --node-count 3 \
  --node-vm-size Standard_D2s_v3 \
  --enable-addons monitoring \
  --enable-cluster-autoscaler \
  --min-count 1 \
  --max-count 10 \
  --generate-ssh-keys

Azure App Service

配置文件

yaml

# azure-pipelines.yml
trigger:
- main

pool:
  vmImage: 'ubuntu-latest'

variables:
  dockerRegistryServiceConnection: 'anythingllm-acr'
  imageRepository: 'anythingllm'
  containerRegistry: 'anythingllmacr.azurecr.io'
  dockerfilePath: '$(Build.SourcesDirectory)/Dockerfile'
  tag: '$(Build.BuildId)'

stages:
- stage: Build
  displayName: Build and push stage
  jobs:
  - job: Build
    displayName: Build
    steps:
    - task: Docker@2
      displayName: Build and push an image to container registry
      inputs:
        command: buildAndPush
        repository: $(imageRepository)
        dockerfile: $(dockerfilePath)
        containerRegistry: $(dockerRegistryServiceConnection)
        tags: |
          $(tag)
          latest

- stage: Deploy
  displayName: Deploy stage
  dependsOn: Build
  jobs:
  - deployment: Deploy
    displayName: Deploy
    environment: 'production'
    strategy:
      runOnce:
        deploy:
          steps:
          - task: AzureWebAppContainer@1
            displayName: 'Azure Web App on Container Deploy'
            inputs:
              azureSubscription: 'anythingllm-subscription'
              appName: 'anythingllm-app'
              containers: '$(containerRegistry)/$(imageRepository):$(tag)'

DigitalOcean 部署

App Platform 部署

配置文件

yaml

# .do/app.yaml
name: anythingllm
services:
- name: web
  source_dir: /
  github:
    repo: your-username/anythingllm
    branch: main
  run_command: npm start
  environment_slug: node-js
  instance_count: 2
  instance_size_slug: basic-xxs
  http_port: 3001
  health_check:
    http_path: /api/health
  env:
  - key: NODE_ENV
    value: production
  - key: DATABASE_URL
    value: ${db.DATABASE_URL}
    type: SECRET
  - key: OPENAI_API_KEY
    value: your-openai-key
    type: SECRET

databases:
- name: db
  engine: PG
  version: "14"
  size: basic-xs
  num_nodes: 1

Droplet 部署

初始化脚本

bash

#!/bin/bash
# droplet-init.sh

# 更新系统
apt update && apt upgrade -y

# 安装 Docker
curl -fsSL https://get.docker.com -o get-docker.sh
sh get-docker.sh

# 安装 Docker Compose
curl -L "https://github.com/docker/compose/releases/download/v2.20.0/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
chmod +x /usr/local/bin/docker-compose

# 创建应用目录
mkdir -p /opt/anythingllm
cd /opt/anythingllm

# 创建 docker-compose.yml
cat > docker-compose.yml << EOF
version: '3.8'
services:
  anythingllm:
    image: mintplexlabs/anythingllm:latest
    ports:
      - "80:3001"
    environment:
      - NODE_ENV=production
      - DATABASE_URL=postgresql://anythingllm:password@db:5432/anythingllm
      - OPENAI_API_KEY=your-openai-key
    depends_on:
      - db
    restart: unless-stopped
    volumes:
      - anythingllm_data:/app/storage

  db:
    image: postgres:14
    environment:
      - POSTGRES_DB=anythingllm
      - POSTGRES_USER=anythingllm
      - POSTGRES_PASSWORD=password
    volumes:
      - postgres_data:/var/lib/postgresql/data
    restart: unless-stopped

volumes:
  anythingllm_data:
  postgres_data:
EOF

# 启动服务
docker-compose up -d

# 设置防火墙
ufw allow 22
ufw allow 80
ufw allow 443
ufw --force enable

Vercel 部署

配置文件

json

{
  "version": 2,
  "builds": [
    {
      "src": "server/index.js",
      "use": "@vercel/node"
    },
    {
      "src": "frontend/package.json",
      "use": "@vercel/static-build",
      "config": {
        "distDir": "dist"
      }
    }
  ],
  "routes": [
    {
      "src": "/api/(.*)",
      "dest": "/server/index.js"
    },
    {
      "src": "/(.*)",
      "dest": "/frontend/dist/$1"
    }
  ],
  "env": {
    "NODE_ENV": "production",
    "DATABASE_URL": "@database-url",
    "OPENAI_API_KEY": "@openai-api-key"
  },
  "functions": {
    "server/index.js": {
      "maxDuration": 30
    }
  }
}

Railway 部署

配置文件

toml

# railway.toml
[build]
builder = "DOCKERFILE"
dockerfilePath = "Dockerfile"

[deploy]
startCommand = "npm start"
healthcheckPath = "/api/health"
healthcheckTimeout = 100
restartPolicyType = "ON_FAILURE"
restartPolicyMaxRetries = 10

[[deploy.environmentVariables]]
name = "NODE_ENV"
value = "production"

[[deploy.environmentVariables]]
name = "PORT"
value = "3001"

监控和日志

Prometheus 监控

配置文件

yaml

# prometheus.yml
global:
  scrape_interval: 15s

scrape_configs:
  - job_name: 'anythingllm'
    static_configs:
      - targets: ['anythingllm:3001']
    metrics_path: '/api/metrics'
    scrape_interval: 30s

  - job_name: 'postgres'
    static_configs:
      - targets: ['postgres-exporter:9187']

  - job_name: 'redis'
    static_configs:
      - targets: ['redis-exporter:9121']

Grafana 仪表板

仪表板配置

json

{
  "dashboard": {
    "title": "AnythingLLM Monitoring",
    "panels": [
      {
        "title": "Request Rate",
        "type": "graph",
        "targets": [
          {
            "expr": "rate(http_requests_total[5m])",
            "legendFormat": "{{method}} {{status}}"
          }
        ]
      },
      {
        "title": "Response Time",
        "type": "graph",
        "targets": [
          {
            "expr": "histogram_quantile(0.95, rate(http_request_duration_seconds_bucket[5m]))",
            "legendFormat": "95th percentile"
          }
        ]
      },
      {
        "title": "Memory Usage",
        "type": "graph",
        "targets": [
          {
            "expr": "process_resident_memory_bytes",
            "legendFormat": "Memory"
          }
        ]
      }
    ]
  }
}

日志聚合

ELK Stack 配置

yaml

# docker-compose.logging.yml
version: '3.8'
services:
  elasticsearch:
    image: docker.elastic.co/elasticsearch/elasticsearch:8.8.0
    environment:
      - discovery.type=single-node
      - xpack.security.enabled=false
    ports:
      - "9200:9200"

  logstash:
    image: docker.elastic.co/logstash/logstash:8.8.0
    volumes:
      - ./logstash.conf:/usr/share/logstash/pipeline/logstash.conf
    ports:
      - "5044:5044"

  kibana:
    image: docker.elastic.co/kibana/kibana:8.8.0
    environment:
      - ELASTICSEARCH_HOSTS=http://elasticsearch:9200
    ports:
      - "5601:5601"

  filebeat:
    image: docker.elastic.co/beats/filebeat:8.8.0
    volumes:
      - ./filebeat.yml:/usr/share/filebeat/filebeat.yml
      - /var/log:/var/log:ro
      - /var/lib/docker/containers:/var/lib/docker/containers:ro
    command: filebeat -e -strict.perms=false

自动扩展

Kubernetes HPA

yaml

# hpa.yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: anythingllm-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: anythingllm
  minReplicas: 2
  maxReplicas: 20
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70
  - type: Resource
    resource:
      name: memory
      target:
        type: Utilization
        averageUtilization: 80
  behavior:
    scaleDown:
      stabilizationWindowSeconds: 300
      policies:
      - type: Percent
        value: 10
        periodSeconds: 60
    scaleUp:
      stabilizationWindowSeconds: 60
      policies:
      - type: Percent
        value: 50
        periodSeconds: 60

AWS Auto Scaling

json

{
  "AutoScalingGroupName": "anythingllm-asg",
  "MinSize": 2,
  "MaxSize": 10,
  "DesiredCapacity": 2,
  "DefaultCooldown": 300,
  "HealthCheckType": "ELB",
  "HealthCheckGracePeriod": 300,
  "LaunchTemplate": {
    "LaunchTemplateName": "anythingllm-template",
    "Version": "$Latest"
  },
  "TargetGroupARNs": [
    "arn:aws:elasticloadbalancing:region:account:targetgroup/anythingllm"
  ],
  "Tags": [
    {
      "Key": "Name",
      "Value": "anythingllm-instance",
      "PropagateAtLaunch": true
    }
  ]
}

备份策略

数据库备份

自动备份脚本

bash

#!/bin/bash
# backup.sh

DATE=$(date +%Y%m%d_%H%M%S)
BACKUP_DIR="/backups"
DB_NAME="anythingllm"

# 创建备份目录
mkdir -p $BACKUP_DIR

# 数据库备份
pg_dump $DATABASE_URL > $BACKUP_DIR/db_backup_$DATE.sql

# 压缩备份
gzip $BACKUP_DIR/db_backup_$DATE.sql

# 上传到 S3
aws s3 cp $BACKUP_DIR/db_backup_$DATE.sql.gz s3://anythingllm-backups/

# 清理本地备份 (保留7天)
find $BACKUP_DIR -name "db_backup_*.sql.gz" -mtime +7 -delete

echo "Backup completed: db_backup_$DATE.sql.gz"

Kubernetes CronJob 备份

yaml

# backup-cronjob.yaml
apiVersion: batch/v1
kind: CronJob
metadata:
  name: database-backup
spec:
  schedule: "0 2 * * *"  # 每天凌晨2点
  jobTemplate:
    spec:
      template:
        spec:
          containers:
          - name: backup
            image: postgres:14
            command:
            - /bin/bash
            - -c
            - |
              DATE=$(date +%Y%m%d_%H%M%S)
              pg_dump $DATABASE_URL | gzip > /backup/db_backup_$DATE.sql.gz
              aws s3 cp /backup/db_backup_$DATE.sql.gz s3://anythingllm-backups/
            env:
            - name: DATABASE_URL
              valueFrom:
                secretKeyRef:
                  name: anythingllm-secrets
                  key: database-url
            volumeMounts:
            - name: backup-storage
              mountPath: /backup
          volumes:
          - name: backup-storage
            emptyDir: {}
          restartPolicy: OnFailure

安全配置

SSL/TLS 配置

Let's Encrypt 证书

bash

# 安装 Certbot
apt install certbot python3-certbot-nginx

# 获取证书
certbot --nginx -d anythingllm.yourdomain.com

# 自动续期
echo "0 12 * * * /usr/bin/certbot renew --quiet" | crontab -

Nginx 配置

nginx

# nginx.conf
server {
    listen 80;
    server_name anythingllm.yourdomain.com;
    return 301 https://$server_name$request_uri;
}

server {
    listen 443 ssl http2;
    server_name anythingllm.yourdomain.com;

    ssl_certificate /etc/letsencrypt/live/anythingllm.yourdomain.com/fullchain.pem;
    ssl_certificate_key /etc/letsencrypt/live/anythingllm.yourdomain.com/privkey.pem;
    
    ssl_protocols TLSv1.2 TLSv1.3;
    ssl_ciphers ECDHE-RSA-AES256-GCM-SHA512:DHE-RSA-AES256-GCM-SHA512:ECDHE-RSA-AES256-GCM-SHA384:DHE-RSA-AES256-GCM-SHA384;
    ssl_prefer_server_ciphers off;
    ssl_session_cache shared:SSL:10m;

    location / {
        proxy_pass http://localhost:3001;
        proxy_http_version 1.1;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection 'upgrade';
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;
        proxy_cache_bypass $http_upgrade;
    }
}

网络安全

防火墙配置

bash

# UFW 配置
ufw default deny incoming
ufw default allow outgoing
ufw allow ssh
ufw allow 80
ufw allow 443
ufw enable

# 限制 SSH 访问
ufw limit ssh

安全组配置 (AWS)

json

{
  "GroupName": "anythingllm-sg",
  "Description": "Security group for AnythingLLM",
  "SecurityGroupRules": [
    {
      "IpPermissions": [
        {
          "IpProtocol": "tcp",
          "FromPort": 80,
          "ToPort": 80,
          "IpRanges": [{"CidrIp": "0.0.0.0/0"}]
        },
        {
          "IpProtocol": "tcp",
          "FromPort": 443,
          "ToPort": 443,
          "IpRanges": [{"CidrIp": "0.0.0.0/0"}]
        },
        {
          "IpProtocol": "tcp",
          "FromPort": 22,
          "ToPort": 22,
          "IpRanges": [{"CidrIp": "YOUR_IP/32"}]
        }
      ]
    }
  ]
}

故障排除

常见问题

容器启动失败

bash

# 检查容器日志
docker logs anythingllm

# 检查资源使用
docker stats anythingllm

# 检查网络连接
docker exec anythingllm curl -I http://localhost:3001/api/health

数据库连接问题

bash

# 测试数据库连接
psql $DATABASE_URL -c "SELECT 1;"

# 检查数据库状态
kubectl get pods -l app=postgres
kubectl logs postgres-pod-name

性能问题

bash

# 检查资源使用
kubectl top pods
kubectl top nodes

# 检查 HPA 状态
kubectl get hpa
kubectl describe hpa anythingllm-hpa

调试工具

健康检查脚本

bash

#!/bin/bash
# health-check.sh

echo "Checking AnythingLLM health..."

# 检查应用健康
if curl -f http://localhost:3001/api/health > /dev/null 2>&1; then
    echo "✓ Application is healthy"
else
    echo "✗ Application health check failed"
    exit 1
fi

# 检查数据库连接
if psql $DATABASE_URL -c "SELECT 1;" > /dev/null 2>&1; then
    echo "✓ Database connection is healthy"
else
    echo "✗ Database connection failed"
    exit 1
fi

# 检查磁盘空间
DISK_USAGE=$(df / | awk 'NR==2 {print $5}' | sed 's/%//')
if [ $DISK_USAGE -lt 90 ]; then
    echo "✓ Disk usage is normal ($DISK_USAGE%)"
else
    echo "⚠ Disk usage is high ($DISK_USAGE%)"
fi

echo "Health check completed"

最佳实践

部署检查清单

部署前检查

[ ] 选择合适的云平台和服务
[ ] 配置环境变量和密钥
[ ] 设置数据库和存储
[ ] 配置网络和安全组
[ ] 准备监控和日志系统
[ ] 制定备份策略
[ ] 测试部署流程

部署后验证

[ ] 应用健康检查通过
[ ] 数据库连接正常
[ ] API 端点可访问
[ ] 监控指标正常
[ ] 日志收集工作
[ ] 备份任务运行
[ ] 安全配置生效

性能优化建议

应用层优化

启用应用缓存
优化数据库查询
使用 CDN 加速静态资源
实施负载均衡
配置合适的资源限制

基础设施优化

选择合适的实例类型
配置自动扩展
使用多可用区部署
优化网络配置
实施缓存策略

成本控制

成本优化策略

使用预留实例或节约计划
实施自动扩展减少闲置资源
选择合适的存储类型
监控和优化数据传输成本
定期审查和清理未使用资源

通过遵循本指南，您可以在各种云平台上成功部署AnythingLLM，并确保其在生产环境中的稳定运行。记住要根据具体的业务需求和预算选择最适合的部署方案。

云端部署指南 ​

部署架构概览 ​

基础架构组件 ​

部署模式选择 ​

单实例部署 ​

高可用部署 ​

微服务架构 ​

AWS 部署 ​

Amazon ECS 部署 ​

基础配置 ​

ECS 服务配置 ​

Amazon EKS 部署 ​

Kubernetes 部署文件 ​

Ingress 配置 ​

AWS App Runner 部署 ​

App Runner 配置 ​

RDS 数据库配置 ​

PostgreSQL 配置 ​

Google Cloud Platform 部署 ​

Cloud Run 部署 ​

基础部署 ​

Cloud Run 配置文件 ​

GKE 部署 ​

集群创建 ​

Helm Chart 部署 ​

Cloud SQL 配置 ​

Microsoft Azure 部署 ​

Azure Container Instances ​

基础部署 ​

ARM 模板部署 ​

Azure Kubernetes Service (AKS) ​

集群创建 ​

Azure App Service ​

配置文件 ​

DigitalOcean 部署 ​

App Platform 部署 ​

配置文件 ​

Droplet 部署 ​

初始化脚本 ​

Vercel 部署 ​

配置文件 ​

Railway 部署 ​

配置文件 ​

监控和日志 ​

Prometheus 监控 ​

配置文件 ​

Grafana 仪表板 ​

仪表板配置 ​

日志聚合 ​

ELK Stack 配置 ​

自动扩展 ​

Kubernetes HPA ​

AWS Auto Scaling ​

备份策略 ​

数据库备份 ​

自动备份脚本 ​

Kubernetes CronJob 备份 ​

安全配置 ​

SSL/TLS 配置 ​

Let's Encrypt 证书 ​

Nginx 配置 ​

网络安全 ​

防火墙配置 ​

安全组配置 (AWS) ​

故障排除 ​

常见问题 ​

容器启动失败 ​

数据库连接问题 ​

性能问题 ​

调试工具 ​

健康检查脚本 ​

最佳实践 ​

部署检查清单 ​

部署前检查 ​

部署后验证 ​

性能优化建议 ​

应用层优化 ​

基础设施优化 ​

成本控制 ​

成本优化策略 ​

云端部署指南

部署架构概览

基础架构组件

部署模式选择

单实例部署

高可用部署

微服务架构

AWS 部署

Amazon ECS 部署

基础配置

ECS 服务配置

Amazon EKS 部署

Kubernetes 部署文件

Ingress 配置

AWS App Runner 部署

App Runner 配置

RDS 数据库配置

PostgreSQL 配置

Google Cloud Platform 部署

Cloud Run 部署

基础部署

Cloud Run 配置文件

GKE 部署

集群创建

Helm Chart 部署

Cloud SQL 配置

Microsoft Azure 部署

Azure Container Instances

基础部署

ARM 模板部署

Azure Kubernetes Service (AKS)

集群创建

Azure App Service

配置文件

DigitalOcean 部署

App Platform 部署

配置文件

Droplet 部署

初始化脚本

Vercel 部署

配置文件

Railway 部署

配置文件

监控和日志

Prometheus 监控

配置文件

Grafana 仪表板

仪表板配置

日志聚合

ELK Stack 配置

自动扩展

Kubernetes HPA

AWS Auto Scaling

备份策略

数据库备份

自动备份脚本

Kubernetes CronJob 备份

安全配置

SSL/TLS 配置

Let's Encrypt 证书

Nginx 配置

网络安全

防火墙配置

安全组配置 (AWS)

故障排除

常见问题

容器启动失败

数据库连接问题

性能问题

调试工具

健康检查脚本

最佳实践

部署检查清单

部署前检查

部署后验证

性能优化建议

应用层优化

基础设施优化

成本控制

成本优化策略