deep seek企业级本地部署手册

以下是基于DeepSeek大模型的商业级本地部署方案的详细操作教程（Linux环境）：###########################DeepSeek本地部署详细教程############################前置条件-已获得DeepSeek官方授权的加密模型镜像文件（deepseek-encrypted-image.tar.gz）-物理服务器就绪（至少4节点，NVIDIAH100HGX）-网络配置完成（双冗余交换机，防火墙放行443端口）###########第一阶段：基础环境准备############1.操作系统安装与加固（在所有节点执行）sudoaptupdate&&sudoaptinstall-yubuntu-minimalopenssh-serversudoufwenablesudoufwallow22/tcpsudoufwallow443/tcpsudoufw--forceenable#安装CIS加固工具并配置sudoaptinstall-ylynissudolynisauditsystem--quicksudonano/etc/sysctl.d/99-security.conf#添加：net.ipv4.conf.all.rp_filter=1net.ipv4.icmp_echo_ignore_broadcasts=1#2.安装NVIDIA驱动（计算节点）sudoaptinstall-ycuda-drivers-535nvidia-smi--query-gpu=name--format=csv|grepH100||echo"驱动未正确安装"#3.Kubernetes集群初始化（主节点执行）sudokubeadminit\--apiserver-advertise-address=00\--pod-network-cidr=/16\--control-plane-endpoint=master:6443\--kubernetes-version=1.28.0mkdir-p$HOME/.kubesudocp-i/etc/kubernetes/admin.conf$HOME/.kube/configsudochown$(id-u):$(id-g)$HOME/.kube/config#4.安装网络插件（Calico）kubectlcreate-f/projectcalico/calico/v3.26.0/manifests/tigera-operator.yamlkubectlcreate-f/projectcalico/calico/v3.26.0/manifests/custom-resources.yaml###########第二阶段：安全组件部署############1.密钥管理系统安装（HashiCorpVault）helmrepoaddhashicorphelminstallvaulthashicorp/vault\--setserver.dev.enabled=false\--setserver.ha.enabled=true\--setserver.ha.raft.enabled=true#初始化Vault并生成根密钥vaultoperatorinit-key-shares=5-key-threshold=3#安全保存输出的密钥和根令牌！#加密模型密钥存储vaultsecretsenabletransitvaultwrite-ftransit/keys/deepseek_model_keytype=aes256-gcm96#2.API网关配置（Kong)cat<<EOF|kubectlapply-f-apiVersion:v1kind:Servicemetadata:name:kong-proxyspec:ports:-name:proxyport:443protocol:TCPselector:app:kongtype:LoadBalancer---apiVersion:/v1kind:KongPluginmetadata:name:rate-limitingconfig:minute:500policy:localplugin:rate-limitingEOF###########第三阶段：模型服务部署############1.导入加密的DeepSeek镜像sudodockerload<deepseek-encrypted-image.tar.gz#2.创建GPU隔离的命名空间kubectlcreatensdeepseek-productionkubectllabelnsdeepseek-production/gpu=present#3.部署模型推理服务cat<<EOF>deepseek-deploy.yamlapiVersion:apps/v1kind:Deploymentmetadata:name:deepseek-inferencenamespace:deepseek-productionspec:replicas:4selector:matchLabels:app:deepseektemplate:metadata:labels:app:deepseekspec:securityContext:runAsUser:1000fsGroup:2000containers:-name:modelimage:deepseek-encrypted:latestresources:limits:/gpu:2requests:cpu:"8"memory:"32Gi"volumeMounts:-name:model-storemountPath:/modelsvolumes:-name:model-storepersistentVolumeClaim:claimName:ceph-pvc---apiVersion:v1kind:Servicemetadata:name:deepseek-servicenamespace:deepseek-productionspec:selector:app:deepseekports:-port:8000targetPort:8000EOFkubectlapply-fdeepseek-deploy.yaml###########第四阶段：功能验证############API测试（使用测试客户端）curl-XPOST"/v1/completions"\-H"Authorization:Bearer$API_KEY"\-H"Content-Type:application/json"\-d'{"model":"deepseek-7b-chat","prompt":"你好，DeepSeek","temperature":0.7,"max_tokens":1024}'#监控查看（需提前部署Prometheus）kubectlport-forwardsvc/prometheus-k8s9090:9090-nmonitoring#访问http://localhost:9090查看GPU使用率和API错误率###########故障排查小贴士############GPU相关问题：-查看NVIDIA驱动日志：nvidia-bug-report.sh-检查设备插件状态：kubectldescribenode|grep-igpu#模型服务异常：-查看容器日志：kubectllogs-ndeepseek-production[pod_name]-检查模型加载状态：curllocalhost:8000/status（在Pod内执行）#网络连通性测试：-节点间延迟测试：ping<peer_IP>-带宽测试：iperf3-c<target_IP>###########################可选高级配置###########################1.混合云容灾：结合Velero将PV快照备份至S3存储2.AutoML优化：集成NNI框架进行超参数自动调优3.计算加速：安装NVIDIATritonInferenceServer实现动态批处理4.私有知识库对接：通过LangChain框架集成企业内部文档注意事项：密钥管理：任何阶段产生的加密密钥必须使用HSM模块或KMS进行保护，禁止明文存储。性能调优：建议在生产前进行阶段性压力测试，并根据实际负载调整HPA参数：Yaml#示例HPA配置apiVersion:autoscaling/v2kind:HorizontalPodAutoscalermetadata:name:deepseek-hpanamespace:deepseek-productionspec:scaleTargetRef:apiVersion:apps/v1kind:Deploymentname:deepseek-inferenceminReplicas:3maxReplicas:10metrics:-type:Resourceresource:name:/gputarget:type:UtilizationaverageUtilization:85安全审计：建议每季度使用下列工具进行扫描：漏洞扫描：Nessus（CVE