34 lines
1.4 KiB
Bash
34 lines
1.4 KiB
Bash
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# login AKS
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az cloud set --name AzureCloud # Switch CLI to Azure cloud
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# az login # Log in to Azure China account (browser or device code flow)
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az account set -s 079d8bd8-b4cc-4892-9307-aa6dedf890e9 #! set subs
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az aks get-credentials -g rg-aiflow-lab -n aks-aiflow-lab --overwrite-existing --file ~/.kube/config
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####
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kubectl config use-context aks-aiflow-lab
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kubectl config current-context
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docker build . -t agentic-rag:1.0.16
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docker tag agentic-rag:1.0.16 acrsales2caiprd.azurecr.cn/agentic-rag:1.0.16
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docker push acrsales2caiprd.azurecr.cn/agentic-rag:1.0.16
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# kubectl create namespace knowledge-agent
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kubectl delete configmap agentic-rag-config -n knowledge-agent
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kubectl create configmap agentic-rag-config -n knowledge-agent --from-file=./deploy/prd/config.yaml --from-file=llm_prompt.yaml
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kubectl delete deployment agentic-rag -n knowledge-agent
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# kubectl delete ingress agentic-rag-ingress -n knowledge-agent # 注释掉，不要删除生产 Ingress
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kubectl apply -f deploy/prd/k8s-manifest.yml -n knowledge-agent
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# restart deployment
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kubectl rollout restart deployment agentic-rag -n knowledge-agent
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kubectl rollout status deployment/agentic-rag -n knowledge-agent
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kubectl get deployment agentic-rag -o wide -n knowledge-agent
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kubectl get pods -l app=agentic-rag -o wide -n knowledge-agent
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# Monitor logs
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kubectl logs -f deployment/agentic-rag -n knowledge-agent
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