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Commit 0541253

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Yuriy Bezsonov
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Add eks scripts to agent
1 parent edabc2a commit 0541253

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‎infrastructure/scripts/spring-ai/eks-agent-deploy.sh‎

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#!/bin/bash
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# eks-agent-deploy.sh - Script to connect to ECR, build and push image, restart deployment, and show logs
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set -e
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echo "Starting deployment process for Spring AI Agent..."
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# Login to ECR
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echo "Logging in to Amazon ECR..."
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aws ecr get-login-password --region $AWS_REGION | docker login --username AWS --password-stdin $ECR_URI
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# Navigate to project directory
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echo "Navigating to project directory..."
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cd ~/environment/unicorn-spring-ai-agent || {
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echo "Error: Project directory not found. Exiting."
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exit 1
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}
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# Build and push container image
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echo "Building container image..."
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mvn spring-boot:build-image -DskipTests -Dspring-boot.build-image.imageName=$ECR_URI:latest
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echo "Pushing container image to ECR..."
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docker push $ECR_URI:latest
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# Restart deployment by applying a rolling update
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echo "Restarting deployment..."
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kubectl rollout restart deployment unicorn-spring-ai-agent -n unicorn-spring-ai-agent
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# Wait for pods to be ready
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echo "Waiting for pods to be ready..."
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kubectl rollout status deployment unicorn-spring-ai-agent -n unicorn-spring-ai-agent --timeout=300s
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# Get the pod name
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POD_NAME=$(kubectl get pods -n unicorn-spring-ai-agent -l app=unicorn-spring-ai-agent -o jsonpath='{.items[0].metadata.name}')
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if [ -z "$POD_NAME" ]; then
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echo "Error: Could not find pod. Exiting."
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exit 1
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fi
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# Show logs
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echo "Showing logs from pod $POD_NAME..."
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kubectl logs -f $POD_NAME -n unicorn-spring-ai-agent
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echo "Deployment process completed successfully!"

‎infrastructure/scripts/spring-ai/eks-agent-setup.sh‎

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#!/bin/bash
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# eks-agent-setup.sh - Script to set up EKS deployment, service, and ingress
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set -e
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echo "Setting up EKS resources for Spring AI Agent..."
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# Check if namespace exists, exit if it doesn't
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if ! kubectl get namespace unicorn-spring-ai-agent &>/dev/null; then
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echo "Error: Namespace 'unicorn-spring-ai-agent' does not exist. Please create it first."
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exit 1
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fi
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# Get MCP Server URL - continue with placeholder if not found
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echo "Getting MCP Server URL..."
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if ! MCP_URL=$(kubectl get ingress unicorn-store-spring -n unicorn-store-spring -o jsonpath='{.status.loadBalancer.ingress[0].hostname}' 2>/dev/null); then
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echo "Warning: Could not get MCP URL. Using placeholder value."
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MCP_URL="http://placeholder-mcp-url.example.com"
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else
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MCP_URL="http://$MCP_URL"
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echo "MCP URL: $MCP_URL"
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fi
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# Get ECR URI - exit if not found
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echo "Getting ECR URI..."
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if ! ECR_URI=$(aws ecr describe-repositories --repository-names unicorn-spring-ai-agent | jq --raw-output '.repositories[0].repositoryUri' 2>/dev/null); then
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echo "Error: Could not get ECR URI. Repository 'unicorn-spring-ai-agent' may not exist. Exiting."
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exit 1
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else
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echo "ECR URI: $ECR_URI"
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fi
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# Get database connection string
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echo "Getting database connection string..."
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if ! SPRING_DATASOURCE_URL=$(aws ssm get-parameter --name unicornstore-db-connection-string | jq --raw-output '.Parameter.Value' 2>/dev/null); then
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echo "Warning: Could not get database connection string. Using placeholder value."
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SPRING_DATASOURCE_URL="jdbc:postgresql://placeholder-db-url:5432/unicornstore"
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else
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echo "Database connection string retrieved successfully."
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fi
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# Create directory for Kubernetes manifests
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echo "Creating directory for Kubernetes manifests..."
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mkdir -p ~/environment/unicorn-spring-ai-agent/k8s
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# Create deployment manifest
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echo "Creating deployment manifest..."
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cat <<EOF > ~/environment/unicorn-spring-ai-agent/k8s/deployment.yaml
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apiVersion: apps/v1
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kind: Deployment
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metadata:
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name: unicorn-spring-ai-agent
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namespace: unicorn-spring-ai-agent
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labels:
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project: unicorn-store
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app: unicorn-spring-ai-agent
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spec:
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replicas: 1
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selector:
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matchLabels:
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app: unicorn-spring-ai-agent
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template:
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metadata:
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labels:
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app: unicorn-spring-ai-agent
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spec:
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nodeSelector:
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karpenter.sh/nodepool: dedicated
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serviceAccountName: unicorn-spring-ai-agent
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containers:
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- name: unicorn-spring-ai-agent
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resources:
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requests:
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cpu: "1"
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memory: "2Gi"
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image: ${ECR_URI}:latest
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imagePullPolicy: Always
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env:
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- name: SPRING_DATASOURCE_PASSWORD
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valueFrom:
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secretKeyRef:
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name: "unicornstore-db-secret"
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key: "password"
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optional: false
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- name: SPRING_DATASOURCE_URL
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value: ${SPRING_DATASOURCE_URL}
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- name: SPRING_AI_MCP_CLIENT_SSE_CONNECTIONS_SERVER1_URL
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value: ${MCP_URL}
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ports:
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- containerPort: 8080
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livenessProbe:
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httpGet:
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path: /actuator/health/liveness
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port: 8080
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failureThreshold: 6
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periodSeconds: 5
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readinessProbe:
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httpGet:
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path: /actuator/health/readiness
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port: 8080
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failureThreshold: 6
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periodSeconds: 5
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initialDelaySeconds: 10
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startupProbe:
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httpGet:
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path: /
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port: 8080
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failureThreshold: 6
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periodSeconds: 5
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initialDelaySeconds: 10
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lifecycle:
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preStop:
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exec:
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command: ["sh", "-c", "sleep 10"]
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securityContext:
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runAsNonRoot: true
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allowPrivilegeEscalation: false
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EOF
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kubectl apply -f ~/environment/unicorn-spring-ai-agent/k8s/deployment.yaml
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# Create service manifest
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echo "Creating service manifest..."
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cat <<EOF > ~/environment/unicorn-spring-ai-agent/k8s/service.yaml
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apiVersion: v1
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kind: Service
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metadata:
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name: unicorn-spring-ai-agent
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namespace: unicorn-spring-ai-agent
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labels:
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project: unicorn-store
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app: unicorn-spring-ai-agent
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spec:
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type: ClusterIP
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ports:
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- port: 80
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targetPort: 8080
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protocol: TCP
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selector:
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app: unicorn-spring-ai-agent
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EOF
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kubectl apply -f ~/environment/unicorn-spring-ai-agent/k8s/service.yaml
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# Create ingress manifest
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echo "Creating ingress manifest..."
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cat <<EOF > ~/environment/unicorn-spring-ai-agent/k8s/ingress.yaml
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apiVersion: networking.k8s.io/v1
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kind: Ingress
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metadata:
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name: unicorn-spring-ai-agent
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namespace: unicorn-spring-ai-agent
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annotations:
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alb.ingress.kubernetes.io/scheme: internet-facing
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alb.ingress.kubernetes.io/target-type: ip
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alb.ingress.kubernetes.io/load-balancer-attributes: idle_timeout.timeout_seconds=3600
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labels:
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project: unicorn-store
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app: unicorn-spring-ai-agent
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spec:
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ingressClassName: alb
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rules:
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- http:
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paths:
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- path: /
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pathType: Prefix
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backend:
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service:
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name: unicorn-spring-ai-agent
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port:
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number: 80
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EOF
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kubectl apply -f ~/environment/unicorn-spring-ai-agent/k8s/ingress.yaml
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kubectl wait deployment unicorn-spring-ai-agent -n unicorn-spring-ai-agent --for condition=Available=True --timeout=120s
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kubectl get deployment unicorn-spring-ai-agent -n unicorn-spring-ai-agent
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SVC_URL=http://$(kubectl get ingress unicorn-spring-ai-agent -n unicorn-spring-ai-agent -o jsonpath='{.status.loadBalancer.ingress[0].hostname}')
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while [[ $(curl -s -o /dev/null -w "%{http_code}" $SVC_URL/) != "200" ]]; do echo "Service not yet available ..." && sleep 5; done
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echo $SVC_URL
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echo Service is Ready!

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