Azure Container Services Comparison – Part 4: Cost Analysis & Migration Strategies

Azure Container Services Comparison – Part 4: Cost Analysis & Migration Strategies

This entry is part 4 of 5 in the series Azure Container Services Comparison

Azure Container Services Comparison: Container Apps vs Container Instances vs AKS

Part 4: Cost Analysis & Migration Strategies

Understanding the true cost implications and having clear migration paths between Azure’s container services can make or break your long-term success. Let’s dive into real-world pricing scenarios and practical migration strategies.

Real-World Cost Scenarios

Scenario 1: E-commerce API Backend

ServiceConfigurationMonthly CostBest For
ACINot suitableN/ANo auto-scaling
Container Apps0.5 vCPU, 1GB, 2-8 replicas$85-120Perfect fit
AKS3-node cluster$180-280Over-engineered

Scenario 2: Data Processing Pipeline

ServiceConfigurationMonthly CostBest For
ACI2 vCPU, 8GB, 2 hours daily$25-40Most cost-effective
Container Apps1 vCPU, 4GB, queue-triggered$60-90Event-driven automation
AKSJob controller, 2-node cluster$120-200Complex workflows

Migration Strategies

From ACI to Container Apps

# Migration steps for ACI to Container Apps
# 1. Convert container configuration
# Original ACI
{
    "containers": [{
        "name": "my-app",
        "image": "myregistry.azurecr.io/my-app:v1",
        "resources": {
            "requests": {
                "cpu": 1,
                "memoryInGB": 2
            }
        }
    }]
}

# Container Apps equivalent
{
    "template": {
        "containers": [{
            "name": "my-app",
            "image": "myregistry.azurecr.io/my-app:v1",
            "resources": {
                "cpu": 1,
                "memory": "2Gi"
            }
        }],
        "scale": {
            "minReplicas": 1,
            "maxReplicas": 10
        }
    }
}

From Container Apps to AKS

# Container Apps to Kubernetes migration
# Container Apps scaling rules become HPA
properties:
  template:
    scale:
      rules:
      - name: http-scaling
        http:
          metadata:
            concurrentRequests: "10"

# Equivalent Kubernetes HPA
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: my-app-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: my-app
  minReplicas: 2
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70

Cost Optimization Tips

  • Right-size resources: Start small and scale based on actual usage
  • Use scale-to-zero: For Container Apps, enable when traffic is intermittent
  • Optimize scaling rules: Fine-tune concurrent requests and CPU thresholds
  • Monitor and adjust: Regular cost reviews and optimization cycles

Coming Up Next

In Part 5, we’ll wrap up with production considerations, monitoring best practices, troubleshooting common issues, and Microsoft’s future roadmap for container services.


Cost optimization isn’t just about choosing the cheapest option—it’s about finding the sweet spot between cost, features, and operational complexity.

Navigate<< Azure Container Services Comparison – Part 3: Scaling, Networking & Advanced FeaturesAzure Container Services Comparison – Part 5: Production Considerations & Future Roadmap >>

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