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Cost Optimization

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What You’ll Learn

• Why cloud costs spiral out of control - The $50,000 surprise cloud bill (true story!)
• Azure pricing model - How Azure charges you (compute, storage, network) and hidden costs
• Quick wins - How to save 30-60% immediately (right-sizing, auto-shutdown, reserved instances)
• FinOps framework - How to implement Financial Operations culture in your team
• Service-specific optimization - AKS, Cosmos DB, Storage cost reduction tactics
• Real-world cost reduction - Case studies showing $28,000/month savings

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Introduction: The Cloud Cost Crisis (Start Here if You’re New)

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The $50,000 Surprise Bill (True Story)

Month 1: Azure bill = $500
  ↓ "Looks reasonable!"
  ↓
Month 2: Azure bill = $2,000
  ↓ "We launched new features, makes sense"
  ↓
Month 3: Azure bill = $8,000
  ↓ "Uh oh..."
  ↓
Month 4: Azure bill = $50,000 ❌
  ↓ CEO: "WE'RE GOING BANKRUPT!"

• Developer left 20 VMs running for testing (forgot to shut them down)
• Autoscaling set to create unlimited VMs (no budget limit)
• Storage set to Hot tier for all data (including old logs)
• Network traffic exploded (no CDN, serving 100 TB/month from Azure directly)
• No monitoring, no alerts, no cost tracking

• 20 test VMs @ $200/month =$4,000/month
• 50 autoscaled production VMs @ $300/month =$15,000/month
• 200 TB storage (Hot tier) @ $37/TB =$7,400/month
• 100 TB network egress @ $87/TB =$8,700/month
• Cosmos DB (50,000 RU/s always on) = $4,800/month
• Azure SQL (Premium tier, unused) = $3,000/month
• Misc (snapshots, disks, load balancers) = $7,100/month

• Auto-shutdown test VMs at night → Saved $2,400/month (60% savings)
• Right-sized production VMs → Saved $6,000/month
• Moved old data to Archive tier → Saved $6,500/month
• Added Azure Front Door CDN → Saved $7,000/month
• Cosmos DB autoscale → Saved $2,500/month
• Deleted unused resources → Saved $10,000/month

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Why Cloud Costs Are Hard to Control

Buy 10 servers upfront: $100,000
  ↓ Pay once
  ↓ Use for 3 years
  ↓ Total cost: $100,000 (fixed, predictable)
  ↓ Cost per month: $2,778
  ↓ No surprises ✅

Spin up 10 VMs: $0 upfront
  ↓ Pay per second of usage
  ↓ Developer creates 50 more VMs for testing
  ↓ Autoscaling creates 100 more VMs during spike
  ↓ Someone leaves VM running over weekend
  ↓ Total cost: Unpredictable! ❌
  ↓ Can range from $1,000 to $100,000/month

• Easy to spend: Spinning up resources takes 5 minutes, costs happen instantly
• Hard to track: Bills come 30 days later (you forget what you created)
• Invisible waste: Unused resources keep billing you (forgotten VMs, orphaned disks)
• Complex pricing: 1,000+ pricing variables (VM sizes, storage tiers, network egress, etc.)

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Real-World Cost Horror Stories

• QA team created test environment for Black Friday load testing
• Used production-sized VMs (50 Standard_D16s_v3 VMs)
• Ran load test for 2 days
• Forgot to delete test environment
• Test VMs ran for 6 months

• 50 VMs × $600/month × 6 months =$180,000
• Should have cost: 50 VMs × $600/month × 0.07 months (2 days) =$2,100
• Waste: $177,900

• Auto-delete policy: Delete all resources tagged “Test” after 7 days
• Cost: $0 (built-in Azure feature)

• E-commerce site serves product images directly from Azure Storage
• No CDN (Content Delivery Network)
• 500 TB/month of network egress

• Network egress: 500 TB × $87/TB =$43,500/month
• Storage: 10 TB × $18/TB =$180/month
• Total: $43,680/month

• CDN cache hit rate: 95%
• Network egress from Azure: 25 TB (95% served from CDN cache)
• 25 TB × $87/TB =$2,175/month
• CDN cost: $2,000/month
• Total: $4,175/month (90% savings!)

• Developer “stopped” 20 VMs thinking it would save money
• VMs showed as “Stopped” in Azure Portal
• Still got charged $4,000/month

• VMs were “Stopped” (shutdown OS) but NOT “Deallocated”
• Azure still reserved the hardware (CPU, RAM)
• Still charging compute costs

# Wrong: Just shutting down OS (still charges!)
Stop-VM -Name "my-vm"

# Correct: Deallocate VM (stops compute charges)
Stop-AzVM -Name "my-vm" -ResourceGroupName "rg-prod" -Force

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Understanding Azure Pricing (Simple Explanation)

• What: Cost to run VMs, App Services, Functions, Containers
• How charged: Per second/minute/hour
• Analogy: Renting a car (pay per hour you use it)
• Example: Standard_D2s_v3 VM = $0.096/hour =$70/month (if running 24/7)

• What: Cost to store data (disks, blobs, databases)
• How charged: Per GB stored per month + operations (read/write)
• Analogy: Renting a storage unit (pay per square foot per month)
• Example: 1 TB Blob Storage (Hot tier) = $18/month

• What: Cost to transfer data in/out of Azure
• How charged: Per GB transferred
• Analogy: Shipping packages (pay per pound shipped)
• Example: 100 GB egress = $8.70

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The Hidden Costs Nobody Tells You About

• VM stopped (OS shutdown): Still charges compute ❌
• VM deallocated: Compute stops, only storage charged ✅

• Deleted VM, but disk still exists: $100/month waste
• Fix: Delete disks when deleting VMs

• 10 snapshots × 100 GB × $0.05/GB =$50/month
• Fix: Delete old snapshots after 30 days

• Static public IP: $3.50/month (even if not attached to anything)
• Unattached public IPs: Common waste

• Empty load balancer: $20/month
• Fix: Delete unused load balancers

• Automatic backups for Azure SQL: Included
• Keeping backups > 35 days: Extra cost ($0.20/GB/month)

• The Problem: Cloud bills can spiral out of control. A $1,000/month bill can become$10,000/month if not monitored.
• The Solution: Understand what you’re paying for, eliminate waste, and optimize resources.

• Before Optimization: Company spends $50,000/month on Azure
  • 50 VMs running 24/7 (even at night)
  • Oversized VMs (using 10% CPU but paying for 100%)
  • Unused resources (old disks, snapshots)
  • No reservations (paying full price)
• After Optimization: Company spends $20,000/month (60% savings!)
  • Auto-shutdown for dev/test VMs
  • Right-sized VMs
  • Deleted unused resources
  • Purchased 3-year reservations

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Understanding Azure Pricing

Standard_D2s_v3 VM:
- Running: $0.096/hour = $70/month (if running 24/7)
- Stopped (deallocated): $0/month compute, $10/month storage
- Stopped (not deallocated): $70/month (still reserves hardware!)

1 TB Blob Storage:
- Hot tier: $18.40/month
- Cool tier: $10/month (44% savings)
- Archive tier: $0.99/month (95% savings!)

Website serving 100 GB/month:
- First 5 GB: Free
- Remaining 95 GB: $9.50/month (at $0.10/GB)

Standard_D2s_v3 VM:
- Pay-as-you-go: $70/month
- 1-year reservation: $42/month (40% savings)
- 3-year reservation: $28/month (60% savings)

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1. Azure Cost Management

[!WARNING] Gotcha: B-Series Credits “Burstable” (B-series) VMs are cheap because they limit your CPU. If you use 100% CPU for too long, you run out of “credits” and your VM gets throttled to 10% speed. Monitor your CPUCreditsRemaining metric!

[!TIP] Jargon Alert: Amortization If you pay $3,600 upfront for a 3-year reservation, "Amortized Cost" shows it as$100/month in your reports. This helps you track the effective monthly burn rate, not just the cash flow.

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2. Quick Wins

# Before: Standard_D4s_v3 (4 vCPU, $150/month)
# After: Standard_D2s_v3 (2 vCPU, $75/month)
# Savings: $75/month (50%)

az vm resize \
  --resource-group rg-prod \
  --name vm-web-01 \
  --size Standard_D2s_v3

# Stop VMs at 6 PM on weekdays
# Start VMs at 8 AM on weekdays

# Using Azure Automation
# Savings: 60% (nights + weekends)

# Find unattached disks
az disk list --query "[?diskState=='Unattached'].{Name:name, ResourceGroup:resourceGroup}"

# Delete them
az disk delete --name disk-old --resource-group rg-prod --yes

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3. Storage Cost Optimization

Hot → Cool → Archive

Example: 1 TB for 1 year
- Hot: $216/year
- Cool: $120/year (44% savings)
- Archive: $12/year (94% savings!)

{
  "rules": [{
    "name": "MoveToCool",
    "enabled": true,
    "type": "Lifecycle",
    "definition": {
      "actions": {
        "baseBlob": {
          "tierToCool": { "daysAfterModificationGreaterThan": 30 },
          "tierToArchive": { "daysAfterModificationGreaterThan": 90 },
          "delete": { "daysAfterModificationGreaterThan": 365 }
        }
      }
    }
  }]
}

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4. FinOps Best Practices

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5. FinOps Framework

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FinOps Principles

1. Teams need to collaborate: Finance, Engineering, Product work together
2. Everyone takes ownership: Engineers see cost impact of their decisions
3. Centralized team drives FinOps: Dedicated FinOps team enables best practices
4. Reports should be accessible: Real-time cost visibility for all stakeholders
5. Decisions are driven by business value: Cost vs performance tradeoffs
6. Take advantage of variable cost model: Right-size continuously

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FinOps Lifecycle

┌─────────────┐
│   INFORM    │  ← Visibility, allocation, benchmarking
└──────┬──────┘
       ↓
┌─────────────┐
│  OPTIMIZE   │  ← Right-sizing, reservations, waste removal
└──────┬──────┘
       ↓
┌─────────────┐
│  OPERATE    │  ← Continuous improvement, automation
└─────────────┘

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Implementing FinOps

# 1. Enable Cost Management
az costmanagement export create \
  --name daily-costs \
  --type ActualCost \
  --schedule-recurrence Daily \
  --storage-account-id /subscriptions/.../storageAccounts/costs

# 2. Tag all resources
az tag create --resource-id $RESOURCE_ID \
  --tags Environment=Production Team=Platform CostCenter=Engineering

# 3. Create cost alerts
az consumption budget create \
  --budget-name monthly-budget \
  --amount 10000 \
  --time-grain Monthly \
  --start-date 2026-01-01 \
  --end-date 2026-12-31

• Assign cost owners to each resource group
• Create showback reports per team
• Monthly cost review meetings

• Implement right-sizing recommendations
• Purchase reserved instances for base load
• Automate waste removal

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6. Tagging Strategy & Governance

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Essential Tags

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Tag Governance with Azure Policy

{
  "if": {
    "allOf": [
      {
        "field": "type",
        "equals": "Microsoft.Compute/virtualMachines"
      },
      {
        "field": "tags['Environment']",
        "exists": "false"
      }
    ]
  },
  "then": {
    "effect": "deny"
  }
}

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Bulk Tagging Script

# Tag all VMs in a resource group
$rg = "rg-production"
$tags = @{
    Environment = "Production"
    CostCenter = "Engineering"
    Owner = "[email protected]"
}

Get-AzResource -ResourceGroupName $rg | ForEach-Object {
    $resource = $_
    $resourceTags = $resource.Tags
    
    # Merge tags (don't overwrite existing)
    foreach ($key in $tags.Keys) {
        if (-not $resourceTags.ContainsKey($key)) {
            $resourceTags[$key] = $tags[$key]
        }
    }
    
    Set-AzResource -ResourceId $resource.ResourceId -Tag $resourceTags -Force
}

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7. Service-Specific Cost Optimization

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AKS Cost Optimization

1. Right-size node pools:

# Enable cluster autoscaler
az aks nodepool update \
  --cluster-name aks-prod \
  --name nodepool1 \
  --min-count 3 \
  --max-count 10 \
  --enable-cluster-autoscaler

2. Use Spot VMs for fault-tolerant workloads:

az aks nodepool add \
  --cluster-name aks-prod \
  --name spotpool \
  --priority Spot \
  --eviction-policy Delete \
  --spot-max-price -1 \
  --node-count 3

# Savings: Up to 90% for batch jobs

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Cosmos DB Cost Optimization

1. Use Autoscale instead of Manual:

# Before: 20,000 RU/s manual = $1,920/month (always on)
# After: 2,000-20,000 RU/s autoscale = $960/month avg

az cosmosdb sql container throughput update \
  --account-name mycosmosdb \
  --database-name mydb \
  --name mycontainer \
  --max-throughput 20000  # Autoscale

2. Optimize queries (reduce RU consumption):

-- Bad: Full collection scan (1000 RUs)
SELECT * FROM c WHERE c.status = 'active'

-- Good: Use index (5 RUs)
SELECT c.id, c.name FROM c WHERE c.status = 'active'

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Storage Cost Optimization

{
  "rules": [
    {
      "name": "move-to-cool-after-30-days",
      "type": "Lifecycle",
      "definition": {
        "filters": {
          "blobTypes": ["blockBlob"]
        },
        "actions": {
          "baseBlob": {
            "tierToCool": {
              "daysAfterModificationGreaterThan": 30
            },
            "tierToArchive": {
              "daysAfterModificationGreaterThan": 90
            }
          }
        }
      }
    }
  }
}

• Hot: $0.0184/GB =$1,884/month for 100 TB
• Cool: $0.01/GB =$1,024/month (46% savings)
• Archive: $0.00099/GB =$101/month (95% savings)

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8. Real-World Cost Reduction Case Studies

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Case Study 1: E-Commerce Platform

• Monthly cost: $45,000
• 50 VMs running 24/7
• All resources in Premium tier

1. Right-sized VMs (avg CPU 15%) → Saved $8,000/month
2. Stopped dev/test VMs at night → Saved $6,000/month
3. Purchased 3-year RIs for prod → Saved $12,000/month
4. Moved logs to Cool storage → Saved $2,000/month

• Monthly cost: $17,000
• Savings: $28,000/month (62%)

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Case Study 2: SaaS Startup

• Monthly cost: $12,000
• AKS cluster with 20 nodes
• Cosmos DB at 50,000 RU/s

1. Enabled AKS cluster autoscaler → Saved $3,500/month
2. Cosmos DB autoscale → Saved $2,500/month
3. Lifecycle management for storage → Saved $1,200/month
4. Deleted unused resources → Saved $800/month

• Monthly cost: $4,000
• Savings: $8,000/month (67%)

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9. Cost Optimization Checklist

✅ Right-sized VMs (not oversized)
✅ Reserved Instances for stable workloads
✅ Spot VMs for batch/testing
✅ Auto-shutdown for dev/test
✅ Deleted unused resources
✅ Storage lifecycle policies
✅ Monitoring and alerts enabled
✅ Tags on all resources
✅ Regular cost reviews scheduled

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6. Interview Questions

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Beginner Level

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Intermediate Level

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Advanced Level

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7. Key Takeaways

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Next Steps