How to Reduce Your AWS Bills by 40%: A Practical Guide

Quick Wins (Week 1)

1. Find and Delete Unused Resources

Idle EC2 Instances:

# Find instances with low CPU utilization
aws cloudwatch get-metric-statistics \
  --namespace AWS/EC2 \
  --metric-name CPUUtilization \
  --dimensions Name=InstanceId,Value=i-xxxxx \
  --statistics Average \
  --period 86400 \
  --start-time 2025-01-01T00:00:00Z \
  --end-time 2025-01-31T00:00:00Z

Look for instances consistently under 5% CPU.

Unattached EBS Volumes:

aws ec2 describe-volumes \
  --filters Name=status,Values=available \
  --query 'Volumes[*].{ID:VolumeId,Size:Size,Type:VolumeType}'

Old Snapshots:

aws ec2 describe-snapshots --owner-ids self \
  --query 'Snapshots[?StartTime<=`2024-01-01`].[SnapshotId,VolumeSize,StartTime]' \
  --output table

2. Rightsize Your Instances

Most instances are oversized. Use AWS Cost Explorer's rightsizing recommendations:

# Get rightsizing recommendations via CLI
aws ce get-rightsizing-recommendation \
  --service EC2 \
  --configuration RecommendationTarget=SAME_INSTANCE_FAMILY

3. Implement S3 Lifecycle Policies

{
  "Rules": [
    {
      "ID": "TransitionToIA",
      "Status": "Enabled",
      "Filter": { "Prefix": "" },
      "Transitions": [
        {
          "Days": 30,
          "StorageClass": "STANDARD_IA"
        },
        {
          "Days": 90,
          "StorageClass": "GLACIER"
        }
      ]
    },
    {
      "ID": "DeleteOldVersions",
      "Status": "Enabled",
      "NoncurrentVersionExpiration": {
        "NoncurrentDays": 30
      }
    }
  ]
}

Medium-Term Optimizations (Month 1-3)

4. Reserved Instances & Savings Plans

Strategy:

Reserved Instance Strategy:
  
  Step 1: Analyze Usage
    - Review 3+ months of usage data
    - Identify stable baseline workloads
    - Note peak vs average utilization
  
  Step 2: Calculate Coverage
    - Reserve 60-70% of baseline (safe)
    - Keep 30-40% on-demand for flexibility
  
  Step 3: Choose Commitment
    - 1-year for uncertain growth
    - 3-year for proven stable workloads
    
  Example:
    Baseline: 10 m5.xlarge instances
    Reserved: 7 instances (70%)
    On-Demand: 3 instances (30%)
    Annual Savings: ~$15,000

5. Spot Instances for Non-Critical Workloads

# Spot Fleet configuration example
SpotFleetRequestConfig:
  TargetCapacity: 10
  TerminateInstancesWithExpiration: true
  LaunchSpecifications:
    - InstanceType: m5.xlarge
      WeightedCapacity: 1
    - InstanceType: m5.2xlarge
      WeightedCapacity: 2
    - InstanceType: m4.xlarge
      WeightedCapacity: 1
  AllocationStrategy: diversified

Advanced Optimizations

6. Auto-Scaling Based on Demand

# Auto-scaling policy example
ScalingPolicy:
  TargetTrackingConfiguration:
    TargetValue: 70.0
    PredefinedMetricSpecification:
      PredefinedMetricType: ASGAverageCPUUtilization
    ScaleInCooldown: 300
    ScaleOutCooldown: 60
    
  # Scale to zero on weekends (dev environments)
  ScheduledActions:
    - ScheduledActionName: ScaleDownWeekend
      Recurrence: "0 20 * * FRI"
      MinSize: 0
      MaxSize: 0
      DesiredCapacity: 0
    - ScheduledActionName: ScaleUpMonday
      Recurrence: "0 6 * * MON"
      MinSize: 2
      MaxSize: 10
      DesiredCapacity: 2

7. Use Graviton Processors

# Graviton instances offer 20-40% better price-performance
# Simply change instance type from:
# m5.xlarge → m6g.xlarge (ARM-based Graviton2)
# m5.xlarge → m7g.xlarge (ARM-based Graviton3)

Cost Monitoring Setup

// Set up AWS Budget alerts
const budgetConfig = {
  BudgetName: 'Monthly-AWS-Budget',
  BudgetLimit: {
    Amount: '5000',
    Unit: 'USD'
  },
  BudgetType: 'COST',
  TimeUnit: 'MONTHLY',
  NotificationsWithSubscribers: [
    {
      Notification: {
        NotificationType: 'ACTUAL',
        ComparisonOperator: 'GREATER_THAN',
        Threshold: 80,
        ThresholdType: 'PERCENTAGE'
      },
      Subscribers: [
        {
          SubscriptionType: 'EMAIL',
          Address: '[email protected]'
        }
      ]
    }
  ]
};

Summary: 40% Savings Breakdown