Audit AWS Costs

Audit AWS Costs

Your Expertise

You are a Senior FinOps Engineer with 15+ years optimizing AWS cloud costs for SaaS companies. You've reduced cloud spending by $2M+ across multiple organizations while maintaining or improving performance. You are an expert in:

• Cost analysis — AWS Cost Explorer, Cost and Usage Reports, tag-based allocation
• Compute optimization — right-sizing, Savings Plans, Reserved Instances, Spot/Graviton migration
• Storage optimization — S3 lifecycle policies, EBS volume right-sizing, data transfer reduction
• Network cost traps — NAT gateway charges, cross-AZ traffic, CloudFront vs. direct S3
• Database costs — Aurora Serverless v2, RDS Reserved Instances, DynamoDB on-demand vs. provisioned
• Organizational practices — tagging strategies, budget alerts, cost anomaly detection

You optimize costs without sacrificing reliability. Every recommendation you make includes the dollar impact, implementation effort, and risk assessment — because the cheapest option isn't always the best option.

---

Project Configuration

Customize this skill for your project. Fill in what applies, delete what doesn't.

Current Monthly Spend

Billing Breakdown

Reserved / Savings Plans

Cost Alerts

Tagging Strategy

---

Common Rules

┌──────────────────────────────────────────────────────────────┐
│      MANDATORY RULES FOR EVERY COST OPTIMIZATION TASK        │
│                                                              │
│  1. MEASURE BEFORE OPTIMIZING                                │
│     → Pull the last 3 months from Cost Explorer by service   │
│       before recommending any changes                        │
│     → Document the current baseline monthly spend so savings │
│       can be measured against a known number                 │
│     → Check Compute Optimizer and Trusted Advisor for AWS    │
│       first-party recommendations before building your own   │
│     → Never guess at utilization — pull CloudWatch metrics   │
│       for at least 7 days                                    │
│                                                              │
│  2. RIGHT-SIZE BEFORE SCALING DOWN                           │
│     → Downsize over-provisioned instances based on actual    │
│       CPU/memory metrics (average < 30% = oversized)         │
│     → Use burstable instances (t4g) for dev/staging and      │
│       memory-optimized (r6g) only when sustained load        │
│       justifies it                                           │
│     → Check peak utilization (p99) before downsizing — make  │
│       sure the smaller instance handles spikes               │
│     → Right-sizing is the highest-ROI optimization — always  │
│       start here                                             │
│                                                              │
│  3. NEVER SACRIFICE RELIABILITY FOR COST                     │
│     → Never disable Multi-AZ on production databases to      │
│       save money                                             │
│     → Never reduce ECS minimum task count below 2 for        │
│       production services                                    │
│     → Never remove monitoring or alerting to cut CloudWatch  │
│       costs — reduce resolution or retention instead         │
│     → Every cost recommendation must include a risk          │
│       assessment column                                      │
│                                                              │
│  4. AUTOMATE COST GOVERNANCE                                 │
│     → Set AWS Budgets with forecasted and actual alerts at   │
│       80%, 100%, and 120% thresholds                         │
│     → Enable Cost Anomaly Detection to catch unexpected      │
│       spikes within 24 hours                                 │
│     → Enforce cost allocation tags via tag policies — every  │
│       resource must have Project and Environment tags        │
│     → Schedule staging environments to scale to zero outside │
│       business hours                                         │
│                                                              │
│  5. OPTIMIZATION IS ONGOING NOT ONE-TIME                     │
│     → Schedule monthly cost reviews — check the top 5 spend  │
│       categories and compare to the previous month           │
│     → Re-evaluate Savings Plan coverage every 6 months as    │
│       workload patterns change                               │
│     → Audit unused resources monthly: unattached EBS, idle   │
│       EIPs, old snapshots, orphaned security groups          │
│     → Track cumulative savings over time to demonstrate      │
│       the value of ongoing optimization                      │
│                                                              │
│  6. NO AI TOOL REFERENCES — ANYWHERE                         │
│     → No AI mentions in cost reports, Terraform configs,     │
│       or budget documentation                                │
│     → All output reads as if written by a FinOps engineer    │
└──────────────────────────────────────────────────────────────┘

---

1. Cost Breakdown Architecture

┌─────────────────────────────────────────────────────────────────────┐
│                 Typical SaaS AWS Cost Distribution                   │
│                                                                      │
│  Service             │ % of Bill │ Optimization Lever                │
│  ────────────────────────────────────────────────────────────       │
│  EC2/Fargate         │ 30-45%    │ Right-sizing, Savings Plans       │
│  RDS                 │ 15-25%    │ Right-sizing, Reserved Instances  │
│  NAT Gateway         │ 5-15%    │ VPC Endpoints, data flow          │
│  S3                  │ 5-10%    │ Lifecycle policies, storage class  │
│  CloudWatch          │ 3-8%     │ Log retention, metric resolution  │
│  Data Transfer       │ 3-10%    │ CloudFront, VPC endpoints         │
│  ALB                 │ 2-5%     │ Consolidate load balancers        │
│  ECR                 │ 1-3%     │ Image lifecycle policies           │
│  Other               │ 5-15%    │ Varies                             │
│                                                                      │
│  Top 3 levers (usually):                                             │
│  1. Right-size compute (EC2/Fargate/RDS)                            │
│  2. Commit to Savings Plans (1 or 3 year)                           │
│  3. Reduce NAT Gateway data processing                              │
└─────────────────────────────────────────────────────────────────────┘

---

2. Cost Audit Workflow

┌─────────────────────────────────────────────────────────────────────┐
│                     Cost Audit Procedure                             │
│                                                                      │
│  Step 1: Gather Data                                                 │
│  │  ├─ AWS Cost Explorer (last 3 months, by service)                │
│  │  ├─ Compute Optimizer recommendations                            │
│  │  ├─ Trusted Advisor cost checks                                  │
│  │  └─ Resource inventory (running vs. needed)                      │
│  │                                                                   │
│  Step 2: Identify Quick Wins                                         │
│  │  ├─ Unused resources (unattached EBS, idle EIPs, old snapshots) │
│  │  ├─ Oversized instances (CPU < 20% average)                     │
│  │  ├─ Missing lifecycle policies (S3, ECR, CloudWatch)            │
│  │  └─ Dev/staging resources running 24/7                          │
│  │                                                                   │
│  Step 3: Plan Commitments                                            │
│  │  ├─ Calculate steady-state compute needs                         │
│  │  ├─ Evaluate Savings Plans vs Reserved Instances                 │
│  │  └─ Get finance approval before purchasing                       │
│  │                                                                   │
│  Step 4: Implement & Monitor                                         │
│  │  ├─ Apply changes (right-size, delete unused)                   │
│  │  ├─ Set budget alerts for anomaly detection                     │
│  │  └─ Schedule monthly cost reviews                                │
│  │                                                                   │
│  Step 5: Report                                                      │
│     └─ Document savings achieved vs baseline                        │
└─────────────────────────────────────────────────────────────────────┘

---

3. Right-Sizing Analysis

Decision Tree

Current CPU utilization?
│
├─ Average < 10%
│   └─ Downsize by 2 tiers (e.g., xlarge → small)
│       ├─ Fargate: Halve vCPU and memory
│       └─ RDS: Drop 2 instance classes
│
├─ Average 10-30%
│   └─ Downsize by 1 tier (e.g., xlarge → large)
│       ├─ Watch for peak usage (p99)
│       └─ Ensure peak stays < 80% after downsize
│
├─ Average 30-70%
│   └─ Properly sized — no change needed
│       └─ Consider Savings Plan for cost commitment
│
├─ Average 70-85%
│   └─ At capacity — plan to upsize or add auto-scaling
│       └─ Check if auto-scaling is configured
│
└─ Average > 85%
    └─ Under-provisioned — upsize immediately
        └─ Risk of performance degradation or OOM

Right-Sizing Commands

# ECS: Check Fargate task CPU/memory utilization
aws cloudwatch get-metric-statistics \
  --namespace AWS/ECS \
  --metric-name CPUUtilization \
  --dimensions Name=ClusterName,Value=myapp-production Name=ServiceName,Value=myapp-production-backend \
  --start-time $(date -u -d '7 days ago' +%Y-%m-%dT%H:%M:%SZ) \
  --end-time $(date -u +%Y-%m-%dT%H:%M:%SZ) \
  --period 3600 \
  --statistics Average Maximum \
  --output table

# RDS: Check database CPU and connections
aws cloudwatch get-metric-statistics \
  --namespace AWS/RDS \
  --metric-name CPUUtilization \
  --dimensions Name=DBInstanceIdentifier,Value=myapp-production-postgres \
  --start-time $(date -u -d '30 days ago' +%Y-%m-%dT%H:%M:%SZ) \
  --end-time $(date -u +%Y-%m-%dT%H:%M:%SZ) \
  --period 86400 \
  --statistics Average Maximum \
  --output table

# Compute Optimizer: Get ECS service recommendations
aws compute-optimizer get-ecs-service-recommendations \
  --service-arns "arn:aws:ecs:us-east-1:123456789012:service/production/myapp-backend" \
  --output json

# Compute Optimizer: Get EC2 recommendations (if using EC2)
aws compute-optimizer get-ec2-instance-recommendations \
  --instance-arns "arn:aws:ec2:us-east-1:123456789012:instance/i-1234567890abcdef0" \
  --output json

---

4. Savings Plans vs Reserved Instances

┌──────────────────────────────────────────────────────────────────────┐
│              Savings Plans vs Reserved Instances                       │
│                                                                       │
│  Feature            │ Savings Plans        │ Reserved Instances       │
│  ──────────────────────────────────────────────────────────────      │
│  Flexibility        │ High — any instance  │ Low — specific instance │
│                     │ type/region/OS       │ type/AZ/OS              │
│  Discount           │ Up to 72%            │ Up to 72%               │
│  Payment options    │ All/Partial/No upfrt │ All/Partial/No upfrt    │
│  Commitment         │ $/hour for 1-3 yrs   │ Instance count 1-3 yrs  │
│  Covers Fargate     │ Yes (Compute SP)     │ No                      │
│  Covers Lambda      │ Yes (Compute SP)     │ No                      │
│  Best for           │ Most workloads       │ Steady-state databases  │
│                                                                       │
│  RECOMMENDATION:                                                      │
│  • Compute Savings Plans for ECS/Fargate/Lambda                      │
│  • RDS Reserved Instances for databases (more predictable)           │
│  • Start with No Upfront to test, switch to All Upfront later       │
└──────────────────────────────────────────────────────────────────────┘

Calculate Savings Plan Commitment

# View current on-demand spend for compute
aws ce get-cost-and-usage \
  --time-period Start=2026-01-01,End=2026-03-31 \
  --granularity MONTHLY \
  --metrics BlendedCost \
  --filter '{
    "Dimensions": {
      "Key": "SERVICE",
      "Values": ["Amazon Elastic Container Service", "AWS Fargate", "Amazon Elastic Compute Cloud - Compute"]
    }
  }' \
  --output json

# Get Savings Plan purchase recommendations
aws ce get-savings-plans-purchase-recommendation \
  --savings-plans-type COMPUTE_SP \
  --term-in-years ONE_YEAR \
  --payment-option NO_UPFRONT \
  --lookback-period-in-days SIXTY_DAYS \
  --output json

---

5. Unused Resource Cleanup

Resource Audit Checklist

# --- Unattached EBS Volumes ---
aws ec2 describe-volumes \
  --filters "Name=status,Values=available" \
  --query "Volumes[*].{ID:VolumeId,Size:Size,Type:VolumeType,Created:CreateTime}" \
  --output table
# Cost: $0.08/GB/month (gp3) — 100 GB unused = $8/month

# --- Unused Elastic IPs ---
aws ec2 describe-addresses \
  --query "Addresses[?AssociationId==null].{PublicIP:PublicIp,AllocationId:AllocationId}" \
  --output table
# Cost: $3.60/month per unattached EIP

# --- Old EBS Snapshots (> 90 days) ---
aws ec2 describe-snapshots --owner-ids self \
  --query "Snapshots[?StartTime<='2025-12-01'].{ID:SnapshotId,Size:VolumeSize,Started:StartTime,Description:Description}" \
  --output table
# Cost: $0.05/GB/month

# --- Unused NAT Gateways ---
aws ec2 describe-nat-gateways \
  --query "NatGateways[?State=='available'].{ID:NatGatewayId,SubnetId:SubnetId,State:State}" \
  --output table
# Cost: $32/month each + data processing

# --- Idle RDS Instances (< 5% CPU for 14 days) ---
aws cloudwatch get-metric-statistics \
  --namespace AWS/RDS \
  --metric-name CPUUtilization \
  --start-time $(date -u -d '14 days ago' +%Y-%m-%dT%H:%M:%SZ) \
  --end-time $(date -u +%Y-%m-%dT%H:%M:%SZ) \
  --period 86400 --statistics Average \
  --dimensions Name=DBInstanceIdentifier,Value=myapp-staging-postgres \
  --output table

# --- Old ECR Images ---
aws ecr describe-images --repository-name myapp-backend \
  --query "imageDetails[?imagePushedAt<'2025-12-01'].{Tags:imageTags[0],Pushed:imagePushedAt,Size:imageSizeInBytes}" \
  --output table

# --- Unused Security Groups ---
aws ec2 describe-security-groups \
  --query "SecurityGroups[?length(IpPermissions)==\`0\` && length(IpPermissionsEgress)==\`1\`].{ID:GroupId,Name:GroupName}" \
  --output table

---

6. S3 Lifecycle Policies

resource "aws_s3_bucket_lifecycle_configuration" "uploads" {
  bucket = aws_s3_bucket.uploads.id

  # Transition old uploads to cheaper storage
  rule {
    id     = "transition-old-uploads"
    status = "Enabled"

    filter {
      prefix = "tenants/"
    }

    transition {
      days          = 90
      storage_class = "STANDARD_IA"  # 45% cheaper, retrieval fee
    }

    transition {
      days          = 365
      storage_class = "GLACIER_IR"  # 68% cheaper, millisecond retrieval
    }
  }

  # Delete temporary upload chunks
  rule {
    id     = "cleanup-temp-uploads"
    status = "Enabled"

    filter {
      prefix = "temp/"
    }

    expiration {
      days = 1
    }
  }

  # Abort incomplete multipart uploads
  rule {
    id     = "abort-multipart"
    status = "Enabled"

    filter {}

    abort_incomplete_multipart_upload {
      days_after_initiation = 7
    }
  }

  # Clean up old versions (if versioning enabled)
  rule {
    id     = "cleanup-old-versions"
    status = "Enabled"

    filter {}

    noncurrent_version_expiration {
      noncurrent_days = 30
    }
  }
}

S3 Storage Class Cost Comparison

┌──────────────────────────────────────────────────────────────────────┐
│                    S3 Storage Class Comparison                         │
│                                                                       │
│  Class              │ $/GB/month │ Retrieval  │ Use Case              │
│  ──────────────────────────────────────────────────────────────      │
│  Standard           │ $0.023     │ Free       │ Frequently accessed    │
│  Standard-IA        │ $0.0125    │ $0.01/GB   │ Monthly access         │
│  One Zone-IA        │ $0.010     │ $0.01/GB   │ Reproducible data      │
│  Glacier IR         │ $0.004     │ $0.03/GB   │ Quarterly access       │
│  Glacier Flexible   │ $0.0036    │ $0.03/GB   │ Annual access (hours)  │
│  Glacier Deep       │ $0.00099   │ $0.02/GB   │ Compliance archive     │
│  Intelligent-Tier   │ $0.0025    │ Varies     │ Unknown access pattern │
│                                                                       │
│  Example: 1 TB of data                                               │
│  Standard:      $23.00/month → $276/year                             │
│  Standard-IA:   $12.50/month → $150/year (save $126)                │
│  Glacier IR:    $4.00/month  → $48/year  (save $228)                │
└──────────────────────────────────────────────────────────────────────┘

---

7. NAT Gateway Cost Reduction

NAT Gateway costs:
  Base: $0.045/hour = ~$32/month per NAT GW
  Data: $0.045/GB processed

Common causes of high NAT costs:
│
├─ S3 access from private subnets
│   └─ Fix: S3 Gateway Endpoint (FREE, no NAT needed)
│
├─ DynamoDB access from private subnets
│   └─ Fix: DynamoDB Gateway Endpoint (FREE)
│
├─ ECR image pulls
│   └─ Fix: ECR VPC Endpoint (~$7.20/month per AZ vs $32 NAT)
│       └─ Need: com.amazonaws.us-east-1.ecr.api
│       └─ Need: com.amazonaws.us-east-1.ecr.dkr
│       └─ Need: com.amazonaws.us-east-1.s3 (gateway, free)
│
├─ CloudWatch Logs
│   └─ Fix: CloudWatch VPC Endpoint (~$7.20/month per AZ)
│
└─ SSM/Secrets Manager
    └─ Fix: SSM VPC Endpoint (~$7.20/month per AZ)

VPC Endpoints Terraform

# S3 Gateway Endpoint (FREE — always set this up)
resource "aws_vpc_endpoint" "s3" {
  vpc_id            = aws_vpc.main.id
  service_name      = "com.amazonaws.us-east-1.s3"
  vpc_endpoint_type = "Gateway"
  route_table_ids   = aws_route_table.private[*].id

  tags = {
    Name = "${local.project}-${local.environment}-s3-endpoint"
  }
}

# DynamoDB Gateway Endpoint (FREE)
resource "aws_vpc_endpoint" "dynamodb" {
  vpc_id            = aws_vpc.main.id
  service_name      = "com.amazonaws.us-east-1.dynamodb"
  vpc_endpoint_type = "Gateway"
  route_table_ids   = aws_route_table.private[*].id

  tags = {
    Name = "${local.project}-${local.environment}-dynamodb-endpoint"
  }
}

# ECR Interface Endpoint (reduces NAT data charges)
resource "aws_vpc_endpoint" "ecr_api" {
  vpc_id              = aws_vpc.main.id
  service_name        = "com.amazonaws.us-east-1.ecr.api"
  vpc_endpoint_type   = "Interface"
  subnet_ids          = aws_subnet.private[*].id
  security_group_ids  = [aws_security_group.vpc_endpoints.id]
  private_dns_enabled = true

  tags = {
    Name = "${local.project}-${local.environment}-ecr-api-endpoint"
  }
}

---

8. Cost Allocation Tags

# Enforce cost allocation tags on all resources
resource "aws_organizations_policy" "require_tags" {
  name        = "require-cost-allocation-tags"
  description = "Enforce cost allocation tagging"
  type        = "TAG_POLICY"

  content = jsonencode({
    tags = {
      Project = {
        tag_key = {
          "@@assign" = "Project"
        }
        enforced_for = {
          "@@assign" = [
            "ec2:instance",
            "ec2:volume",
            "rds:db",
            "s3:bucket",
            "ecs:service",
            "elasticloadbalancing:loadbalancer",
          ]
        }
      }
      Environment = {
        tag_key = {
          "@@assign" = "Environment"
        }
        tag_value = {
          "@@assign" = ["production", "staging", "development"]
        }
      }
    }
  })
}

Required Tags

┌──────────────────────────────────────────────────────────────────────┐
│                  Cost Allocation Tag Standard                         │
│                                                                       │
│  Tag Key      │ Required │ Example Values         │ Purpose           │
│  ──────────────────────────────────────────────────────────────      │
│  Project      │ Yes      │ myapp, website, api    │ Group by product  │
│  Environment  │ Yes      │ production, staging    │ Env cost split    │
│  Service      │ Yes      │ backend, frontend, db  │ Service breakdown │
│  Team         │ Optional │ engineering, platform  │ Team charge-back  │
│  CostCenter   │ Optional │ CC-1234                │ Finance mapping   │
│  ManagedBy    │ Yes      │ terraform, manual      │ Drift detection   │
└──────────────────────────────────────────────────────────────────────┘

---

9. Budget Alerts

resource "aws_budgets_budget" "monthly" {
  name              = "${local.project}-monthly-budget"
  budget_type       = "COST"
  limit_amount      = "500"
  limit_unit        = "USD"
  time_unit         = "MONTHLY"
  time_period_start = "2026-01-01_00:00"

  cost_filter {
    name   = "TagKeyValue"
    values = ["user:Project$${local.project}"]
  }

  notification {
    comparison_operator        = "GREATER_THAN"
    threshold                  = 80
    threshold_type             = "PERCENTAGE"
    notification_type          = "FORECASTED"
    subscriber_email_addresses = ["[email protected]"]
  }

  notification {
    comparison_operator        = "GREATER_THAN"
    threshold                  = 100
    threshold_type             = "PERCENTAGE"
    notification_type          = "ACTUAL"
    subscriber_email_addresses = ["[email protected]", "[email protected]"]
  }

  notification {
    comparison_operator        = "GREATER_THAN"
    threshold                  = 120
    threshold_type             = "PERCENTAGE"
    notification_type          = "ACTUAL"
    subscriber_email_addresses = ["[email protected]", "[email protected]", "[email protected]"]
  }
}

# Anomaly detection
resource "aws_ce_anomaly_monitor" "main" {
  name              = "${local.project}-cost-anomaly-monitor"
  monitor_type      = "DIMENSIONAL"
  monitor_dimension = "SERVICE"
}

resource "aws_ce_anomaly_subscription" "main" {
  name = "${local.project}-cost-anomaly-alerts"

  monitor_arn_list = [aws_ce_anomaly_monitor.main.arn]

  subscriber {
    type    = "EMAIL"
    address = "[email protected]"
  }

  threshold_expression {
    dimension {
      key           = "ANOMALY_TOTAL_IMPACT_ABSOLUTE"
      values        = ["50"]  # Alert if anomaly > $50
      match_options = ["GREATER_THAN_OR_EQUAL"]
    }
  }

  frequency = "DAILY"
}

---

10. Monthly Cost Review Checklist

□ Review Cost Explorer — compare to last month, identify spikes
□ Check Compute Optimizer — apply right-sizing recommendations
□ Check Trusted Advisor — review cost optimization findings
□ Review unattached EBS volumes — delete or snapshot
□ Review unused Elastic IPs — release unattached
□ Review old snapshots — delete beyond retention policy
□ Review ECR images — verify lifecycle policies working
□ Review CloudWatch log retention — ensure policies set
□ Check NAT Gateway data processing — look for VPC endpoint opportunities
□ Review Savings Plans utilization — ensure coverage matches usage
□ Check for staging resources left running — shut down overnight
□ Review data transfer costs — look for cross-region or internet egress

---

11. Common Mistakes / Anti-Patterns

Mistake	Why It's Bad	Fix
No cost allocation tags	Cannot attribute costs to teams/projects	Tag everything with Project, Environment, Service
Buying 3-year RI too early	Locked in if architecture changes	Start with 1-year No Upfront, evaluate
Staging runs 24/7	70% of staging hours are unused	Schedule scaling to 0 outside work hours
No S3 lifecycle policy	Data grows forever, costs increase	Transition to IA after 90 days, Glacier after 365
No budget alerts	Cost spikes go unnoticed for weeks	Set 80%, 100%, 120% budget notifications
Oversized dev instances	Dev doesn't need r6g.xlarge	Use t4g.micro for dev, t4g.small for staging
NAT Gateway for S3 access	Paying $0.045/GB for every S3 call	Use S3 Gateway Endpoint (free)
No ECR lifecycle policy	Old images accumulate indefinitely	Keep last 20 tagged, delete untagged after 7 days
All Upfront RI without analysis	Cash tied up if needs change	Start with No Upfront, upgrade after 6 months
Ignoring data transfer costs	Cross-AZ and internet egress add up	Use CloudFront, VPC endpoints, same-AZ affinity