Cost Optimization Strategies

Cost optimization is a key differentiator for cloud architects. Interviewers expect you to balance performance, reliability, and cost effectively.

AWS Pricing Models

Compute Pricing Options

Model	Discount	Commitment	Best For
On-Demand	0%	None	Variable workloads
Savings Plans	Up to 72%	1-3 years	Predictable compute
Reserved Instances	Up to 72%	1-3 years	Specific instances
Spot Instances	Up to 90%	None	Fault-tolerant workloads

Savings Plans vs Reserved Instances

Aspect	Savings Plans	Reserved Instances
Flexibility	Any instance family	Specific instance type
Region	Region-flexible (Compute SP)	Region-specific
Service	EC2, Lambda, Fargate	EC2, RDS only
Management	Simpler	More complex
Recommendation	Modern choice	Legacy workloads

Interview Question: Cost Strategy

Q: "Design a cost optimization strategy for a variable workload with a predictable baseline."

A: Hybrid approach:

Workload Analysis:
├── Baseline: 100 instances (consistent)
├── Peak: 300 instances (variable)
└── Fault-tolerant batch: 50 instances

Cost Strategy:
├── Baseline (100): Compute Savings Plan (3-year)
│   └── 66% savings
├── Variable (0-200): On-Demand + Spot mix
│   ├── Critical: On-Demand
│   └── Non-critical: Spot (70/30 mix)
└── Batch (50): Spot Instances
    └── Up to 90% savings

Expected Savings: 45-55% compared to all On-Demand.

Right-Sizing

Analysis Process

1. Collect Metrics (2-4 weeks minimum)

   • CPU utilization
   • Memory usage
   • Network throughput
   • Storage IOPS

2. Identify Candidates

   • Average CPU < 40%: Downsize
   • CPU consistently > 80%: Upsize
   • Memory-bound: Consider memory-optimized

3. Test and Validate

   • Load test new size
   • Monitor for 1-2 weeks
   • Rollback plan ready

AWS Tools for Right-Sizing

Tool	Function	Cost
Cost Explorer	Right-sizing recommendations	Free
Compute Optimizer	ML-based recommendations	Free (basic)
Trusted Advisor	Instance recommendations	Business/Enterprise

Interview Question: Right-Sizing RDS

Q: "Your RDS database is consistently at 20% CPU. What's your recommendation?"

A: Don't immediately downsize. Analyze holistically:

1. Check Memory Pressure

   • Low CPU doesn't mean oversized
   • Database may be memory-bound

2. Analyze Query Patterns

   • Peak vs average utilization
   • Batch job timing

3. Consider Buffer Pool

   • Larger instance = more cache
   • May improve performance significantly

4. Recommendation

   • If memory and IOPS also low: Downsize
   • If memory high: Stay or switch to memory-optimized
   • Test thoroughly before production change

Storage Optimization

S3 Storage Classes

Class	Access Pattern	Cost (per GB)	Retrieval
Standard	Frequent	$$$	Instant
Intelligent-Tiering	Variable	$$$ + monitoring	Instant
Standard-IA	Infrequent (30+ days)	$$	Instant
One Zone-IA	Infrequent, non-critical	$	Instant
Glacier Instant	Archive, instant access	$	Instant
Glacier Flexible	Archive	¢	Minutes-hours
Glacier Deep Archive	Long-term archive	¢	Hours

S3 Lifecycle Policies

Lifecycle Rules:
  - Transition to Standard-IA: 30 days
  - Transition to Glacier: 90 days
  - Transition to Deep Archive: 365 days
  - Delete: 7 years (compliance)

EBS Optimization

Volume Type	Use Case	Cost Consideration
gp3	General purpose	20% cheaper than gp2
io2	High IOPS	Pay for provisioned IOPS
st1	Throughput	Cheaper for sequential
sc1	Cold storage	Cheapest block storage

Quick Win: Migrate gp2 to gp3 for immediate 20% savings with same or better performance.

Data Transfer Costs

Transfer Cost Matrix

From	To	Cost
Internet	AWS	Free
AWS	Internet	$0.09/GB (first 10TB)
Same Region (AZ to AZ)		$0.01/GB
Cross-Region		$0.02/GB
VPC Peering (same region)		$0.01/GB
PrivateLink		$0.01/GB + hourly

Cost Reduction Strategies

1. Use VPC Endpoints

   • S3 Gateway endpoint: Free
   • Avoid NAT Gateway data processing

2. Regional Deployment

   • Keep compute near data
   • Multi-region only when required

3. CloudFront for Egress

   • Often cheaper than direct egress
   • Additional caching benefits

4. Compression

   • Compress data before transfer
   • Significant savings for text/logs

Interview Question: Data Transfer

Q: "Your monthly data egress is $50,000. How would you reduce it?"

A: Multi-pronged approach:

Strategy	Potential Savings
CloudFront distribution	20-40%
Response compression	30-50%
Caching headers	20-30%
Regional endpoints	10-20%
S3 Transfer Acceleration review	Variable

Action Plan:

1. Analyze CloudWatch for transfer patterns
2. Implement CloudFront for repeat requests
3. Enable gzip/brotli compression
4. Review API response sizes
5. Consider reserved capacity for predictable egress

FinOps Practices

Cost Allocation

1. Tagging Strategy

   • Mandatory: Environment, Owner, Project, CostCenter
   • Enforce via SCP or AWS Config

2. AWS Organizations

   • Separate accounts by business unit
   • Consolidated billing
   • Reserved capacity sharing

Monitoring and Governance

Tool	Purpose
AWS Budgets	Alerts and forecasting
Cost Anomaly Detection	ML-based anomaly alerts
Cost Explorer	Analysis and reporting
Savings Plans recommendations	Purchase guidance

Chargeback Model

Central IT Budget
    ↓
Cost Allocation Tags
    ↓
Monthly Reports per Team
    ↓
Business Unit Chargeback

Key Insight: Cost optimization is continuous, not one-time. Implement automated policies, regular reviews, and team accountability to maintain efficiency as workloads evolve.

Next, we'll explore the AWS Well-Architected Framework. :::