COST06: How do you meet cost targets when you select resource type, size and number?

Ensure that you choose the appropriate resource type, size, and number of resources for your workload to meet cost targets. Use data-driven approaches, cost modeling, and load testing to make informed decisions about resource selection and sizing.

Overview

Meeting cost targets when selecting resources requires a systematic approach that combines cost modeling, data-driven decision making, automated optimization, and performance validation. This involves understanding your workload requirements, modeling different resource configurations, and continuously optimizing based on actual usage patterns and performance metrics.

Key Principles

Data-Driven Decisions: Base resource selection on actual usage data, performance metrics, and cost analysis rather than assumptions or over-provisioning for worst-case scenarios.

Cost Modeling: Use comprehensive cost models that account for all cost components including compute, storage, network, and operational overhead to make informed resource selection decisions.

Automated Optimization: Implement automated systems that can adjust resource type, size, and number based on real-time metrics and predefined cost targets.

Performance Validation: Use load testing and performance monitoring to validate that selected resources meet both cost targets and performance requirements.

Best Practices

COST06-BP01: Perform cost modeling

Create comprehensive cost models that help you understand the cost implications of different resource configurations and make informed decisions about resource selection to meet cost targets.

COST06-BP02: Select resource type, size, and number based on data

Use actual usage data, performance metrics, and workload characteristics to make informed decisions about resource type, size, and number rather than relying on assumptions or over-provisioning.

COST06-BP03: Select resource type, size, and number automatically based on metrics

Implement automated systems that can dynamically adjust resource configurations based on real-time metrics, cost targets, and performance requirements.

COST06-BP04: Load test your workload

Use load testing to validate that your selected resource configurations can meet performance requirements while staying within cost targets under various load conditions.

Implementation Strategy

1. Establish Cost Modeling Framework

Create comprehensive cost models for different resource types
Include all cost components (compute, storage, network, operational)
Model different usage scenarios and growth patterns
Validate models against actual costs regularly

2. Implement Data Collection

Set up comprehensive monitoring and metrics collection
Gather usage patterns, performance data, and cost information
Create data pipelines for analysis and decision making
Establish baselines and benchmarks for comparison

3. Develop Automated Optimization

Implement auto-scaling based on cost and performance metrics
Create policies for automated resource selection and sizing
Set up alerts and notifications for cost target deviations
Build feedback loops for continuous optimization

4. Establish Testing and Validation

Create comprehensive load testing frameworks
Test different resource configurations under various conditions
Validate cost and performance trade-offs
Document findings and optimization opportunities

AWS Services to Consider

AWS Pricing Calculator

Model costs for different resource configurations and scenarios. Use the calculator to understand cost implications of different resource choices and optimize for cost targets.

AWS Compute Optimizer

Get rightsizing recommendations based on actual usage data. Use Compute Optimizer to identify optimal resource types and sizes for your workloads.

Amazon CloudWatch

Monitor resource utilization and performance metrics. Use CloudWatch data to make informed decisions about resource sizing and optimization.

AWS Auto Scaling

Automatically adjust resource capacity based on demand and cost targets. Use Auto Scaling to optimize resource usage and costs dynamically.

AWS Cost Explorer

Analyze cost trends and patterns to inform resource selection decisions. Use Cost Explorer to understand the cost impact of different resource configurations.

AWS Load Testing Solutions

Test workload performance under different load conditions. Use load testing to validate resource configurations and optimize for cost-performance balance.

Common Anti-Patterns

Over-provisioning for Peak: Provisioning resources for peak load without considering cost optimization strategies like auto-scaling or spot instances.

Assumption-Based Sizing: Making resource selection decisions based on assumptions rather than actual data and performance requirements.

Ignoring Cost in Performance Testing: Focusing only on performance metrics during testing without considering cost implications of different resource configurations.

Static Resource Allocation: Using fixed resource allocations without implementing dynamic optimization based on changing requirements and usage patterns.

Incomplete Cost Modeling: Creating cost models that don’t account for all cost components or fail to consider operational and indirect costs.

Success Metrics

Cost Target Achievement: Percentage of workloads meeting defined cost targets
Resource Utilization: Average utilization rates across different resource types
Cost per Transaction: Cost efficiency metrics for business transactions
Rightsizing Accuracy: Percentage of resources that are appropriately sized
Automated Optimization Coverage: Percentage of resources under automated optimization