COST05-BP03: Perform a thorough analysis of each component
Conduct detailed analysis of individual workload components to understand their cost characteristics, performance requirements, and optimization opportunities. Thorough component analysis enables informed decisions about service selection and configuration.
Implementation guidance
Detailed component analysis involves examining each workload component individually to understand its specific requirements, cost drivers, usage patterns, and potential alternatives. This analysis forms the foundation for making informed service selection decisions.
Component Analysis Framework
Functional Analysis: Understand what each component does, its role in the overall workload, and its specific functional requirements.
Performance Analysis: Analyze performance characteristics including throughput, latency, availability, and scalability requirements.
Cost Analysis: Examine current costs, cost drivers, and how costs change with different usage patterns and configurations.
Alternative Evaluation: Identify and evaluate alternative services or configurations that could meet the same requirements.
Analysis Dimensions
Technical Requirements: CPU, memory, storage, network, and other technical specifications needed for optimal performance.
Business Requirements: Availability, compliance, security, and other business-driven requirements that affect service selection.
Usage Patterns: How the component is used over time, including peak and average loads, seasonal variations, and growth trends.
Integration Requirements: How the component integrates with other parts of the workload and external systems.
AWS Services to Consider
Implementation Steps
1. Define Analysis Scope
- Identify components to be analyzed
- Define analysis criteria and objectives
- Establish success metrics and evaluation criteria
- Set timeline and resource allocation for analysis
2. Gather Component Data
- Collect performance and utilization metrics
- Analyze cost data and trends
- Document current configurations and settings
- Identify usage patterns and requirements
3. Evaluate Current State
- Assess current performance against requirements
- Identify gaps and inefficiencies
- Calculate current total cost of ownership
- Document findings and observations
4. Identify Alternatives
- Research alternative services and configurations
- Evaluate managed vs. self-managed options
- Consider different pricing models and options
- Assess migration complexity and costs
5. Perform Comparative Analysis
- Compare alternatives against current state
- Evaluate trade-offs between cost, performance, and features
- Calculate total cost of ownership for each option
- Assess risks and benefits of each alternative
6. Make Recommendations
- Prioritize recommendations based on impact and effort
- Document rationale and supporting analysis
- Create implementation roadmap and timeline
- Establish success metrics and monitoring plan
Component Analysis Framework
Detailed Component Analyzer
Analysis Templates and Frameworks
Component Analysis Report Template
Common Challenges and Solutions
Challenge: Incomplete Performance Data
Solution: Implement comprehensive monitoring and observability. Use multiple data sources and extend monitoring periods. Consider application-level metrics in addition to infrastructure metrics.
Challenge: Complex Cost Attribution
Solution: Use detailed tagging strategies and cost allocation methods. Implement resource-level cost tracking. Use AWS Cost and Usage Reports for granular cost analysis.
Challenge: Evaluating Trade-offs Between Options
Solution: Use multi-criteria decision analysis with weighted scoring. Create standardized evaluation frameworks. Consider total cost of ownership, not just direct costs.
Challenge: Keeping Analysis Current
Solution: Implement automated analysis and monitoring. Set up regular review cycles. Use alerts and notifications for significant changes in usage patterns.
Challenge: Analyzing Interdependent Components
Solution: Consider system-level impacts when analyzing individual components. Use dependency mapping and impact analysis. Test changes in isolated environments first.