COST09: How do you manage demand, and supply resources?
Implement strategies to manage workload demand and dynamically supply resources to optimize costs while maintaining performance and availability. Effective demand and supply management ensures you only pay for the resources you need when you need them.
Overview
Managing demand and supply involves understanding workload patterns, implementing mechanisms to control demand when necessary, and dynamically adjusting resource supply to match actual requirements. This approach minimizes waste, reduces costs, and ensures optimal resource utilization while maintaining service quality.
Key Principles
Demand Analysis: Understand workload demand patterns, including peak usage, seasonal variations, and growth trends to inform resource planning and optimization strategies.
Demand Management: Implement mechanisms to manage and control demand through buffering, throttling, queuing, and load balancing to prevent resource over-provisioning.
Dynamic Supply: Automatically adjust resource supply based on actual demand using auto-scaling, serverless architectures, and elastic resource provisioning.
Cost-Performance Balance: Optimize the balance between cost efficiency and performance requirements through intelligent demand and supply management.
Best Practices
COST09-BP01: Perform an analysis on the workload demand
Analyze workload demand patterns, usage trends, and capacity requirements to understand resource needs and identify optimization opportunities for cost-effective resource planning.
COST09-BP02: Implement a buffer or throttle to manage demand
Implement buffering, throttling, and queuing mechanisms to manage demand spikes and prevent resource over-provisioning while maintaining acceptable service levels.
COST09-BP03: Supply resources dynamically
Implement dynamic resource provisioning through auto-scaling, serverless architectures, and elastic resource management to match supply with actual demand in real-time.
Implementation Strategy
1. Analyze Demand Patterns
- Collect and analyze historical usage data and demand patterns
- Identify peak usage periods, seasonal variations, and growth trends
- Understand workload characteristics and resource requirements
- Create demand forecasting models and capacity planning strategies
2. Implement Demand Management
- Deploy buffering and queuing mechanisms for demand smoothing
- Implement throttling and rate limiting to control resource consumption
- Use load balancing and traffic shaping to distribute demand
- Create demand management policies and automated controls
3. Enable Dynamic Supply
- Implement auto-scaling for compute, storage, and database resources
- Deploy serverless architectures for event-driven workloads
- Use elastic resource provisioning and just-in-time allocation
- Create automated resource lifecycle management
4. Monitor and Optimize
- Track demand patterns and resource utilization continuously
- Monitor cost efficiency and performance metrics
- Adjust demand management and supply strategies based on data
- Implement continuous optimization and improvement processes
Demand and Supply Management Patterns
Predictive Scaling: Use historical data and machine learning to predict demand and pre-scale resources proactively.
Reactive Scaling: Automatically scale resources in response to real-time demand changes and performance metrics.
Scheduled Scaling: Scale resources based on known patterns and scheduled events to optimize for predictable demand.
Elastic Architectures: Design architectures that can dynamically expand and contract based on demand without manual intervention.
Demand Shaping: Influence demand patterns through pricing, incentives, and user experience design to optimize resource utilization.
AWS Services to Consider
Common Anti-Patterns
Static Resource Provisioning: Provisioning resources for peak demand without implementing dynamic scaling, leading to waste during low-demand periods.
Ignoring Demand Patterns: Not analyzing demand patterns and usage trends, missing opportunities for optimization and cost reduction.
Over-Aggressive Scaling: Scaling too quickly or frequently, causing resource thrashing and increased costs without performance benefits.
Lack of Demand Management: Not implementing buffering or throttling mechanisms, leading to resource over-provisioning to handle spikes.
Manual Resource Management: Relying on manual processes for resource scaling instead of implementing automated demand and supply management.
Success Metrics
- Resource Utilization: Average utilization rates across different resource types
- Cost Efficiency: Cost per unit of work or transaction processed
- Demand Response Time: Time to scale resources in response to demand changes
- Service Level Achievement: Percentage of time service levels are met during demand variations
- Waste Reduction: Reduction in idle or underutilized resources