Compute Purchasing Models & Optimization
AWS offers flexible compute purchasing models that allow businesses like SecureCart to balance cost, scalability, and performance. By understanding and optimizing compute purchasing strategies, SecureCart can minimize costs while ensuring high availability and responsiveness.
✔ Why SecureCart Needs Compute Purchasing Optimization?
Ensures the best pricing model for each workload.
Reduces long-term infrastructure costs through reserved pricing and spot instances.
Balances cost savings with performance and availability.
Utilizes cost management tools to monitor and optimize spending.
🔹 Step 1: Understanding AWS Compute Purchasing Models
AWS offers multiple pricing models that allow businesses to choose the most cost-effective compute option based on workload characteristics.
Purchasing Model
Best Use Case
Cost Optimization Strategy
SecureCart Use Case
On-Demand Instances
Short-lived, unpredictable workloads.
No long-term commitment, pay for compute per second.
Used for SecureCart’s ad-hoc development/testing instances.
Reserved Instances (RIs)
Steady-state workloads with predictable demand.
1-3 year commitment for up to 72% discount.
Used for SecureCart’s always-on payment processing APIs.
Spot Instances
Flexible, fault-tolerant workloads (e.g., batch jobs, analytics).
Up to 90% discount, but instances may be interrupted.
Used for SecureCart’s batch data processing tasks.
Savings Plans
Predictable compute usage across EC2, Fargate, and Lambda.
Up to 66% discount, flexible across services.
Used for SecureCart’s containerized workloads.
Dedicated Hosts
Compliance-driven workloads requiring physical servers.
Reduce licensing costs for BYOL (Bring Your Own License).
Used for SecureCart’s regulatory workloads.
✅ Best Practices: ✔ Use On-Demand for unpredictable workloads but avoid long-term use. ✔ Reserve instances for stable, long-running services. ✔ Leverage Spot Instances for batch and stateless workloads. ✔ Use Savings Plans instead of RIs for greater flexibility.
🔹 Step 2: Cost Optimization Strategies for Compute Workloads
✔ SecureCart optimizes compute spending by using the right pricing model for each workload.
Workload Type
Optimized Pricing Model
Cost Optimization Strategy
Frontend APIs
On-Demand / Reserved Instances
Use Auto Scaling to right-size resources.
Backend Microservices
Savings Plans / Fargate
Use containers to reduce EC2 costs.
Batch Jobs (Analytics, Reporting)
Spot Instances / AWS Batch
Run Spot Instances for batch workloads at lower cost.
CI/CD Pipelines
EC2 Spot Instances / Lambda
Use Spot Instances or serverless for build jobs.
✅ Best Practices: ✔ Use Auto Scaling to scale workloads dynamically and avoid over-provisioning. ✔ Run Lambda or Fargate for workloads that don’t need persistent instances. ✔ Schedule non-production instances to shut down during off-peak hours.
🔹 Step 3: Comparing Reserved Instances vs. Savings Plans
Feature
Reserved Instances (RIs)
Savings Plans
Discounts
Up to 72% savings on EC2
Up to 66% savings on EC2, Lambda, and Fargate
Commitment
1-3 years
1-3 years
Flexibility
Locked to instance family, region
Applies across different services
Best for
Predictable, steady workloads
Mixed compute usage (EC2, Fargate, Lambda)
✅ Best Practices: ✔ Use Reserved Instances for stable, single-instance family workloads. ✔ Use Compute Savings Plans to cover multiple compute services. ✔ Convert Convertible RIs to adjust to changing workload needs.
🔹 Step 4: Optimizing EC2 Instance Selection
AWS provides a wide variety of EC2 instance types that businesses can optimize for cost, memory, compute, and storage.
Instance Type
Optimized For
Use Case
SecureCart Implementation
T-Series (Burstable, T3, T4g)
Cost-efficient for low CPU usage
Development & testing environments
Runs SecureCart’s dev/test instances.
M-Series (General Purpose, M6i, M7g)
Balanced compute, memory, and storage
Backend APIs, microservices
Hosts SecureCart’s backend services.
C-Series (Compute Optimized, C6i, C7g)
High CPU workloads
High-performance analytics, machine learning
Processes SecureCart’s recommendation models.
R-Series (Memory Optimized, R6i, R7g)
Memory-intensive workloads
In-memory databases, caching
Runs SecureCart’s Redis caching layer.
✅ Best Practices: ✔ Use T-Series instances for development and non-critical workloads. ✔ Use M-Series for general workloads with a balance of performance and cost. ✔ Use C-Series for compute-intensive workloads that need high processing power. ✔ Use R-Series for workloads that require large amounts of memory.
🔹 Step 5: Monitoring & Managing Compute Costs
✔ SecureCart continuously monitors compute costs and performance using AWS tools.
AWS Cost Optimization Tool
Purpose
SecureCart Implementation
AWS Cost Explorer
Tracks compute usage and spending trends.
Analyzes SecureCart’s EC2 cost trends.
AWS Compute Optimizer
Recommends right-sizing for compute resources.
Helps SecureCart reduce underutilized EC2 costs.
AWS Trusted Advisor
Identifies cost-saving opportunities.
Detects idle EC2 instances SecureCart can terminate.
AWS Budgets
Sets cost alerts for compute usage.
Prevents SecureCart from exceeding spending limits.
✅ Best Practices: ✔ Use AWS Compute Optimizer to right-size EC2 instances. ✔ Enable AWS Cost Explorer to analyze compute cost trends. ✔ Set AWS Budgets to track and control compute spending.
🚀 Summary
✔ Choose the best compute pricing model (On-Demand, Reserved, Spot, Savings Plans) based on workload needs. ✔ Use Auto Scaling, Lambda, and Fargate to optimize compute resource utilization. ✔ Leverage Reserved Instances or Savings Plans for predictable, long-term workloads. ✔ Use EC2 Spot Instances for batch, analytics, and other fault-tolerant workloads. ✔ Monitor and optimize compute spending using AWS Cost Explorer, Budgets, and Compute Optimizer.
Scenario:
SecureCart needs to reduce long-term compute costs by using Spot Instances, Reserved Instances, and Compute Savings Plans.
Key Learning Objectives:
✅ Use Spot Instances for fault-tolerant and flexible workloads ✅ Implement Reserved Instances for steady-state workloads ✅ Apply Compute Savings Plans for cost efficiency
Hands-on Labs:
1️⃣ Deploy an EC2 Spot Instance Fleet for Batch Processing 2️⃣ Purchase and Manage Reserved Instances for a Production Workload 3️⃣ Implement Compute Savings Plans to Reduce Long-Term Compute Costs
🔹 Outcome: SecureCart reduces compute expenses by using the right AWS purchasing model.
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