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.

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🔹 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.

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🔹 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.

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🔹 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.

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🔹 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.

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🔹 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.

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🚀 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.