Compute Optimization & Cost Efficiency

AWS offers multiple compute options, and optimizing compute resources is essential for achieving cost efficiency, scalability, and high performance. SecureCart must ensure its compute infrastructure is optimized to handle demand fluctuations while minimizing unnecessary costs.

✔ Why does SecureCart need compute optimization & cost efficiency?

• Avoids over-provisioning compute resources, reducing costs.

• Ensures workloads run efficiently without unnecessary latency.

• Utilizes auto-scaling to adjust compute capacity dynamically.

• Maximizes AWS pricing models to optimize spending.

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🔹 Step 1: Understanding Compute Optimization Strategies

✔ Compute optimization is about balancing performance and cost by selecting the right instance types, scaling strategies, and pricing models.

Optimization Strategy	Definition	SecureCart Use Case
Right-Sizing Instances	Selecting the appropriate compute resources for workload demands.	Using Graviton-based instances for better price-performance.
Auto-Scaling	Dynamically adjusts compute resources based on demand.	Expanding checkout services during high traffic periods.
Compute Pricing Optimization	Using the best pricing model (On-Demand, Reserved, Spot).	Using Spot Instances for non-critical background tasks.
Efficient Workload Distribution	Load balancing and workload segmentation.	Distributing product catalog queries across optimized instance types.

✅ Best Practices: ✔ Right-size instances by monitoring CPU, memory, and I/O usage. ✔ Use auto-scaling to handle demand fluctuations dynamically. ✔ Utilize Spot Instances and Savings Plans to reduce costs.

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🔹 Step 2: Choosing the Right AWS Compute Services

✔ AWS provides multiple compute services that offer different cost-saving benefits:

AWS Compute Service	Cost Efficiency Strategy	SecureCart Implementation
Amazon EC2	Use right-sizing and Reserved Instances for predictable workloads.	Runs SecureCart’s backend services and order management system.
Amazon EC2 Auto Scaling	Scale instances dynamically based on traffic patterns.	Handles traffic spikes during flash sales.
AWS Lambda	Pay-per-execution with no idle costs.	Processes checkout transactions efficiently.
AWS Fargate	Serverless containers with automatic scaling.	Manages SecureCart’s product search service.
Amazon ECS/EKS	Optimize container workloads with Spot Instances and cluster scaling.	Runs SecureCart’s AI-based recommendation engine.

✅ Best Practices: ✔ Use EC2 Reserved Instances for predictable, long-term workloads. ✔ Leverage Lambda for event-driven processing to minimize idle costs. ✔ Use Fargate for containerized workloads that don’t require dedicated EC2 instances.

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🔹 Step 3: AWS Compute Pricing Models & Cost-Saving Strategies

✔ AWS offers different pricing models that help optimize costs:

Pricing Model	Best For	SecureCart Implementation
On-Demand Instances	Short-term workloads with unpredictable usage.	Handles real-time order processing.
Spot Instances	Non-critical, interruptible workloads at a lower price.	Runs SecureCart’s background analytics jobs.
Reserved Instances (RIs)	Long-term workloads with predictable usage.	Supports SecureCart’s web servers with a 1-year RI commitment.
Savings Plans	Flexible compute savings over a 1-3 year period.	Optimizes SecureCart’s general compute costs.

✅ Best Practices: ✔ Use On-Demand for short-term workloads. ✔ Utilize Spot Instances for fault-tolerant workloads. ✔ Adopt Savings Plans for steady-state workloads to maximize cost efficiency.

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🔹 Step 4: Optimizing Compute Performance & Utilization

✔ AWS provides tools and strategies to improve compute efficiency and reduce wastage:

Optimization Method	Purpose	SecureCart Implementation
Compute Optimizer	Recommends right-sized EC2 instances based on usage.	Suggests M6g instead of M5 for cost efficiency.
Graviton-Based Instances	Uses ARM-based instances for better price-performance.	Switching SecureCart’s web API from x86 to Graviton.
Auto Scaling Policies	Ensures optimal compute capacity.	Adjusts checkout service instances dynamically.
Instance Scheduling	Turns off unused instances during non-peak hours.	Shuts down development environments at night.

✅ Best Practices: ✔ Enable Compute Optimizer to identify underutilized instances. ✔ Leverage AWS Graviton-based instances for performance gains. ✔ Use instance scheduling to stop unused instances.

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🔹 Step 5: Cost Optimization for Serverless & Containers

✔ Why? – SecureCart reduces compute costs by optimizing serverless and containerized workloads.

✔ Cost-Optimization Strategies for AWS Serverless & Containers:

Optimization Method	Purpose	SecureCart Implementation
Provisioned Concurrency for Lambda	Reduces cold-start latency for critical functions.	Ensures checkout processing remains fast.
Spot Instances for ECS/EKS	Saves costs on non-critical containerized workloads.	Runs AI model training at lower costs.
Savings Plans for Fargate	Reduces costs for predictable container workloads.	Optimizes SecureCart’s product search service.

✅ Best Practices: ✔ Use Provisioned Concurrency for Lambda functions that require low latency. ✔ Leverage Spot Instances for ECS/EKS workloads that can tolerate interruptions. ✔ Adopt Savings Plans for steady-state workloads running on Fargate.

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🔹 Step 6: Monitoring & Cost Analysis for Compute Efficiency

✔ Why? – SecureCart tracks compute costs and optimizes infrastructure for maximum efficiency.

✔ AWS Cost Monitoring Tools for Compute Optimization:

Monitoring Tool	Purpose	SecureCart Use Case
AWS Cost Explorer	Analyzes compute cost trends and usage.	Identifies cost spikes in compute resources.
AWS Budgets	Sets cost limits and alerts for exceeding budgets.	Prevents unexpected compute overages.
AWS Compute Optimizer	Recommends optimal instance types.	Suggests cost-efficient alternatives for workloads.
AWS Trusted Advisor	Provides cost-saving recommendations.	Detects underutilized instances in SecureCart’s environment.

✅ Best Practices: ✔ Use Cost Explorer to track cost trends and optimize spending. ✔ Set budgets and alerts to prevent unexpected costs. ✔ Regularly review Compute Optimizer recommendations for right-sizing.

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🚀 Summary

✔ Use AWS auto-scaling and compute right-sizing to dynamically adjust capacity. ✔ Leverage Spot Instances, Reserved Instances, and Savings Plans to reduce costs. ✔ Monitor compute costs using Cost Explorer, Budgets, and Compute Optimizer. ✔ Optimize Lambda, Fargate, and containerized workloads for cost efficiency. ✔ Use Graviton-based instances for better price-performance ratios.

Scenario:

SecureCart must optimize compute costs while maintaining scalability and performance.

Key Learning Objectives:

✅ Use Compute Savings Plans & EC2 Spot Instances ✅ Right-size EC2 instances & Lambda memory allocations ✅ Optimize serverless function execution with cost-efficient architectures

Hands-on Labs:

1️⃣ Use AWS Compute Optimizer to Right-Size EC2 Instances 2️⃣ Deploy Spot Instances & Compare Cost Savings 3️⃣ Optimize AWS Lambda Costs Using Memory & Execution Tuning

🔹 Outcome: SecureCart reduces compute costs while maintaining scalability.