Task Statement 4.2: Design Cost-Optimized Compute Solutions

This study group will explore how to design cost-efficient compute architectures in AWS by leveraging auto-scaling, serverless computing, purchasing options (Spot, Reserved, and Savings Plans), hybrid computing, and AWS cost management tools.

We will follow SecureCart, an e-commerce platform, as they optimize their compute resources, reduce costs, and ensure performance at scale.

---

📅 Study Group Agenda

Week	Topic	Key AWS Services
Week 1	AWS Compute Options & Cost Management Tools	Amazon EC2, AWS Lambda, AWS Fargate, AWS Cost Explorer, AWS Budgets
Week 2	Compute Purchasing Models & Optimization	Spot Instances, Reserved Instances, Savings Plans
Week 3	Scaling Strategies for Cost Efficiency	Auto Scaling Groups, Elastic Load Balancing, EC2 Hibernation
Week 4	Serverless & Container-Based Cost Optimization	AWS Lambda, AWS Fargate, Amazon ECS, Amazon EKS
Week 5	Hybrid & Edge Compute Cost Strategies	AWS Outposts, AWS Snowball Edge, AWS Wavelength
Week 6	Hands-on Labs & Final Challenge	Implementing a Cost-Optimized AWS Compute Solution

---

Final Study Group Summary

Week	Focus Area	Outcome
Week 1	AWS Compute Options & Cost Management	Select the Most Cost-Effective AWS Compute Services
Week 2	Compute Purchasing Models	Optimize Compute Costs Using Spot, Reserved, & Savings Plans
Week 3	Scaling Strategies	Reduce Compute Costs with Auto Scaling & Load Balancing
Week 4	Serverless & Containers	Optimize Costs Using Lambda, Fargate, ECS, & EKS
Week 5	Hybrid & Edge Compute	Implement Hybrid & Edge Compute Solutions with AWS Outposts & Snowball
Week 6	Hands-on Scenarios	Deploy a Cost-Optimized Compute Solution

---

🚀 Next Steps

Would you like: ✅ Terraform automation scripts for AWS compute cost optimization? ✅ Scenario-based quizzes for each study group session? ✅ Instructor-led deep-dive discussions?