# Hands-on Labs & Final Challenge

#### **Scenario:**

SecureCart’s engineering team must **implement a cost-optimized AWS compute solution** balancing **performance, scalability, and cost efficiency**.

#### **Final Study Group Challenges:**

✅ **Scenario 1:** Select the Most Cost-Effective AWS Compute Service for a Given Workload\
✅ **Scenario 2:** Implement Auto Scaling to Reduce Compute Costs During Low Traffic Periods\
✅ **Scenario 3:** Optimize Compute Purchasing Using Spot Instances & Reserved Instances\
✅ **Scenario 4:** Deploy a Serverless Architecture Using AWS Lambda & Fargate\
✅ **Scenario 5:** Extend AWS Compute to Hybrid & Edge Environments Using AWS Outposts

🔹 **Outcome:** Learners **demonstrate AWS best practices for cost-optimized compute architectures**.

***

### **📚 Recommended Study Resources**

✅ **AWS Well-Architected Framework – Cost Optimization Pillar**\
✅ **AWS Compute Optimization Best Practices**\
✅ **AWS Cost Explorer & AWS Budgets for Compute Cost Management**\
✅ **AWS Auto Scaling & Load Balancing Strategies**\
✅ **AWS Savings Plans & Spot Instances for Cost Reduction**


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