Task Statement 3.2: Design High-Performing and Elastic Compute Solutions

📌 Task Statement 3.2: Design High-Performing and Elastic Compute Solutions

This study group focuses on designing scalable, high-performing, and elastic compute architectures that dynamically adjust to workload demands while maintaining cost efficiency.

We will follow SecureCart, an e-commerce platform, as they optimize their compute workloads, transition to event-driven compute solutions, and explore containerized and serverless architectures.

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📅 Study Group Agenda

Week	Topic	Key AWS Services
Week 1	AWS Compute Services & Use Cases	EC2, Fargate, Lambda, AWS Batch
Week 2	Elastic & Auto-Scaling Compute Architectures	EC2 Auto Scaling, AWS Auto Scaling
Week 3	Decoupling Workloads for Performance	SQS, SNS, EventBridge, Step Functions
Week 4	Serverless & Containerized Compute Solutions	AWS Lambda, AWS Fargate, ECS, EKS
Week 5	Compute Optimization & Cost Efficiency	Right-Sizing EC2, Compute Savings Plans, Spot Instances
Week 6	Hands-on Labs & Final Challenge	Implementing a High-Performance AWS Compute Solution

Final Study Group Summary

Week	Focus Area	Outcome
Week 1	AWS Compute Services & Use Cases	Select the Best Compute Service for Workloads
Week 2	Elastic & Auto-Scaling Architectures	Implement Auto Scaling for Compute Resources
Week 3	Decoupling Workloads for Performance	Use SQS, SNS, & EventBridge for Scalable Systems
Week 4	Serverless & Containerized Compute	Deploy Lambda, Fargate, ECS, & EKS
Week 5	Compute Optimization & Cost Efficiency	Optimize EC2, Lambda, & Compute Costs
Week 6	Hands-on Scenarios	Implement a Scalable Compute Solution

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🚀 Next Steps

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