AWS DevOps Infrastructure Automation -- 2

I need my existing AWS account transformed into a fully automated, production-ready environment. The goal is to design the architecture, configure every layer, and then codify it so that future changes are repeatable and version-controlled. Scope of work • Architect an environment that reliably runs our web applications, data-processing jobs, and upcoming machine-learning models on EC2 with persistent storage on S3. • Build an Infrastructure as Code baseline (Terraform or CloudFormation) that provisions VPC, subnets, security groups, EC2 launch templates, Auto Scaling groups, Application Load Balancers, and the supporting IAM roles and policies. • Automate the entire deployment process through a CI/CD pipeline (GitHub Actions, CodePipeline, or similar) so that pushing to the main branch promotes all services through staging to production without manual steps. • Implement dynamic scaling and load-balancing rules to keep response times low while optimising cost. • Wire in centralised logging and metrics to CloudWatch (or an equivalent open-source stack) and set sensible alarms for CPU, memory, 5xx rates, and custom business KPIs. Deliverables 1. Source-controlled IaC repository with clear README. 2. Pipeline configuration files and minimal documentation showing how to trigger deployments. 3. Diagram of the final architecture. 4. One-hour hand-off call or recorded walkthrough demo. Acceptance criteria – Running terraform/apply (or the CloudFormation stack) from a clean account produces the same environment described. – A single commit can push an updated container image all the way to production with zero downtime. – Auto Scaling adds and removes EC2 instances based on a sample load test. – CloudWatch (or chosen stack) raises an alert when thresholds are breached. If this is clear, tell me which IaC toolkit and CI/CD stack you prefer and why you think it fits best here.