Architecting a 3-Tier Application on AWS VPC with ASG, ELB, and AI-Driven Backup Plan: Design and deploy a highly available 3-tier application on AWS using VPC, ALB, and ASGs. Integrate AI-powered monitoring tools for predictive scaling and anomaly detection. Use AI-based backup automation tools to ensure smart backup scheduling and quick disaster recovery based on usage patterns and criticality analysis.

Automating Deployment of MERN Stack on AWS App Runner with AWS CodePipeline & AI Testing: Automate the deployment of a MERN stack application using AWS CodePipeline and AWS App Runner. Integrate AI-based code review bots, and automated UI testing frameworks powered by computer vision. Use tools like Diffblue or ReTest to enhance unit test coverage automatically using AI.

Dockerized Microservices on Kubernetes: CI/CD with Jenkins, GitHub & AI Observability : Build and deploy a Dockerized microservices architecture on Kubernetes. Automate the CI/CD process using Jenkins and GitHub. Integrate AI/ML-driven observability platforms like Prometheus + Grafana with ML plugins, or Dynatrace Davis AI for real-time insights, intelligent alerting, and automated root cause analysis.

AI-Optimized OTT Platform: Scaling for Millions : Develop and deploy an OTT platform that supports millions of concurrent users. Utilize AI/ML for user behavior analytics, content recommendation engines, and dynamic load prediction. Implement AI-based autoscaling to optimize infrastructure usage and control costs, ensuring high availability with minimal manual intervention.