20-Week Real-World Project based AWS DevOps Bootcamp

Complete Hands-on Bootcamp with Advanced Real-World Projects, real production context, implementations, and live troubleshooting.

• Topic covered: Cloud, DevOps, AIops, DevSecOps, SRE
• Format: Live sessions, 150 min duration.
• Tools used: AWS, Terraform, Docker, Linux, Kubernetes, ArgoCD, Helm, Github Actions, Python, Prometheus, Grafana, Loki, Postgres, Ansible, and other modern DevOps tools
• Target Audience: Those who want to learn how a DevOps engineer builds things in the real world
• Prerequisite: Basic understanding of Linux, AWS
• All classes will be live classes, and they will also be recorded
• The recording will be shared along with notes, assignments, resources, and other relevant materials. Lifetime access to recordings.
• Group Chat on WhatsApp and Discord for all communications, discussions, and troubleshooting during bootcamp

Module 1: Foundation Skills – Linux, Shell Scripting, AWS & Docker (Classes 1-5)

Class 1: Linux and Shell Scripting Fundamentals

• Linux command-line essentials, file permissions, process management, and system monitoring
• Variables, loops, conditionals, functions in bash scripting, and input/output redirection
• Project: Create comprehensive system information script

Class 2: Advanced Shell Scripting for DevOps Automation

• Log Monitor Script: Real-time log monitoring with email alerts for HTTP 500 errors
• System Monitor Script: Automated metrics collection with report generation and Container Monitor Script for performance monitoring Project: Create automated backup and disk cleanup scripts

Class 3: AWS Fundamentals

• AWS account setup, security best practices, IAM fundamentals, and core services (EC2, VPC, Security Groups, Load Balancers)
• AWS CLI configuration, basic automation, and cost management basics
• Project: Deploy personal portfolio website with proper AWS architecture

Class 4: Docker Fundamentals and Best Practices

• Docker architecture, multi-stage builds, Docker Compose for multi-container applications
• Container networking, volume management, security, and image optimization techniques
• Project: Containerize full-stack application with proper optimization

Class 5: Advanced Container Monitoring Project

• Real-time container monitoring with visual dashboard and interactive charts for performance visualization
• Alert system with AWS SES email notifications and stress testing for different load scenarios
• Project: Extend monitoring system with custom metrics and notifications

Module 2: AWS ECS, Infrastructure as Code & CI/CD (Classes 6-13)

Class 6: Two-Tier App Deployment on ECS (Console)

• ECS fundamentals: clusters, services, task definitions, and Application Load Balancer configuration
• Container service discovery, logging, health checks, and basic CloudWatch monitoring
• Project: Deploy database-backed web application on ECS

Class 7: Terraform Fundamentals

• Terraform basics: providers, resources, state management, and writing modular configurations
• Variable management, workspace concepts, and planning infrastructure changes safely
• Project: Convert manual AWS setup to Terraform code

Class 8: ECS Infrastructure with Terraform

• Converting manual ECS deployment to Infrastructure as Code with HTTPS and SSL certificates
• Multi-environment setup with Terraform modules and state management strategies
• Project: Create development and production environments

Class 9: Git and GitHub Actions Fundamentals

• Git workflows, branching strategies, and GitHub Actions: workflows, jobs, steps
• Secrets management, environment variables, and basic CI/CD pipeline creation
• Project: Create multi-stage pipeline with automated testing

Class 10: Automated Build and Deploy for ECS with GitHub Actions

• Container image building, versioning strategies, and automated testing integration
• ECS deployment automation with GitHub Actions and environment-specific workflows
• Project: Implement blue-green deployment strategy

Class 11: ECS Load Testing, Auto Scaling, and Monitoring

• Application and container auto-scaling configuration with load testing strategies
• CloudWatch logging, custom dashboards, and alert management automation
• Project: Create comprehensive monitoring and alerting setup

Class 12: Three-Tier Application with Advanced Terraform

• Advanced Terraform: modules, data sources, multi-environment strategies (dev, staging, prod)
• Database tier with RDS, networking, security best practices, and CloudFront CDN integration
• Project: Implement disaster recovery and backup strategies

Class 13: OIDC with AWS and GitHub for Keyless Authentication

• OpenID Connect (OIDC) setup between GitHub and AWS with IAM roles and trust relationships
• Keyless authentication for Terraform and application deployments with security best practices
• Project: Implement fine-grained permissions and security policies

Module 3: Python for DevOps, Lambda & FinOps (Classes 14-20)

Class 14: Python for DevOps Automation

• Python essentials for DevOps: boto3, requests, automation libraries, and AWS SDK integration
• Error handling, logging, testing best practices, and creating reusable Python modules
• Project: Build automated AWS resource provisioning tool

Class 15: AWS Lambda and Serverless Architecture

• Lambda fundamentals: functions, triggers, execution models, and event-driven architecture patterns
• Lambda layers for code reusability and integration with SQS, SNS, S3 for event processing
• Project: Create serverless data processing pipeline

Class 16: Advanced Lambda Projects with Terraform

• DRY Terraform configurations for multi-Lambda setups and deployment automation with CI/CD
• VPC integration, security groups, networking, and monitoring serverless applications
• Project: Build multi-service serverless architecture

Class 17: Event-Driven Architecture and Lambda Orchestration

• Step Functions for Lambda orchestration and EventBridge for event routing and processing
• Dead letter queues, error handling strategies, performance optimization, and cost management
• Project: Create complex business workflow automation

Class 18: FinOps Fundamentals and Cost Management

• FinOps principles, cloud cost management strategies, AWS Cost Explorer, budgets, and billing alerts
• Resource tagging strategies, cost allocation, and building cost dashboards and reports
• Project: Create comprehensive cost monitoring and optimization plan

Class 19: RDS Migration for Cost Savings – Part 1

• RDS cost analysis, optimization strategies, and Python scripts for database migration automation
• Data validation, integrity checking, migration planning, and rollback strategies
• Project: Build automated migration testing framework

Class 20: RDS Migration for Cost Savings – Part 2

• ECS job for large-scale database migration and Lambda triggers for migration workflow automation
• Monitoring and alerting during migration process with post-migration validation and cleanup
• Project: Implement zero-downtime migration strategy

Module 4: Kubernetes and Container Orchestration (Classes 21-32)

Class 21: Kubernetes Fundamentals

• Kubernetes architecture, core concepts, pods, services, deployments, ConfigMaps
• kubectl commands, cluster management, and local development with Minikube
• Project: Deploy multi-tier application on Kubernetes

Class 22: Advanced Kubernetes Concepts

• StatefulSets, DaemonSets, Jobs, persistent volumes, and storage classes
• Network policies, security contexts, resource limits, and quality of service
• Project: Implement stateful application with proper storage

Class 23: Kubernetes Monitoring with Prometheus, Grafana, and Loki

• Prometheus setup, service discovery, Grafana dashboards, and visualization
• Loki for centralized log aggregation and Alert manager configuration
• Project: Create custom metrics and alerting rules

Class 24: GitOps with ArgoCD

• ArgoCD installation, configuration, and application deployment through GitOps
• Sync policies, automated deployments, and managing configuration through Git Project: Implement progressive delivery strategies

Class 25: Terraform for EKS – Infrastructure Setup

• EKS cluster creation with managed node groups and VPC networking configuration
• IAM roles, security configuration, cluster autoscaling, and cost optimization
• Project: Multi-AZ EKS setup with disaster recovery

Class 26: EKS Advanced Configuration and Security

• Self-managed node groups, Fargate profiles, and Pod Identity implementation
• SSL/TLS management with cert-manager, ACM, network security, and encryption
• Project: Implement zero-trust network policies

Class 27: Microservices Architecture on EKS – Part 1

• Microservices design principles, patterns, service discovery, and communication
• API gateway, load balancing, and database per service pattern
• Project: Implement circuit breaker and retry patterns

Class 28: Microservices Architecture on EKS – Part 2

• Advanced service mesh with Istio and distributed tracing and observability
• Config management, secret handling, and inter-service authentication
• Project: Implement canary deployments and feature flags

Class 29: Helm and Kustomize for Kubernetes

• Helm charts for complex applications and Kustomize for environment-specific configurations
• Chart templating, value management, and application versioning strategies
• Project: Create reusable Helm charts library

Class 30: Kubernetes Security and Pod Identity

• Pod Security Standards, admission controllers, and Workload Identity management
• Image scanning, vulnerability management, and runtime security monitoring
• Project: Implement comprehensive security scanning pipeline

Class 31: Multi-Environment Kubernetes Strategy

• Environment isolation, namespace strategies, resource quotas, and limit ranges
• Environment promotion workflows and cluster federation management Project: Implement GitOps across multiple environments

Class 32: Advanced GitHub Actions for Kubernetes

• Matrix builds for multiple microservices and reusable workflows with composite actions
• Security scanning integration (SAST, DAST, SCA) and compliance workflows
• Project: Build enterprise-grade CI/CD pipeline

Module 5: SRE Practices and Operational Excellence (Classes 33-34)

Class 33: SRE Fundamentals and Incident Response

• Site Reliability Engineering principles, incident response procedures, and on-call management
• SLI, SLO, error budget management, and incident command system
• Project: Build comprehensive incident response framework

Class 34: Postmortems and Agile Practices

• Postmortem culture, blameless analysis, root cause analysis, and sprint planning
• Retrospectives, design reviews, and project management for DevOps teams
• Project: Implement postmortem analysis and agile framework

Module 6: DevSecOps and Security (Classes 35-37)

Class 35: DevSecOps Fundamentals and Security Scanning

• Security shift-left principles and SAST, DAST, SCA integration in CI/CD
• Container image vulnerability scanning and infrastructure security scanning
• Project: Create comprehensive security scanning pipeline

Class 36: Advanced Security: Secrets Management and Compliance

• HashiCorp Vault integration and AWS Secrets Manager integration
• Compliance automation (SOC2, PCI DSS, HIPAA) and security policy as code Project: Implement end-to-end secrets rotation automation

Class 37: Security Monitoring and Incident Response

• SIEM integration, log analysis, intrusion detection, and automated response
• Security alerting, incident management, and forensics implementation
• Project: Build automated security incident response system

Module 7: AIops and Intelligent Automation (Classes 38-40)

Class 38: AI Tools for DevOps Engineers

• Effective use of ChatGPT, GitHub Copilot, Claude for DevOps tasks and prompt engineering
• AI-assisted code generation, debugging, documentation, and infrastructure design
• Project: Create AI-generated documentation and automation scripts

Class 39: Intelligent Monitoring and Infrastructure Optimization

• Machine learning for anomaly detection and intelligent alerting systems
• AI for resource usage prediction, automated scaling decisions, and cost optimization
• Project: Implement ML-based monitoring and optimization system

Class 40: Advanced AIops Integration and Self-Healing Infrastructure

• Self-healing infrastructure with AI decision making and intelligent deployment strategies
• AI-powered performance analysis and advanced ChatOps with incident management
• Project: Build comprehensive AIops platform demonstration

Course Completion and Certification

Upon completion of all 40 classes and associated projects, students will receive:

• Advanced DevOps Practitioner Certificate with AIops specialization
• Portfolio of 15+ real-world projects including microservices and AIops implementations
• GitHub repository showcasing all implemented solutions
• Reference architecture diagrams and best practices documentation
• Interview preparation and job placement assistance

This curriculum follows a logical, incremental learning path from Linux fundamentals to advanced AIops, ensuring each concept builds upon previous knowledge