20-Week Real World Project based AWS DevOps Bootcamp

Real-world DevOps bootcamp by Akhilesh Mishra with real-world projects, live troubleshooting, live incident management with production-level context

This bootcamp is designed to teach you what a real world Devops project looks like, and you will learn everything by doing all real-world projects, troubleshooting live issues, and navigating live production incidents. For the next 5 months, you will live the experience of a Devops Enginner

My bootcamps will get you a good enough Devops experience that will help you crack any Devops interview

Bootcamp Details

• Bootcamp Level -> beginners to advanced
• Start date: 27th Jan 2026
• Total Classes -> 60
• Class Days: Tuesday, Wednesday, Friday
• Timings: 10 PM IST – 11.55 PM IST
• Class Duration: 2 hours each
• Language: English
• Teacher: Akhilesh Mishra
• All classes are recorded, and students get lifetime access to recordings, code, notes, and resources
• All classes will use real-world projects, production-level context, and details
• All classes will be live, with real-time troubleshooting

Bootcamp Details – week by week schedule

Module: Linux (Devops starts with Linux)

Week 1: Linux for Devops, basic shell scripting

• Linux command-line essentials, tree navigation, file permissions, process management, system monitoring
• Shell scripting basics, command line arguments, wildcards, input/output redirection
• Variables, loops, conditionals, and functions in bash scripting
• System Monitor Script: Automated metrics collection with report generation, and Container Monitor Script for performance monitoring

Project:

• Create automated backup and disk cleanup scripts
• Create a comprehensive system information script
• Real-time log monitoring with email alerts for HTTP 500 errors

Module: Cloud (AWS) and containers

Week 2: Evolution of cloud computing, networking, AWS fundamentals, AWS VPC, EC2

Topics to be covered

• History of computing, introduction to cloud computing
• networking fundamentals, networking for cloud
• AWS networking (VPC), Compute(EC2, Load balancers, Autoscaling ), Storage (s3, ebs, efs)
• AWS IAM, Route53, certificate manager

Projects:

• Hosting a web app on AWS ec2, with a custom domain, SSL, and nginx (production style)
• Web app autoscaling with AWS EC2 autoscaling groups, Load balancers, and real-time load testing

Week3: AWS storage, Databases, Custom networks

Topics:

• AWS storage services fundamentals (AWS S3, EBS, EFS) and Cloud Front (CDN)
• AWS Databases(RDS) with real-world use cases, patterns, and disaster recovery
• S3 life cycle, replication with production usecases

Project:

• Hosting a static website on S3 and CloudFront
• Database Disaster Recovery planning, recovery with disaster simulation
• real-world project around S3 replication across accounts, and lifecycle management

Week 4: Containerization using Docker and Docker Compose

• Evolution of Docker, its architecture, and everyday commands
• Building, sharing, and running custom Docker images
• Container networking, volume management, security, and image optimization techniques, multi-stage builds
• Docker Compose for multi-container applications, simulating real-time application, load testing, and alerting

Project

• Containerize a full-stack application with proper optimization
• Real-time container monitoring with a visual dashboard and interactive charts for performance visualization
• Alert system with AWS SES email notifications and stress testing for different load scenarios

Module: Running containers on Production + IAC + CICD

Week 5: Running containers on production with AWS ECS and Terraform on AWS

• ECS fundamentals: clusters, services, task definitions, and Application Load Balancer configuration
• running a production-level application on ECS
• Kubernetes vs ECS: How to decide which one to use from real-world case studies
• Container service discovery, logging, health checks, and basic CloudWatch monitoring
• Terraform basics: providers, resources, state management, and writing modular configurations
• Variable management, workspace concepts, and planning infrastructure changes safely

Project

• Deploy a database-backed web application (2-tier app) on ECS with security best practices, domain, SSL, and load balancer
• Deploy the ECS infra with Terraform
• Load testing and autoscaling the 2-tier app, and creating custom alerts

Week 6: Terraform Advanced, SDLC, Git, GitHub, Jira

• Terraform modules (private and public), Terraform import
• Converting manual ECS deployment to Infrastructure as Code with HTTPS and SSL certificates
• Multi-environment setup with Terraform modules and state management strategies
• interview questions around Terraform
• software development life cycle (past and present)
• GitHub and git fundamentals
• real-world practices around git and GitHub
• Day-to-day of a Devops engineer, SRE
• project requirements gathering, task allocation

Project

• Deploying the web app on ec2 (From week 2) using Terraform
• Building a Terraform module using a real-world pattern
• Deploying a 2-tier app on ecs with Terraform in real world way, following the best practices of Terraform
• Terraform drift detection, Terraform state recovery, and importing manually created resources to Terraform management
• Simulating real-world projects built in a team
• real-world simulation of Jira tickets with production-level context

Week 7: CI/CD (Github Actions)

• CICD fundamentals
• Github Action basics
• GitHub action on production
• Shared GitHub Actions
• Multi-environment deployment from real production
• Real-world, multi-environment Branching strategy with examples
• Build and deploy a 2-tier app on ECS (with Terraform) using GitHub Actions

Projects:

• Automate the infra build with Terraform while following the real-world practices
• Automate the build and deploy the 2 -tier app from week 5 on ECS

Week 8: Running microservices on ECS and Devsecops part 1

• Running microservices on AWS ECS, with air-tight security, advanced monitoring, and alerting
• Dynamic Terraform infra that creates resources for different environments(Dev, Prod, staging)
• Terraform automatically creates rds instance on dev and an RDS Aurora cluster on prod
• OIDC with AWS and GitHub for Keyless Authentication for Terraform build and app build/deploy
• Using GitHub Action hooks to trigger the deployment from a different GitHub repo (app code on 1 repo, and infra in another repo)

Projects:

• Deploy microservices on ECS with Terraform, GitHub Actions, while following production best practices
• Docker images scanning for microservices for vulnerability (Devsecops Project)
• App lint + test using GitHub Action and modern DevSecOps Tools
• Devsecops for Terraform using Checkov and tfsec

Module: Python for Devops

Week 9: Python for Devops using projects on AWS

• Python fundamentals
• Python data structures
• Python loops, conditionals, functions
• Python environment setup and virtual environments
• Essential DevOps libraries: boto3, requests, os, subprocess, pathlib
• File operations, JSON/YAML parsing
• Creating a custom CLI with Python and argparse
• making api calls with Python request modules
• Error handling and exception management
• File handling in Python

Hands-on project:

• Rest API CRUD operation with Python (requests)
• Creating AWS resources with Python
• Creating a cloud usage report from an AWS account with Python (boto3)

Week 10: Python Automations on AWS with Lambda (Serverless Architecture)

What you’ll learn:

• Lambda fundamentals: functions, triggers, execution models
• Event-driven architecture patterns
• Building Python functions for Lambda
• Lambda layers for code reusability
• Stitching together multiple automations with Lambdas
• Integration with SQS, SNS, and S3 for event processing
• Deploying Python automation on Lambda deployment with Terraform
• Lambda deployment best practices
• IAM roles and security for Lambda

Project:

• Automate sending cloud reports to the team (Python, AWS Lambda, AWS SES)
• IAM key rotation (Python, AWS Eventbridge from cron job)
• Image processing pipeline using multiple Lambda functions, Lambda layers for dependencies management
• Deploy Lambda with Terraform

Week 11: Python automation for Finops and Security driven project

• RDS cost analysis, optimization strategies, and Python scripts for database migration automation
• Implementing Python automation to scan inbound files with ClamAV
• Data validation, integrity checking, migration planning, and rollback strategies
• ECS job for large-scale database migration and Lambda triggers for migration workflow automation
• Terraform code for complete implementation
• Monitoring and alerting during the migration process with post-migration validation and cleanup

Production Project:

• Implement RDS migration automation with Python, and deployment on AWS ECS and Lambda with Terraform
• Building end-to-end automation to automate inbound file scanning with ClamAV, Python, Terraform (ecs job)

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Module: Kubernetes

Week 12: Kubernetes basics, building projects using minikube and Kind

• Kubernetes architecture, core concepts, pods, services, deployments, ConfigMaps
• kubectl commands, cluster management, and local development with Minikube
• StatefulSets, DaemonSets, Jobs, persistent volumes, and storage classes
• Network policies, security contexts, resource limits, and quality of service

Projects:

• Running 2-tier and 3-tier apps on Kubernetes using minikube and Kind clusters
• Logging and monitoring of applications on Kubernetes with Prometheus and Grafana

Week 13: Kubernetes on EKS with advanced concepts, and debugging Interview scenarios

• Running microservices on AWS EKS with Automode and a standard cluster
• Microservices design principles, patterns, service discovery, and communication
• Terraform to deploy a production-level EKS cluster
• k8s to AWS auth with IRSA and pod identity
• Terraform to deploy the k8s objects like configmaps, secrets, deployments, and ingress
• Running apps on fargate and managed nodes
• SSL/TLS management with cert-manager, ACM, network security, and encryption
• Deploying microservices on Kubernetes(EKS) and Terraform, following the production best projects
• Debugging Interview scenarios on kubernetes

project:

• running a 3-tier app on Kubernetes, creating EKS with EKSCTL, and making it production-ready with domain, SSL, load balancing, rolling upgrade
• Deploying a microservice on Kubernetes with Terraform deployment

Week 14: Gitops ArgoCD, Helm, Kustomise, and basics of kubernetes Observability

• Helm charts for complex applications and Kustomize for environment-specific configurations
• Init containers and sidecar patterns
• Jobs and CronJobs for batch processing and scheduled tasks
• Chart templating, value management, and application versioning strategies
• Implementing GitOps with ArgoCD to automate the deployment
• setting up logging, monitoring, and dashboarding with production-level details

Week 15: Running stateful apps on Kubernetes + Advanced live troubleshooting

• Deploying a stateful application on kubernetes cluster
• Multi-AZ setup for high availability
• Matrix builds for multiple microservices and reusable workflows with composite actions
• Implementing network policies for controlled traffic management between pods
• Security contexts and pod security standards
• Setting up service mesh with Istio

Week 16: Kubernetes advanced monitoring, SRE implementation, Incident management , RCA and Devsecops

• Advanced logging, monitoring, and dashboarding in Kubernetes with Prometheus, Grafana, and Loki
• Other observability practices in Kubernetes environments using AWS CloudWatch, Open Telemetry
• Site Reliability Engineering principles, incident response procedures, and on-call management.
• SLI, SLO, error budget management, and incident command system
• Postmortem culture, blameless analysis, root cause analysis, and sprint planning
• Retrospectives, design reviews, and project management for DevOps teams
• War room simulation for a live incident on kubernetes cluster with RCA writing and

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Module: Ansible and DevSecOps

Week 17: Ansible

• Ansible fundamentals: Playbooks, roles, variables, templates, and Vault for secret management
• Advanced Ansible: Organizing code with roles, Jinja2 templates, handlers, and conditionals
• Infrastructure provisioning with Packer: Building golden images for AWS, GCP, and Azure
• Automating golden image pipelines with GitHub Actions for CI/CD
• Integrating Ansible with Packer for configuration management

Project

• Build a production-ready automated golden image pipeline

Week 18: Devsecops Advanced

Project:

• Create a comprehensive security scanning pipeline
• Creating checks before PR merges (production-style pipelines)
• Build an enterprise-grade CI/CD pipeline
• Security shift-left principles and SAST, DAST, SCA integration in CI/CD
• Security scanning integration (SAST, DAST, SCA) and compliance workflows

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Module: AIops

Week 19: AIops and Intelligent Automation 

AI Tools for DevOps Engineers

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

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

Week 20: AIops + War room simulation + Resume prep + Interview prep

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 a comprehensive AIops platform demonstration

Resume built for different experience types

• Resume for freshers, experienced
• Job application tips

Devops interview prep, scenarios, tips

• Resume for freshers, experienced
• Job application tips

Course Completion and Certification

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

• Advanced DevOps Practitioner Certificate with AIops specialization
• Portfolio of 15+ real-world projects, including microservices on k8s and DevSecOps
• GitHub repository showcasing all implemented solutions
• Reference architecture diagrams and best practices documentation
• Interview preparation and job placement assistance

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

Reach out for Queries

• Email:livingdevops@gmail.com
• WhatsApp: +91 9259681620