DevOps Engineering Platform
Guided learning from beginner to architect: Linux, Git, CI/CD, Docker, Kubernetes, AWS, Terraform, DevSecOps, and interview readiness.
Modular Learning Path
Learn DevOps step-by-step through focused modules instead of one long page.
Concept Clearing First
Beginners usually quit due to too many tools and unclear concepts. Start with clarity first.
1. DevOps in Simple Language
Definition: DevOps = Development + Operations.
Problem earlier
- Developers wrote code and handed it off to operations.
- Operations deployed code later in a separate process.
- This created delays, environment mismatch, and frequent release conflicts.
DevOps solves: Faster deployment | Automation | Collaboration | Continuous delivery
Used by: Google, Amazon, Microsoft
2. DevOps Lifecycle (Tool Mapping)
Plan
Define work, scope, and delivery goals.
Tool: Jira / GitHub Projects
Code
Write and review application changes.
Tool: Git + GitHub
Build
Compile/package artifacts automatically.
Tool: GitHub Actions / Jenkins
Test
Validate quality before release.
Tool: Unit/Integration Tests + Quality Gates
Release
Version and approve deployable artifacts.
Tool: Artifact Registry + Release Tags
Deploy
Roll out safely to runtime environments.
Tool: Docker + Kubernetes
Monitor
Track reliability and incidents in production.
Tool: Prometheus + Grafana
3. DevOps vs Developer vs SRE
SRE was popularized by Google.
| Role | Focus | Ownership | Success Metric |
|---|---|---|---|
| Developer | Build product features and business logic. | Application code quality and feature delivery. | Feature correctness and delivery velocity. |
| DevOps Engineer | Automate build/deploy and manage infrastructure workflow. | CI/CD pipelines, infra automation, and release safety. | Deployment frequency and lower change failure rate. |
| SRE | Reliability, uptime, and incident response discipline. | SLI/SLO operations, alerting, and production stability. | Availability targets and reduced incident impact. |
4. Core Concepts (Concept First)
CI/CD
Continuous Integration and Continuous Delivery/Deployment automate software delivery steps.
Why it matters: Reduces manual release errors and shortens time to production.
Container
A lightweight package that runs application code with all required dependencies.
Why it matters: Ensures consistent behavior across local, staging, and production.
Infrastructure as Code (IaC)
Provision and manage infrastructure using version-controlled code templates.
Why it matters: Prevents configuration drift and improves reproducibility.
Microservice
An application design where services are split by business capability.
Why it matters: Enables independent deployment and scaling.
Load Balancer
A traffic distribution component that routes requests across healthy instances.
Why it matters: Improves availability and handles traffic spikes.
Scalability
Ability of a system to handle increasing load without performance collapse.
Why it matters: Supports growth without major rewrites.
High Availability
Architecture patterns that minimize downtime using redundancy and failover.
Why it matters: Keeps services available during failures and maintenance.
5. DevOps Architecture Overview
Flow: User -> Application -> Container -> Kubernetes -> Cloud -> Monitoring
Think in full-system flow: user traffic reaches application services, services run in containers, containers are orchestrated by Kubernetes, infrastructure runs on cloud, and monitoring validates reliability.
Cloud example: Amazon Web Services (AWS)
Layer 1: Clarity Layer
DevOps is a delivery and operations practice that helps teams release software faster with automation and reliability.
It exists to remove release friction, reduce outages, and align development with production operations.
Lifecycle: Plan -> Code -> Build -> Test -> Release -> Deploy -> Operate -> Monitor -> Improve
- Developer: builds features.
- DevOps Engineer: builds and operates delivery systems.
- SRE: ensures reliability through SLO-driven operations.
Layer 2: Structured Roadmap Layer
0-30 days
Track A - Beginner
Level: Beginner
Modules: Linux basics + Git and GitHub + Networking fundamentals
Outcome: Deploy a simple app and explain core DevOps terms.
30-90 days
Track B - Core DevOps
Level: Intermediate
Modules: Docker + CI/CD + Cloud basics + Terraform basics
Outcome: Automate build-test-deploy pipeline on cloud.
90-150 days
Track C - Production Level
Level: Intermediate
Modules: Kubernetes + Monitoring + High availability + Load balancing
Outcome: Operate production-like systems with observability and scaling.
150-180 days
Track D - Architect
Level: Advanced
Modules: Distributed systems + Scalability design + Security + GitOps
Outcome: Design resilient platform architecture and governance.
Layer 3: Practical Lab Layer
Build With Me: Node.js to Production
Ship a Node.js app from source code to cloud deployment with CI/CD and monitoring.
- 1. Dockerize app | docker build -t node-app:1.0.0 .
- 2. Push source to GitHub | git add . && git commit -m "Initial deploy pipeline" && git push origin main
- 3. Configure CI/CD | Create `.github/workflows/deploy.yml` for test/build/deploy.
- 4. Deploy on EC2 | ssh ubuntu@<ec2-ip> && docker run -d -p 80:3000 node-app:1.0.0
- 5. Add NGINX reverse proxy | sudo apt install nginx -y && sudo nginx -t && sudo systemctl restart nginx
- 6. Add monitoring | Enable CloudWatch metrics/log collection for EC2 and app.
Layer 4: Career and Authority Layer
Interview prep, troubleshooting, projects, certifications, and salary insights.
Certifications: AWS DevOps Engineer Professional | CKA (Certified Kubernetes Administrator) | Terraform Associate
DevOps Architecture Library
CI/CD Pipeline Diagram
Commit -> CI Trigger -> Build -> Test -> Security Scan -> Artifact Artifact -> Deploy Staging -> Smoke Test -> Approval -> Deploy Production
Kubernetes Architecture Diagram
User -> Ingress -> Service -> Pods Control Plane: API Server | Scheduler | Controller Manager | etcd Worker Nodes: kubelet + container runtime
AWS 3-Tier Architecture Diagram
Internet -> ALB -> Web Tier Web Tier -> App Tier App Tier -> DB Tier (RDS) Observability: CloudWatch | Security: IAM + SG + VPC
DevOps Troubleshooting Lab
CrashLoopBackOff
Debug: kubectl get pods | kubectl describe pod <pod> | kubectl logs <pod> --previous
502 Bad Gateway
Debug: sudo nginx -t | ss -lntp | curl -I http://localhost:<port>
High CPU
Debug: top | ps aux --sort=-%cpu | head | kubectl top pod
CI pipeline failure
Debug: npm ci | npm test | docker build -t app:test .
Cluster Pages
Linux for DevOps
Learn Linux fundamentals for DevOps: filesystem, permissions, services, networking, and scripting.
Linux Shell Scripting for DevOps
Learn shell scripting for deployment, backups, and server automation workflows.
Linux Commands Cheat Sheet for DevOps
Organized Linux command reference with meaning, syntax, and practical DevOps use cases.
Linux Troubleshooting for DevOps
Troubleshoot real Linux production issues: high CPU, disk full, service failures, and port conflicts.
Linux Interview Questions for DevOps
Linux interview question bank for DevOps roles with practical scenario focus.
Git Complete Guide
Master Git and GitHub workflows for collaborative DevOps delivery.
Docker Beginner to Advanced
From Docker basics to production image pipelines and security scanning.
Kubernetes Production Guide
Production-focused Kubernetes: control plane, workloads, policies, Helm, and GitOps.
AWS for DevOps
Use AWS services for deployment, scaling, security, and operations.
Terraform IaC
Provision cloud infrastructure with Terraform modules, state, and environment separation.
DevSecOps
Secure pipelines and infrastructure with scanning, secrets, IAM, and policy-as-code.
DevOps Interview Questions
Topic-wise interview prep covering Linux, CI/CD, Kubernetes, cloud, and troubleshooting.
DevOps Projects
Resume-ready end-to-end DevOps projects with deployment and monitoring.
Glossary A-Z
Artifact: Versioned output from build pipeline.
Blue-Green Deployment: Release strategy with traffic switch between two environments.
CI/CD: Continuous Integration and Continuous Delivery/Deployment.
Container: Runtime unit packaging app and dependencies.
Declarative: Define desired state; system reconciles to it.
GitOps: Git-driven, declarative, pull-based deployment model.
IaC: Infrastructure as Code, provisioning infra using versioned code.
Kubernetes: Container orchestration platform for deployment and scaling.
Load Balancer: Distributes incoming traffic across healthy targets.
Microservices: Architecture with independently deployable services.
Orchestration: Automated scheduling and lifecycle management for workloads.
SLA/SLO/SLI: Service reliability agreement, objective, and indicator.