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DevOps Engineering

Comprehensive DevOps Engineering track covering Linux (Ubuntu/CentOS), GitHub Actions, Jenkins, CI/CD automation, Docker, Kubernetes, AWS (EC2/S3/IAM/VPC/CloudWatch), Terraform, Prometheus, Grafana, ELK, and Bash/Python scripting.

Data-Driven DevOps Roadmap (Fresher to Intermediate)

This roadmap is pulled from Supabase DevOps topics and question banks. Learn Linux first, then networking, then CI/CD, then containers/Kubernetes, and finally cloud + IaC deployment patterns.

Tracks

Questions

641

Fresher

Intermediate

Concept Clearing First

Start concepts first, then tools. This section is designed for beginners who feel DevOps has too many tools and too many new words.

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)

Beginner Clarity

What exactly is DevOps? DevOps is the engineering practice of building, testing, deploying, and operating software continuously with automation and reliability.

Why does DevOps exist? It exists to reduce slow manual releases, environment mismatch issues, and production outages caused by disconnected teams.

Simple analogy: Think of DevOps like a modern airport system: developers are aircraft builders, operations are air traffic controllers, and DevOps is the automated control tower ensuring safe, frequent takeoffs and landings.

Lifecycle: Plan -> Code -> Build -> Test -> Release -> Deploy -> Operate -> Monitor -> Improve

DevOps Explained Simply

Definition: DevOps means building software and running software as one continuous engineering system instead of separate silos.

Analogy: Think of a food delivery app: developers build the app menu and checkout, operations keeps delivery running 24x7, and DevOps automates both so customers always get fast and reliable service.

Daily Work: In daily work, DevOps engineers automate release pipelines, maintain cloud infrastructure, monitor incidents, and improve reliability after every deployment.

What is this? A practical way to ship software faster and safer.
Why learn it? It directly maps to high-demand cloud and platform roles.
How will I use it? Through deployment, monitoring, troubleshooting, and automation tasks.

Why Learn DevOps in 2026?

Career Demand: High demand across product startups, SaaS, fintech, e-commerce, and enterprise cloud modernization.

Career Scope: Roles include DevOps Engineer, Cloud DevOps Engineer, Platform Engineer, SRE, and DevSecOps Engineer.

Top adopters: Google, Amazon, Microsoft

Where to Start (Exact Order)

1. Step 1: Build fundamentals
Linux + Networking + Git/GitHub basics. Learn commands, services, and branch workflow.
2. Step 2: Automate delivery
Learn Docker and CI/CD. Build pipeline from code push to test/build/deploy.
3. Step 3: Run production systems
Learn Kubernetes + Cloud + Terraform + Monitoring + Security and ship end-to-end projects.

Basics Root: Start Here First

This is the core foundation path. Complete these basics first before deep tools or advanced automation.

Linux Basics

File system navigation
Users and permissions
Processes/services
Logs and troubleshooting

Outcome: You can access and manage a Linux server safely.

Networking Basics

DNS and IP
Ports and protocols
HTTP/HTTPS flow
Basic connectivity debugging

Outcome: You can diagnose common app reachability issues.

Git and Collaboration Basics

Commit, branch, merge
Pull request flow
Code review etiquette
Readable commit history

Outcome: You can work in team workflows without breaking delivery.

CI/CD Basics

Pipeline stages
Build/test/deploy flow
Artifacts and versioning
Rollback concept

Outcome: You can ship changes through an automated release path.

Docker Basics

Image vs container
Dockerfile essentials
Container networking
Volumes for persistence

Outcome: You can containerize and run applications consistently.

Kubernetes Basics

Pod, deployment, service
ConfigMap and Secret
Readiness/liveness checks
Rolling updates

Outcome: You can deploy and expose apps on a cluster.

Cloud and IaC Basics

Compute/network/storage building blocks
IAM least privilege
Terraform fundamentals
Environment separation

Outcome: You can provision reproducible infrastructure for dev/stage/prod.

Observability and Security Basics

Metrics and logs
Alerting
Secret handling
Vulnerability scanning

Outcome: You can operate systems with reliability and risk control.

Who Is a DevOps Engineer?

A DevOps Engineer connects development and operations to deliver software faster, safer, and with high reliability.

Automate build, test, and release workflows using CI/CD pipelines.
Manage cloud infrastructure, compute, networking, and secure access.
Containerize services and orchestrate workloads for scale and resilience.
Monitor systems with metrics, logs, and alerts for proactive incident response.
Improve deployment reliability with rollback strategy, runbooks, and SRE practices.

DevOps Learning Modules (Beginner to Advanced)

Beginner

Linux and System Fundamentals

Tools: Linux, Bash, systemd, ssh

Topic Breakdown

File system and permissions
Processes and services
Networking commands
Bash scripting basics

Suggested Project: Provision Ubuntu VM, harden SSH, deploy Nginx, and write maintenance scripts.

Beginner

Git, GitHub, and Team Collaboration

Tools: Git, GitHub

Topic Breakdown

Branching strategy
Pull requests and reviews
Merge conflict handling
Commit hygiene

Suggested Project: Create team repo workflow with branching policy and contribution guide.

Intermediate

CI/CD Engineering

Tools: GitHub Actions, Jenkins, GitLab CI

Topic Breakdown

Pipeline design
Build-test-deploy stages
Artifact versioning
Rollback and release strategy

Suggested Project: Build pipeline for Node.js app with tests, scan, image build, and staged deploy.

Intermediate

Containers and Images

Tools: Docker, Docker Compose, ECR

Topic Breakdown

Dockerfile best practices
Image optimization
Compose for local stacks
Registry workflow

Suggested Project: Dockerize multi-service app with secure image pipeline and versioned tags.

Intermediate

Kubernetes and Orchestration

Tools: Kubernetes, Helm, kubectl

Topic Breakdown

Pods, Deployments, Services
Ingress and traffic routing
ConfigMap/Secret management
HPA basics

Suggested Project: Deploy microservices on Kubernetes with Ingress, autoscaling, and health probes.

Intermediate

Cloud Engineering

Tools: AWS, Azure, GCP

Topic Breakdown

Compute, storage, identity
VPC and load balancing
Security groups and IAM
Cost basics

Suggested Project: Deploy production-style app on AWS EC2 with load balancer and monitoring alarms.

Intermediate

Infrastructure as Code

Tools: Terraform

Topic Breakdown

Providers and resources
State and backend
Reusable modules
Environment separation

Suggested Project: Create Terraform modules to provision VPC, EC2, and IAM roles across environments.

Advanced

Monitoring and Observability

Tools: Prometheus, Grafana, ELK, Loki

Topic Breakdown

Metrics and dashboards
Alerting strategy
Log aggregation
SLO/SLI thinking

Suggested Project: Build golden-signal dashboard and alert matrix with severity routing.

Advanced

DevSecOps and Governance

Tools: Trivy, Vault, OPA, SAST/DAST

Topic Breakdown

Shift-left security
Container/image scanning
Secrets management
Policy as code

Suggested Project: Add security gates to CI/CD and enforce policy checks on infrastructure changes.

Advanced

Interview and Placement Preparation

Tools: System design docs, Incident postmortem templates

Topic Breakdown

Scenario troubleshooting
Architecture explanation
STAR storytelling
Resume project framing

Suggested Project: Prepare portfolio with 3 end-to-end projects and measurable outcomes.

Modules with Real-World Use Cases

Module	Real Use Case Example
Linux	SSH into server, configure services, and troubleshoot logs during incidents.
Git	Use feature branches, pull requests, and reviews for safe code integration.
CI/CD	Automate build-test-deploy so releases happen with minimal manual work.
Docker	Package app into image and run same build from laptop to production.
Kubernetes	Deploy multi-service app with Ingress, scaling, and health probes.
Cloud + IaC	Provision VPC, compute, IAM, and storage through Terraform modules.
Observability	Create dashboards and alerts to detect issues before customers report them.

DevOps Architecture Deep Dive

Monolithic vs Microservices Architecture

Monoliths are simpler to start but harder to scale team ownership.
Microservices improve independent deployment and scaling at the cost of operational complexity.
Choose based on team size, domain boundaries, and release velocity requirements.

High Availability Architecture

Use multi-AZ deployments, redundant instances, and health-checked load balancers.
Eliminate single points of failure in compute, data, and networking.
Design failover runbooks and recovery targets (RTO/RPO).

Scalability Patterns

Horizontal scaling for stateless workloads.
Caching, queue-based buffering, and autoscaling policies for burst traffic.
Database scaling using replicas, partitioning, and workload-aware indexing.

Stateless vs Stateful Applications

Stateless services scale and recover faster.
Stateful services require persistent identity, storage, backup, and migration strategy.
Container orchestration differs: Deployments for stateless, StatefulSets for stateful.

Distributed Systems Basics and CAP Theorem

Network failures and partial outages are normal in distributed systems.
CAP trade-offs force design choices among consistency, availability, and partition tolerance.
Use idempotency, retries, timeouts, and circuit breakers to increase resilience.

Event-Driven and API Gateway Architecture

Event-driven design decouples producers and consumers using queues/streams.
API Gateway centralizes auth, routing, throttling, and observability.
Use async pipelines for background processing and better fault isolation.

DevOps Architecture Diagrams Library

Kubernetes Architecture

Users -> Ingress -> Service -> Pods
                      |
                Control Plane
    API Server | Scheduler | Controller Manager | etcd
                      |
                  Worker Nodes

CI/CD Pipeline Flow

Git Push -> CI Trigger -> Build -> Unit Test -> Security Scan
                                          |
                                     Artifact Store
                                          |
                               Deploy Staging -> Smoke Test
                                          |
                                 Approve -> Deploy Production

AWS 3-Tier Architecture

Internet -> ALB -> Web Tier (EC2/ECS)
                         |
                      App Tier (EC2/EKS)
                         |
                  Data Tier (RDS/ElastiCache)
      + CloudWatch + IAM + VPC (Public/Private Subnets)

30-Minute Daily Basics Process

Use this routine every day to build strong fundamentals with small but consistent progress.

00-05 min
1. Linux warm-up
Run `pwd`, `ls`, `cd`, `cat`, check service status, and read one log stream.
05-10 min
2. Networking check
Validate DNS and connectivity with `curl`, `ping`, and one port check.
10-15 min
3. Git + CI awareness
Review one PR, check pipeline status, and identify one failed/slow stage.
15-20 min
4. Docker and image flow
Read one Dockerfile, map build layers, and verify image tag strategy.
20-25 min
5. Kubernetes control loop
Inspect one deployment, one service, and one probe configuration.
25-30 min
6. Cloud + monitoring + security
Check one cloud alarm, one dashboard panel, and one secret/vuln policy rule.

Time-Based Roadmaps

30-Day Starter Roadmap

Week 1: Linux commands, filesystem, permissions, services.
Week 2: Git/GitHub workflow + networking fundamentals.
Week 3: Docker basics + containerize one app.
Week 4: Basic CI/CD with GitHub Actions and first deployment.

90-Day Internship Roadmap

Month 1: Linux, Git, Docker, basic troubleshooting.
Month 2: CI/CD, AWS fundamentals, deployment automation.
Month 3: Kubernetes basics, Terraform intro, monitoring setup, project polishing.

180-Day Job-Ready Roadmap

Months 1-2: Core fundamentals and Dockerized deployments.
Months 3-4: Cloud + CI/CD + Terraform with multi-environment setup.
Months 5-6: Kubernetes, observability, DevSecOps, and interview-ready portfolio.

Real-World DevOps Projects for Resume

Beginner

Project 1: CI/CD + Docker + AWS EC2

Dockerize Node.js app
Push to GitHub
Build CI/CD pipeline
Deploy to EC2 with Nginx

Intermediate

Project 2: Kubernetes Microservices Platform

Deploy two services
Add Ingress and config management
Set probes and autoscaling
Attach monitoring

Intermediate

Project 3: Terraform Infra Automation

Provision VPC + EC2 via Terraform
Split environments
Add remote state
Connect deployment pipeline

Advanced

Project 4: DevSecOps Pipeline

Integrate SAST/DAST
Add secret scanning
Enforce policy checks
Publish security report

Hands-on Labs (Copy Snippets)

Linux Service Check

Validate that your web service is healthy after deployment.

systemctl status nginx\njournalctl -u nginx --since "15 min ago"\nss -lntp

Git Feature Workflow

Ship changes safely through branch + PR model.

git checkout -b feature/login-fix\ngit add .\ngit commit -m "Fix login timeout"\ngit push origin feature/login-fix

Docker Build and Run

Create portable runtime package.

docker build -t app:v1 .\ndocker run -d -p 3000:3000 app:v1

Kubernetes Deployment

Deploy production workload with rolling updates.

kubectl apply -f deployment.yaml\nkubectl apply -f service.yaml\nkubectl rollout status deployment/api -n prod

Terraform Plan and Apply

Provision infrastructure reproducibly with review step.

terraform init\nterraform validate\nterraform plan -out=tfplan\nterraform apply tfplan

Production Readiness

Logging and Observability

Logs vs Metrics vs Traces: each answers a different debugging question.
OpenTelemetry for consistent instrumentation across services.
Distributed tracing to identify latency bottlenecks and downstream failures.
Prometheus + Grafana dashboards for golden signals (latency, traffic, errors, saturation).

Incident Management and SRE

Use SLI, SLO, and SLA to define reliability objectives and business expectations.
Run incident response with severity levels, ownership, and escalation policy.
Perform Root Cause Analysis (RCA) and publish postmortems with corrective actions.
Adopt SRE practices similar to Google: error budgets, toil reduction, and blameless learning.

Advanced Kubernetes Engineering

Beyond Pods and Deployments: control plane internals, policy, and GitOps operations.

Cluster Architecture and Control Plane Design
etcd, kube-apiserver, scheduler, controller-manager internals
RBAC and namespace isolation strategies
Network Policies for east-west traffic security
Helm chart lifecycle and release management
GitOps for declarative application delivery

Tools: Kubernetes, Helm, Argo CD

DevSecOps for 2026

Container vulnerability scanning integrated into CI/CD.
Secrets management with short-lived credentials and rotation.
IAM least-privilege and role-based access hardening.
Zero Trust model across users, workloads, and network boundaries.
Policy as Code to enforce security and compliance at deploy time.
AWS implementation focus: IAM policies, KMS, Security Hub, and audit trails.

GitOps and Modern Deployment

Git as single source of truth for app and infra desired state.
Declarative infrastructure and application manifests.
Pull-based deployment model improves auditability and rollback safety.
Argo CD and Flux continuously reconcile cluster state.

Tools: Argo CD, Flux

Real DevOps Case Studies

Netflix

Architecture: Cloud-native microservices with extreme traffic and regional resilience requirements.

Tools: AWS, Spinnaker, Observability tooling

Deployment: Progressive delivery with strong reliability automation.

Learning: Design for failure and automate recovery as a first-class requirement.

Amazon

Architecture: Service-oriented platform with high ownership and deployment frequency.

Tools: AWS, Internal deployment platforms, Cloud monitoring

Deployment: Automated deployment pipelines with strict rollback controls.

Learning: Operational excellence requires CI/CD discipline plus strong ownership boundaries.

Google

Architecture: Large-scale distributed systems with mature SRE operating model.

Tools: Kubernetes ecosystem, SRE practices, Extensive observability stack

Deployment: Reliability-driven release process with SLO/error-budget governance.

Learning: Balance feature velocity with reliability objectives using SRE principles.

DevOps Troubleshooting Lab

Pod CrashLoopBackOff

Steps

Inspect pod status/events
Check container logs
Validate env/config/secret references

Debug Commands

kubectl get pods | kubectl describe pod <pod> | kubectl logs <pod> --previous

Sample Log: Error: failed to load config from /app/config.yaml: file not found

RCA: Cause: missing config mount | Fix: update ConfigMap and rollout restart | Prevention: startup config validation.

502 Bad Gateway in NGINX

Steps

Check upstream health
Verify service/port mapping
Confirm app process is listening

Debug Commands

curl -I https://app.example.com | sudo nginx -t | ss -lntp

Sample Log: connect() failed (111: Connection refused) while connecting to upstream

RCA: Cause: upstream app down | Fix: restart service and health checks | Prevention: add readiness checks + alerting.

High CPU Usage

Steps

Identify top process
Correlate with traffic/deploy
Scale or optimize hotspot

Debug Commands

top | ps aux --sort=-%cpu | head | kubectl top pod

Sample Log: CPU throttling observed for container api-service at 95% sustained usage.

RCA: Cause: hot endpoint compute spike | Fix: autoscale and optimize query | Prevention: load test before release.

Memory Leak Detection

Steps

Observe memory trend
Capture heap/profile
Rollback leaking release

Debug Commands

kubectl top pod | free -m | journalctl -u app-service --since "1 hour ago"

Sample Log: OOMKilled: container exceeded memory limit 512Mi.

RCA: Cause: retained object growth | Fix: patch memory handling + restart | Prevention: leak tests in staging.

Failed CI/CD Pipeline

Steps

Locate failed stage
Reproduce build locally
Check credentials/artifacts/dependencies

Debug Commands

npm ci | npm test | docker build -t app:test .

Sample Log: Pipeline failed at security scan stage: HIGH vulnerability found in base image.

RCA: Cause: vulnerable base image | Fix: upgrade base image + re-scan | Prevention: scheduled dependency updates.

Troubleshooting Guide (Beginner Friendly)

Docker build fails

Check Dockerfile syntax
Validate base image and internet access
Rebuild with verbose logs

Kubernetes CrashLoopBackOff

Inspect pod events
Check previous container logs
Verify config/secrets and startup command

CI/CD pipeline error

Find failing stage
Reproduce locally
Fix and rerun from the same commit

Terraform state issue

Confirm backend config
Check lock/state consistency
Run state list/refresh before apply

Roadmap Tracks (Clear Learning Paths)

Track 1 - DevOps Beginner

Target: Intern/Fresher DevOps Engineer

Modules: Linux + Git/GitHub + Docker fundamentals

Track 2 - Cloud DevOps

Target: Cloud DevOps Engineer

Modules: AWS core services + Terraform + CI/CD pipelines

Track 3 - Kubernetes Engineer

Target: Platform/Kubernetes Engineer

Modules: Kubernetes + Helm + Monitoring and observability

Track 4 - DevOps Architect

Target: DevOps/Solution Architect

Modules: System design + High availability + Security and governance

Interactive DevOps Platform Features

DevOps glossary (A-Z) with updated terminology.
Interactive command examples with copy-ready snippets.
Quiz checkpoints after each module.
Build Your Own DevOps Lab guided setup.
Downloadable YAML templates for CI/CD and Kubernetes.
Architecture diagrams library and deployment templates.
100+ practical DevOps command packs.
Terraform module examples and CI/CD YAML examples.

Skills Required for DevOps Fresher

Linux administration basics
Git and GitHub workflow
Docker fundamentals
CI/CD pipelines
AWS basics (EC2, IAM, VPC, S3)
Networking basics
Terraform fundamentals

6-Month Smart Plan (3 to 4 Hours Daily)

Month 1

Linux + Git + GitHub fundamentals

Month 2

Networking + Docker basics + mini deployment

Month 3

AWS core services and one production-style deployment

Month 4

CI/CD pipelines with GitHub Actions and Jenkins

Month 5

Terraform IaC with reusable modules

Month 6

Kubernetes + monitoring + resume-ready projects

Interview Preparation Tracks

Linux

Permissions troubleshooting
Service startup failure
Log-based debugging

Git/GitHub

Merge conflict resolution
Branch strategy
PR review scenarios

CI/CD

Pipeline failure analysis
Rollback strategy
Artifact promotion flow

Kubernetes

CrashLoopBackOff diagnosis
Ingress routing issue
Pod scheduling failure

Cloud

IAM least-privilege design
Network isolation
Scalability decisions

Salary in India (Approximate)

Fresher (0-1 year)

INR 4-7 LPA

2-3 years

INR 10-18 LPA

5+ years

INR 25+ LPA

Career Scope and Recruiter Expectations

Roles: DevOps Engineer, Cloud DevOps Engineer, SRE, Platform Engineer

Hiring companies: Google, Amazon, Microsoft

Hands-on projects with deployment and troubleshooting depth
CI/CD plus cloud plus IaC integration
Reliability mindset and production debugging ability

Certifications ROI

AWS DevOps Engineer Professional: High cloud-role credibility; strong for AWS-centric hiring.
CKA (Certified Kubernetes Administrator): High Kubernetes operations credibility for platform roles.
Terraform Associate: Strong IaC credibility for infra automation and cloud teams.

DevOps Collaboration and Soft Skills

Cross-team communication between developers, QA, security, and operations.
Ownership mindset: close incidents with RCA and prevention actions.
Feedback loops: learn from failures through blameless postmortems.
Documentation discipline: runbooks, architecture notes, and change logs.
Continuous improvement culture over one-time setup mentality.

FAQ: DevOps for Beginners

What is DevOps in one line?

DevOps is a culture and engineering practice that automates software delivery and operations for faster, safer releases.

Is DevOps difficult for beginners?

It is manageable if you follow a sequence: Linux, Git, Docker, CI/CD, Cloud, Kubernetes, Terraform, Monitoring.

Do I need coding for DevOps?

Yes, basic scripting (Bash or Python) is important for automation and troubleshooting.

Which cloud should I start with?

Start with AWS for beginner learning resources and broad hiring demand, then expand to Azure or GCP.

Can I get a DevOps job as a fresher?

Yes, with strong fundamentals plus 2-3 real projects showing CI/CD, Docker, cloud deployment, and debugging.

What are the most important tools to learn first?

Linux, Git/GitHub, Docker, CI/CD, AWS basics, Terraform basics, and monitoring.

How long does it take to become job-ready?

With focused daily study and projects, many students reach entry-level readiness in around 6 months.

What is the difference between DevOps and SRE?

DevOps focuses on delivery collaboration and automation, while SRE focuses on reliability engineering using SLO-driven operations.

Next Action Checklist

Set up Ubuntu VM and complete Linux command practice.
Create GitHub repo and apply branch + pull request workflow.
Dockerize one app and run it locally.
Build one CI/CD pipeline using GitHub Actions.
Deploy app to AWS EC2 and add monitoring.
Prepare resume with project outcomes and metrics.

Structured Update Strategy (Moving Forward)

Review tool changes every quarter (Kubernetes, cloud, CI/CD, security).
Refresh project templates every 60 days based on hiring patterns.
Add new glossary words as industry terms evolve (GitOps, platform engineering, FinOps).
Keep interview section updated with scenario-based questions and current tooling.

Fresher to Intermediate Track Flow

Fresher Stage

DevOps - Linux

Start with Linux administration so you can confidently operate servers, logs, permissions, and service lifecycle.

Supabase Question Bank: 358

Where are cron jobs for users commonly managed?
What does grep do?
What command displays running processes?

Fresher Stage

DevOps - Networking

Build networking fundamentals needed for debugging production traffic, DNS issues, ports, and load balancing.

Supabase Question Bank: 198

Which protocol resolves domain names to IP addresses?
What does HTTP status 502 usually indicate?
What is a subnet mask used for?

Intermediate Stage

DevOps - CI/CD

Automate build, test, and deployment pipelines to move from manual release steps to reliable delivery.

Supabase Question Bank: 20

What is the main purpose of a CI pipeline?
Which Git event commonly triggers a CI workflow?
In CI/CD, what is artifact versioning used for?

Intermediate Stage

DevOps - Containers and Kubernetes

Package applications with Docker and orchestrate safely with Kubernetes deployment, service, and scaling patterns.

Supabase Question Bank: 20

What is a Docker image?
What is a Docker container?
Why keep container images small?

Intermediate Stage

DevOps - Cloud and IaC

Learn AWS provisioning and Infrastructure as Code to launch, secure, and scale systems consistently.

Supabase Question Bank: 20

What is Infrastructure as Code (IaC)?
Why use Terraform in DevOps?
What does terraform plan show?

Intermediate Stage

DevOps CI/CD

Hands-on DevOps practice track for fresher to intermediate progression.

Supabase Question Bank: 25

What does CI stand for in the context of CI/CD?
What does CD stand for in the context of CI/CD?
What is the primary goal of Continuous Integration (CI)?

End-to-End DevOps Roadmap

Follow these phases in order. This covers complete DevOps progression from server basics to platform-level operations.

Step 1

Phase 1: Linux and Networking Foundation

Build a strong operations base so you can run and debug real servers.

Must Know: Linux CLI | Users/permissions | Processes/services | DNS/CIDR/ports | SSH hardening

Deliverable: Secure Linux VM with service management and troubleshooting runbook.

Step 2

Phase 2: Version Control and Automation

Move from manual ops to repeatable CI workflows.

Must Know: Git branching | GitHub Actions | Jenkins pipelines | Artifact versioning | Secret management

Deliverable: CI pipeline that lints, tests, builds, scans, and publishes artifacts.

Step 3

Phase 3: Containerization and Orchestration

Package apps consistently and deploy safely at scale.

Must Know: Dockerfiles | Image scanning | Kubernetes deployments/services | Ingress | Helm and autoscaling

Deliverable: Kubernetes app deployment with rolling update and rollback.

Step 4

Phase 4: Cloud and Infrastructure as Code

Provision cloud infrastructure in a controlled, auditable way.

Must Know: AWS/Azure core services | IAM/RBAC | VPC/networking | Terraform | Environment separation

Deliverable: Reusable Terraform modules provisioning dev/stage/prod stacks.

Step 5

Phase 5: Observability, Reliability, and Security

Operate systems with monitoring, alerts, incident response, and compliance.

Must Know: Prometheus/Grafana | Logging stack | Alert routing | SLO/SLI | Policy and vulnerability controls

Deliverable: Production dashboard, actionable alerts, and incident playbook.

Step 6

Phase 6: Platform and Scale

Standardize internal platform patterns for multiple teams.

Must Know: GitOps | Progressive delivery | Service templates | Cost optimization | DR strategy

Deliverable: Platform playbook with golden paths and governance standards.

Step 7

Phase 7: Interview and Career Readiness

Translate technical work into business impact and interview-ready storytelling.

Must Know: STAR method | Incident storytelling | Scenario debugging | Basic system design | MVP documentation

Deliverable: Interview portfolio with measurable impact stories and architecture walk-through.

DevOps Tools Overview (Complete Stack)

Use this as your one-stop tool map. Every category includes what the tool is for in day-to-day DevOps work.

OS and Networking

Linux: Core server operating system used to host, debug, and maintain workloads.
Bash: Automation scripting for recurring operational tasks.
Nginx: Reverse proxy and ingress edge for routing and load balancing.
SSH: Secure remote administration protocol for server access.

CI/CD

GitHub Actions: Event-driven CI workflows integrated with GitHub repositories.
Jenkins: Highly customizable CI/CD server for complex enterprise pipelines.
Argo CD: GitOps-based continuous delivery for Kubernetes using declarative sync.
SonarQube: Code quality and static analysis gate in pipelines.
Artifact Registry: Stores versioned build outputs for release promotion.

Containers and Orchestration

Docker: Builds immutable container images for consistent runtime behavior.
Kubernetes: Orchestrates container workloads, scaling, and rollout strategies.
Helm: Package manager for Kubernetes manifests and environment values.
Trivy: Container security scanning for vulnerabilities and misconfigurations.

Cloud and IaC

AWS: Cloud platform for compute, storage, networking, and managed services.
Azure: Cloud platform with enterprise integration and managed identity support.
ECR: AWS container registry for storing and versioning Docker images.
Terraform: Infrastructure as Code for reproducible, version-controlled provisioning.
CloudWatch/Azure Monitor: Native cloud metrics, logs, and alarms.
FinOps: Cost governance practice to optimize cloud spending and usage efficiency.

Observability and SRE

Prometheus: Time-series metrics collection and alert query engine.
Grafana: Dashboarding and visualization for metrics and operations health.
Alertmanager: Routing, grouping, and escalation of monitoring alerts.
Loki/ELK: Centralized log aggregation and search for incident debugging.

Security and Governance

Vault/Key Vault: Secure storage and rotation for secrets and credentials.
OPA/Policy as Code: Automates policy checks across infra and deployment pipelines.
Falco: Runtime threat detection for containers and Kubernetes nodes.
SAST/DAST: Security testing stages integrated into CI/CD pipelines.

Collaboration and Engineering Practices

Git: Version control foundation for branching, reviews, and collaboration.
GitHub: Code hosting with pull requests, reviews, and engineering workflow controls.
README: Project communication artifact describing setup, architecture, and operations.
Commit Hygiene: Consistent commit messages and small changes improve traceability.
STAR Method: Interview framework to explain Situation, Task, Action, and Result with impact.

DevOps Tools Context: What, Types, When, Why, How to Use

Linux

What: Linux is the base operating system where most production services run.

Why: Strong Linux skills reduce downtime and improve incident response speed.

Types

Ubuntu/Debian family
RHEL/CentOS family
Minimal container-focused distros

When to use

When you need server setup, service control, logs, and permissions.
When debugging production incidents at OS and process level.

How to use

1Start with filesystem, users, permissions, and systemd commands.
2Practice logs + process troubleshooting daily with mini labs.
3Automate repetitive tasks using shell scripts.

CI/CD Pipelines

What: CI/CD pipelines automate build, test, security checks, and deployment.

Why: Automation reduces release risk and shortens time from commit to production.

Types

GitHub Actions
Jenkins
GitLab CI
Argo CD for GitOps delivery

When to use

When your team is manually building or releasing software.
When you need repeatable release quality gates.

How to use

1Define stages: lint, unit test, integration, scan, deploy.
2Add branch rules, artifact versioning, and rollback steps.
3Measure pipeline duration and failure points for continuous improvement.

Docker

What: Docker packages applications into portable, immutable container images.

Why: Containers make deployments consistent and easier to scale.

Types

Single-stage image
Multi-stage image
Docker Compose local stack

When to use

When environment mismatch exists between local, staging, and production.
When multiple services need consistent runtime packaging.

How to use

1Write secure multi-stage Dockerfiles with small base images.
2Scan images in CI before deployment.
3Tag images semantically and never deploy floating latest in production.

Kubernetes

What: Kubernetes orchestrates containerized workloads across clusters.

Why: Kubernetes improves reliability, rollout safety, and platform consistency.

Types

Deployment for stateless apps
StatefulSet for stateful apps
Helm-based packaged releases

When to use

When applications require scaling, self-healing, and rolling updates.
When you need standard deployment patterns across services.

How to use

1Start with Pods, Deployments, Services, Ingress, ConfigMap, and Secret.
2Add readiness/liveness probes and resource requests/limits.
3Use Helm and namespaces for cleaner release management.

Cloud + IaC

What: Cloud gives runtime infrastructure; IaC provisions it reproducibly from code.

Why: IaC reduces configuration drift and improves governance and repeatability.

Types

AWS/Azure/GCP cloud services
Terraform modules
Environment-specific workspaces

When to use

When infrastructure changes are frequent and manual setup causes drift.
When you need auditable infra changes through pull requests.

How to use

1Create reusable Terraform modules for network, compute, IAM, and storage.
2Run fmt/validate/plan in CI before apply.
3Use remote state with locking and strict review approvals.

Monitoring and Observability

What: Observability combines metrics, logs, and traces for system health and debugging.

Why: Good observability shortens MTTD/MTTR and improves service reliability.

Types

Prometheus + Grafana
Loki/ELK logs
Alertmanager routing

When to use

When incidents take too long to detect or root-cause.
When teams need SLI/SLO visibility for reliability.

How to use

1Instrument golden signals: latency, traffic, errors, saturation.
2Create actionable alerts with ownership and severity.
3Use runbooks linked to alerts for faster recovery.

DevSecOps

What: DevSecOps integrates security controls into delivery workflows.

Why: Shift-left security prevents vulnerabilities from reaching production.

Types

SAST/DAST
Container/IaC scanning
Policy as code and secrets management

When to use

When releases move fast but security checks are manual or delayed.
When compliance and risk controls are required at scale.

How to use

1Add code, dependency, image, and IaC scans in CI gates.
2Manage secrets via vault systems and short-lived credentials.
3Enforce policy checks and block non-compliant deployments.

Video Knowledge Additions for Students

Build mindset first: DevOps is a collaboration and delivery practice, not only tools.

Keep Git fundamentals strong: branching, pull requests, readable commits, and clear README documentation.

Use AI carefully: automate repetitive learning and debugging tasks, but always validate output manually.

Start with mini projects before mega projects, then convert them into portfolio stories with impact metrics.

Include certifications selectively (like Kubernetes/AWS) only after hands-on implementation competence.

Prepare interviews with scenario-based debugging, incident response, and STAR storytelling of real projects.

Learn cloud cost thinking (FinOps) and shared responsibility while designing infrastructure.

Track evolution: from traditional CI/CD toward GitOps and platform engineering workflows.

First Words and Meanings (Linux, Docker, Kubernetes, CI/CD)

Linux

Kernel: Core of Linux that manages hardware, memory, and processes.
Shell: Command interface used to run Linux commands and scripts.
Permission: Access control rules for read, write, and execute on files.
Process: A running program instance managed by the operating system.
Systemd: Service manager used to start, stop, and monitor services.
Cron: Scheduler used to run jobs automatically at fixed times.

Docker

Image: Read-only package that contains app code, runtime, and dependencies.
Container: Running instance of a Docker image.
Dockerfile: Instruction file used to build Docker images.
Layer: Each Dockerfile step creates a cached image layer.
Registry: Remote store where container images are pushed and pulled.
Volume: Persistent storage mounted into containers.

Kubernetes

Pod: Smallest deployable unit that runs one or more containers.
Deployment: Controller that manages pod replicas and rolling updates.
Service: Stable network endpoint for reaching pods.
Ingress: HTTP/HTTPS routing into cluster services.
ConfigMap: Object used to store non-secret configuration values.
Secret: Object used to store sensitive values like tokens/passwords.

CI/CD

CI: Continuous Integration: automated build and test on every code change.
CD: Continuous Delivery/Deployment: automated release flow to environments.
Pipeline: Ordered automation stages like build, test, scan, and deploy.
Artifact: Versioned build output used for deployment.
Rollback: Revert deployment to a previously stable version.
Quality Gate: Rule that must pass before code can move to next stage.

Track Pages Navigation

Open detailed pages for Linux, Networking, GitHub Actions, Jenkins CI/CD, Docker, Kubernetes, AWS, Azure, and Prometheus/Grafana.

fresher

Linux Operations

Master shell, permissions, process control, logging, systemd, and troubleshooting workflows.

Open Page

fresher

Networking for DevOps

Understand DNS, CIDR, ports, load balancing, ingress, and production traffic debugging.

Open Page

intermediate

GitHub Actions Automation

Build CI pipelines for linting, tests, image builds, security checks, and deployment gates.

Open Page

intermediate

Jenkins CI/CD

Design Jenkins declarative pipelines for build/test/deploy with secrets and environment promotion.

Open Page

intermediate

Docker for DevOps

Package applications with optimized Dockerfiles and production-ready image workflows.

Open Page

intermediate

Kubernetes Orchestration

Deploy and operate workloads with deployments, services, ingress, HPA, and observability hooks.

Open Page

intermediate

AWS Cloud Operations

Launch, secure, monitor, and scale cloud workloads using EC2, IAM, networking, and observability services.

Open Page

intermediate

Azure DevOps Deployment

Deploy workloads on Azure using virtual machines, networking, managed identity, and monitor integration.

Open Page

intermediate

Prometheus and Grafana

Instrument services, collect metrics, and build actionable dashboards and alerting rules.

Open Page

advanced

Advanced DevOps Engineering

Production-grade DevOps engineering for students targeting mid-level roles: advanced Kubernetes, CI/CD strategy, IaC patterns, observability, troubleshooting, and DevSecOps.

Open Page

Linux Commands Moved to Linux Track

Linux command basics-to-advanced content is now available inside the dedicated Linux page for focused learning.

Open Linux Track

How to Launch an AWS Instance (Hands-on Runbook)

Use this exact flow for fresher to intermediate cloud deployment. Every step includes what to do and a CLI example.

1. Plan networking and access
Pick region, VPC/subnet, and a security group before launch. Keep SSH (22) restricted to your IP and application ports scoped to trusted CIDR ranges.
aws ec2 create-security-group --group-name devops-app-sg --description "DevOps app security group" --vpc-id vpc-xxxx
2. Create key pair and launch EC2
Create an SSH key pair, launch Ubuntu instance, and bind IAM role for least privilege. For fresher level, start with t3.micro in free-tier eligible setup.
aws ec2 run-instances --image-id ami-xxxxxxxx --instance-type t3.micro --key-name devops-key --security-group-ids sg-xxxx --subnet-id subnet-xxxx --tag-specifications "ResourceType=instance,Tags=[{Key=Name,Value=devops-linux-lab}]"
3. Connect and bootstrap server
After launch, connect through SSH and run baseline hardening: update packages, create non-root user, configure firewall, and disable password SSH login.
ssh -i devops-key.pem ubuntu@<public-ip> && sudo apt update && sudo apt upgrade -y && sudo adduser devopsops
4. Install runtime and deploy app
Install Docker or runtime stack, pull your app image, and run as service. Add health-check endpoint so CI/CD can verify deployment success.
sudo apt install -y docker.io && sudo docker run -d --name web -p 80:3000 your-registry/your-app:1.0.0
5. Observe and secure in production
Send logs/metrics to CloudWatch, set alarms for CPU, memory, and 5xx errors, and define rollback path using previous image tag.
aws cloudwatch put-metric-alarm --alarm-name web-cpu-high --metric-name CPUUtilization --namespace AWS/EC2 --statistic Average --period 300 --threshold 70 --comparison-operator GreaterThanThreshold --dimensions Name=InstanceId,Value=i-xxxx --evaluation-periods 2

Production Readiness Checklist

1Repository enforces protected branches and CI status checks before merge.
2Docker images are versioned, scanned, and promoted across environments.
3Kubernetes workloads use readiness/liveness probes and secret isolation.
4IAM roles follow least privilege and all changes are auditable.
5Terraform plan/apply is controlled through CI approvals with remote state.
6Monitoring includes infrastructure metrics, app health, and centralized logs.
7Rollback steps, incident runbooks, and owner escalation paths are documented.

Learning Notes

DevOps Engineering Master Roadmap

This path is built for practical production skills, not only theory.

Core Coverage

Linux operations: Ubuntu, CentOS, services, permissions, networking basics
CI/CD automation: GitHub Actions and Jenkins pipelines
Containerization: Docker build, registry, runtime optimization
Orchestration: Kubernetes deployments, services, config maps, secrets
AWS cloud: EC2, S3, IAM, VPC, CloudWatch
IaC: Terraform modules and environment management
Observability: Prometheus, Grafana, ELK
Scripting: Bash and Python automation

Execution Strategy

Build Linux fundamentals and shell confidence.
Create CI for lint/test/build/deploy.
Ship containerized workloads through Kubernetes.
Operate cloud infrastructure with Terraform and monitoring.