DevOps Learning Roadmap

This roadmap covers everything you need to go from zero to production-ready DevOps engineer. The notes in this section follow this exact path — study them in order.

Phase 1 — Foundations

1. Linux (Thinking Like a System Engineer)

• File system hierarchy (/, /var, /etc)
• File types, inodes, symbolic vs hard links
• Users, groups, permissions, umask
• sudo internals & security implications
• Process lifecycle (fork, exec, signals)
• systemd:
  • units, targets, dependencies
  • service failures & restart loops
• Logs:
  • journalctl deep usage
  • app logs vs system logs
• Disk:
  • mount points, fstab awareness
  • disk pressure & inode exhaustion
• Memory & CPU:
  • free, vmstat basics
  • CPU load vs CPU usage
• SSH:
  • key-based auth
  • port forwarding use cases
• Common failures:
  • service not starting
  • permission denied
  • disk full
  • high load

2. Bash & Automation Mindset

• Shell execution model
• Exit codes & error handling
• Variables, quoting, conditionals
• Loops & functions
• Positional parameters
• Pipes & redirection
• Cron & scheduling pitfalls
• Idempotent scripting mindset
• Logging in scripts
• Defensive scripting

3. Networking (Absolute Basics)

• OSI vs TCP/IP (practical mapping)
• IP addressing & CIDR
• Ports & sockets
• TCP handshake & common failures
• DNS:
  • resolution flow
  • caching & TTL
• HTTP:
  • request lifecycle
  • headers, status codes
• HTTPS:
  • certificates
  • TLS termination
• Load balancing:
  • L4 vs L7
  • health checks
• Debugging tools:
  • curl (advanced usage)
  • dig / nslookup
  • ss / netstat
  • traceroute
  • tcpdump (basic)

4. Git & Team Workflows

• Git internals (commit tree concept)
• Branching strategies (trunk-based vs feature)
• Merge vs rebase (when & why)
• Conflict resolution
• GitHub / GitLab / BitBucket
• PR review etiquette
• Commit hygiene
• Tagging & releases
• README writing (engineering communication)

Phase 2 — Core DevOps

1. Containers (Docker Deep Reality)

• Why containers exist (VM pain)
• Image vs container vs runtime
• Dockerfile:
  • layer caching
  • ENTRYPOINT vs CMD
  • env handling
• Multi-stage builds
• Image size & attack surface
• Volumes vs bind mounts
• Docker networking
• Docker Compose patterns
• Common failures:
  • container exits
  • port not exposed
  • env misconfig
  • dependency missing

2. Cloud Fundamentals (AWS / Azure / GCP)

• Shared responsibility model
• IAM:
  • users vs roles
  • policies
  • access boundaries
• EC2:
  • instance lifecycle
  • security groups
• VPC:
  • CIDR planning
  • public vs private subnets
• Storage:
  • S3 basics & policies
• Databases:
  • RDS awareness
• Registry:
  • ECR workflow
• Cost awareness — common mistakes

3. CI/CD (Delivery Engineering)

• CI vs CD
• Pipeline design principles
• Pipeline as code
• Build → test → scan → artifact
• Secrets management
• Deployment strategies:
  • rolling
  • blue-green
  • canary (conceptual)
• Rollback mechanisms
• Failure handling
• Pipeline observability (logs / artifacts)

4. Azure DevOps (Enterprise Awareness)

• Why enterprises use it
• Pipelines YAML overview
• Repo + Boards basics
• Comparison with GitHub Actions

Phase 3 — Cloud at Scale

1. Infrastructure as Code (Terraform)

• Declarative vs imperative
• Providers & resources
• Variables & outputs
• State:
  • why it exists
  • drift
• Modules:
  • structure
  • reusability
• Environment separation (workspaces)
• Best practices:
  • naming
  • versioning
• Remote backends
• Providers & modules registry

2. Kubernetes (Operational, Not Theoretical)

• Why Kubernetes exists
• Latest versions / migrations / upgrades (v1.35)
• Cluster architecture (high-level)
• Pods & controllers
• Deployments vs StatefulSets
• Services & networking
• Ingress
• ConfigMaps & Secrets
• Storage:
  • PVCs
• Reliability:
  • probes
  • resource limits
• kubectl:
  • describe
  • logs
  • exec
• Common failures:
  • CrashLoopBackOff
  • image pull errors
  • misconfigured services

3. Helm & GitOps

• Helm chart structure
• Values & templating
• Helm upgrades & rollbacks
• GitOps principles
• Argo CD:
  • sync
  • drift correction
  • rollback via Git
• End-to-end CI/CD pipelines

Phase 4 — Production Readiness

1. Observability

• Metrics vs logs vs traces
• RED & USE signals
• Alerting philosophy
• Prometheus basics
• Grafana dashboards
• Logging patterns
• OpenTelemetry:
  • why it exists
  • traces flow
  • debugging with data

2. DevSecOps (Practical Security)

• Secrets hygiene
• Image scanning
• Dependency awareness
• K8s RBAC basics
• Least privilege mindset
• Supply chain awareness (SBOM)

3. Incident Response & SRE Basics

• On-call responsibility
• Incident lifecycle
• Postmortems
• Runbooks
• Reliability mindset

4. Job Readiness

• Resume with engineering impact
• GitHub as portfolio
• Interview story building
• Debugging interviews
• System design basics (entry level)
• STAR method

Study Order

Follow the sidebar navigation — each section is ordered as a study path. Within each topic, notes go from basics to advanced.

Don’t skip Phase 1. Most DevOps engineers who struggle do so because they have gaps in Linux, networking, or Git fundamentals.