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Roadmap: DevOps and Platform Engineering

This document outlines the four learning phases in this topic, how this topic fits into broader learning paths, and what you can do after completing it.

Table of Contents

Learning Phases

This topic is organized into four progressive phases. Each phase builds on the previous and unlocks the next level of practice.

flowchart LR
    P1["Phase 1\nLinux + Containers\nModules 01–03"]
    P2["Phase 2\nKubernetes\nModules 04–05"]
    P3["Phase 3\nCI/CD + IaC\nModules 06–07"]
    P4["Phase 4\nAdvanced\nModules 08–12"]
    P1 --> P2 --> P3 --> P4

Four phases from foundational culture and Linux skills to full Platform Engineering capability.

Phase 1: Linux and Containers

Modules: 01 (Introduction), 02 (Linux and Shell), 03 (Containers)

Goal: Establish the cultural foundation and core operational building blocks. By the end of Phase 1 you can write bash scripts, manage Linux systems, build Docker images, and run multi-container applications locally.

Key skills unlocked: - Understanding DevOps culture and organizational dynamics - Linux filesystem, process, and user management - Bash scripting for automation - Docker image building, running, and registries - Docker Compose for local multi-service development

Checkpoint: Can you write a Dockerfile for a web application, build and push it to a registry, and run it locally with docker compose?

Phase 2: Kubernetes

Modules: 04 (Kubernetes Fundamentals), 05 (Kubernetes Advanced)

Goal: Move from running containers locally to operating them at scale in a cluster. By the end of Phase 2 you can deploy, scale, expose, and operate applications on Kubernetes with proper RBAC, networking policies, and custom operators.

Key skills unlocked: - Deploying and managing Pods, Deployments, and StatefulSets - Exposing services with Services and Ingress - Managing configuration with ConfigMaps and Secrets - Namespace-based multi-tenancy and RBAC - Horizontal and Vertical Pod Autoscaling - Custom Resource Definitions and Operator pattern

Checkpoint: Can you deploy a production-grade application on Kubernetes with proper RBAC, resource limits, health checks, and network policies?

Phase 3: CI/CD and Infrastructure as Code

Modules: 06 (CI/CD Pipelines), 07 (Infrastructure as Code)

Goal: Automate the path from code commit to production deployment, and describe all infrastructure in version-controlled code. By the end of Phase 3 you can build end-to-end CI/CD pipelines and provision cloud infrastructure using Terraform.

Key skills unlocked: - GitHub Actions and GitLab CI/CD pipeline design - Secrets management in pipelines - Environment-based deployments with approvals - Terraform provider, resource, state, and module management - Drift detection and infrastructure testing - IaC best practices (DRY, module boundaries, state isolation)

Checkpoint: Can you write a complete CI/CD pipeline that builds, tests, scans, and deploys an application, with infrastructure provisioned via Terraform?

Phase 4: Advanced

Modules: 08 (Observability), 09 (GitOps and Delivery), 10 (Platform APIs and IDP), 11 (Security and Compliance), 12 (Capstone Project)

Goal: Master the advanced disciplines that separate good practitioners from elite ones — deep observability, GitOps-based delivery, Internal Developer Platforms, and supply chain security. Culminates in the Capstone Project where you build a real IDP.

Key skills unlocked: - Prometheus metrics and Grafana dashboards - OpenTelemetry distributed tracing - SLO/SLI definition and alerting - ArgoCD and Flux GitOps workflows - Progressive delivery (canary, blue-green, Argo Rollouts) - Backstage service catalog and scaffolding - SBOM generation, Cosign image signing, Trivy scanning - OPA/Gatekeeper policy enforcement - HashiCorp Vault secrets management

Checkpoint: The Capstone Project — design and implement a complete IDP.

Where This Topic Leads

After completing this topic, you are ready for:

  • [[networks]] — deep networking knowledge is required for advanced Kubernetes networking, service mesh configuration, and eBPF-based observability
  • [[qa-testing]] — advanced testing in the pipeline: contract testing, chaos engineering integration, load testing in CI
  • [[feature-flags-monitoring]] — production-level feature management: experimentation platforms, gradual rollouts, and A/B testing infrastructure

Career paths this topic enables: - DevOps Engineer / DevOps Lead - Platform Engineer / Staff Platform Engineer - Site Reliability Engineer (SRE) / Senior SRE - Cloud Infrastructure Engineer - Software Architect (cloud-native focus)