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DevOps Engineer Roadmap 2026

DevOps is a broad field spanning many tools -- this roadmap orders them by what actually depends on what, not by hype.

Stage 1: Linux and Networking Fundamentals (3-4 weeks)

  1. The Linux filesystem, permissions, and core CLI tools
  2. Process management and systemd basics
  3. Core networking concepts -- DNS, HTTP, TCP/IP, load balancing
  4. Example: set up and secure a fresh Linux VPS from scratch, by hand, before automating any of it

Stage 2: Scripting and Version Control (2 weeks)

  1. Bash scripting for automation tasks
  2. Python basics for more complex tooling scripts
  3. Git workflows -- branching, merging, pull requests
  4. Example: write a bash script that automates the manual server setup from Stage 1

Stage 3: Containers (3-4 weeks)

  1. Docker -- images, containers, Dockerfiles, multi-stage builds
  2. Docker Compose for local multi-container development
  3. Container registries and image versioning
  4. Example: containerize a real application (even a simple one) with a proper multi-stage Dockerfile

Stage 4: CI/CD (2-3 weeks)

  1. CI/CD concepts -- build, test, deploy pipelines
  2. A tool like GitHub Actions, GitLab CI, or Jenkins
  3. Automated testing as a pipeline gate
  4. Example: set up a pipeline that automatically builds, tests, and deploys the containerized app from Stage 3 on every push

Stage 5: Orchestration and Infrastructure as Code (4-6 weeks)

  1. Kubernetes fundamentals -- pods, deployments, services, scaling
  2. Terraform for provisioning cloud infrastructure declaratively
  3. Configuration management concepts (Ansible or similar)
  4. Example: deploy the app to a managed Kubernetes cluster, with its infrastructure defined in Terraform

Stage 6: Monitoring and Cloud Platform (3-4 weeks)

  1. Deep expertise in one cloud provider (AWS, Azure, or GCP)
  2. Monitoring and alerting -- Prometheus and Grafana, or a cloud-native equivalent
  3. Centralized logging
  4. Example: add monitoring dashboards and alerts for the deployed app's health and resource usage

Frequently Asked Questions

It helps significantly -- understanding how applications are actually built and what they need to run reliably makes you far more effective at automating and troubleshooting deployments. Many DevOps engineers do start as backend or systems engineers before specializing.
Always after -- Kubernetes orchestrates containers, so you need to genuinely understand what a container is and how to build one well before layering orchestration concepts on top. Skipping straight to Kubernetes without solid Docker fundamentals makes everything harder to debug.

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