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LEARNING PATH · Systems & Backend

From Sysadmin to DevOps / SRE

For system administrators moving into DevOps, SRE, or platform engineering.

Beginner ~1h 45m6 lessons6 steps

A persona-framed re-sequence that starts from the Linux and operations you already know, adds containers, Git, and infrastructure-as-code thinking, and threads through the DevOps, SRE, and platform-engineering roadmaps — the honest route from keeping servers alive to engineering the platform.

  • Build on the Linux and operations knowledge you already have
  • Add containers, Git workflows, and automation as your turning point
  • Move from managing servers to engineering the platform
  • Understand how AI (AIOps) reshapes operations work
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  1. RoadmapNext up

    DevOps Roadmap

    Your destination map — start from the ops and Linux you already know.

  2. Roadmap

    Cloud / AWS Roadmap

    The cloud foundation devops runs on — build it out.

  3. Roadmap

    SRE Roadmap

    Where reliability engineering takes the ops mindset next.

  4. Roadmap

    Platform Engineer Roadmap

    The platform-engineering evolution — build the paved road.

  5. Handbook

    The AI-Era DevOps Engineer

    How AI and AIOps change operations — and what stays human.

  6. Handbook

    The Resume & Portfolio Handbook

    Present the shift from admin to engineer with real automation work.

How this path works

This path is for system administrators, IT operations staff and support engineers who already keep servers, networks and services running and want to move into DevOps, site reliability engineering (SRE) or platform engineering. You probably know Linux, troubleshooting under pressure and what it feels like to be paged. That knowledge is the foundation, not something to leave behind.

What changes is the way of working. Interviews for DevOps and platform roles tend to ask how you automate repeatable work, how you describe infrastructure as code, how you build and release safely, how you observe a running system, and how you handle an incident and learn from it afterward. They also ask for evidence that you can write scripts and read other people's code.

The path is short, because each step is a full roadmap. Start with the DevOps roadmap, whose stations include Linux and the shell, Git, Docker, infrastructure as code, Kubernetes and observability. Then fill the cloud gap, follow the reliability branch into SRE, and the platform branch into internal developer platforms. A handbook on AI-era operations shows what is changing, and a resume step helps you present the move as engineering.

What each step gives you

  1. DevOps Roadmap

    Eighteen stations in three tracks: foundations (Linux and the shell, networking, Git, Docker, cloud, scripting), core DevOps (CI/CD, infrastructure as code, configuration management, Kubernetes, secrets, registries) and production (observability, GitOps, incident response, SLOs, networking at scale, cost). Mark the stations you already know and begin with the ones that feel unfamiliar, usually Git workflows and containers.

  2. Cloud / AWS Roadmap

    A map of cloud engineering on AWS: compute, storage, networking in a VPC, identity, databases, then serverless, containers, infrastructure as code, observability and messaging, and finally the Well-Architected Framework, security, multi-region availability and cost. If your experience is on-premises hardware, this is where shared responsibility, IAM and VPC design translate your network and server knowledge.

  3. SRE Roadmap

    The reliability branch: the SRE mindset, Linux and systems, distributed systems, then SLIs, SLOs and error budgets, alerting, incident response, blameless postmortems, capacity planning, chaos engineering and toil elimination. Your on-call history is relevant. Read it to learn the vocabulary for what you already did, and to see which practices, such as error budgets, you have not used.

  4. Platform Engineer Roadmap

    The platform branch moves from running servers to building a paved road for other engineers: Kubernetes, infrastructure as code, CI/CD and GitOps, observability, platform security, internal developer platforms and treating the platform as a product. Use it to see whether you prefer serving developers with tooling, and to plan which stations to build projects around.

  5. The AI-Era DevOps Engineer

    Argues that pipeline YAML, Dockerfiles, shell scripts and boilerplate infrastructure code are getting cheap, while reviewing changes for blast radius, tuning noisy alerts and building golden paths are becoming scarce. Five exercises include auditing an AI-written infrastructure change. It prepares you for interview questions on using AI safely around production systems.

  6. The Resume & Portfolio Handbook

    Shows how an applicant tracking system scores a resume before a person reads it and what the human wants to see. For an administrator the main change is to express past work as engineering: systems automated, incidents reduced, runbooks turned into code. Add a public repository with infrastructure code and a short write-up of how you tested it.

A study plan

  1. Weeks 1–2

    Read the DevOps Roadmap and mark every station. Pick three unfamiliar ones, typically Git workflows, containers and CI, and build a small pipeline that tests, packages and deploys a sample application to a cheap virtual machine.

  2. Weeks 3–4

    Rebuild part of your usual environment as code: a repeatable server setup with a version-controlled configuration. Then read the Cloud and AWS Roadmap and recreate the same setup in a cloud account with a budget alert on.

  3. Weeks 5–6

    Read the SRE Roadmap. Write service level objectives for something you run, add monitoring that alerts on them, and write a blameless postmortem for a past outage you remember well, as practice.

  4. Weeks 7–8

    Read the Platform Engineer Roadmap and The AI-Era DevOps Engineer handbook. Package your pipeline as a reusable template that another person could adopt, then update your resume following the Resume and Portfolio Handbook.

Questions about this path

How do I move from sysadmin to DevOps?

Keep your operational knowledge and add automation. Learn Git and use it for everything, containerize an application, write a pipeline that builds and deploys it, and describe infrastructure in code instead of clicking through consoles. Then practice observability and incident handling, since you already understand failure. Build one or two projects that show these skills end to end, and describe them in engineering terms. The DevOps roadmap in this path lists the stations in a sensible order.

What is the difference between DevOps, SRE and platform engineering?

The titles overlap, and companies use them differently. DevOps is a way of working that joins development and operations through automation and shared ownership. SRE applies software engineering to reliability, using service level objectives, error budgets and postmortems. Platform engineering builds internal tools and paved roads so developers can ship without handling infrastructure details. Read the job description rather than the title, and use the three roadmaps here to see which responsibilities appeal to you.

Do I need to learn programming to become a DevOps engineer?

Yes, at a practical level. You should be able to write scripts in a language such as Python or Go, read application code, and work with data formats like YAML and JSON. You do not need to be a product developer, but interviews often include a coding or scripting task and questions on automation. Start by replacing your repetitive shell tasks with tested scripts kept in version control, then move to larger tools.

Will AI replace DevOps and operations jobs?

AI is making routine artifacts such as pipeline files, Dockerfiles and basic scripts cheaper to produce, so work built only on those is exposed. Judgment about blast radius, reliability trade-offs, incident response and security is harder to hand off, and reviewing AI-written infrastructure changes is becoming part of the job. Nobody can predict exactly how roles will shift, so build the skills that remain valuable and use AI tools with careful review.

Sysadmins have exactly what DevOps and SRE are built on: real understanding of how systems run, fail, and recover in production. The transition isn’t starting over — it’s adding the automation, containers, and infrastructure-as-code that turn manual operations into engineered platforms. This path re-sequences the site’s assets around that persona so each step builds on your existing strength.

You start at the DevOps roadmap, whose stations cover the Linux and shell you already use, containers, Git and infrastructure as code, then the cloud foundation it runs on. Then it points at where the role grows — SRE and platform engineering — and the AI era, where AIOps automates the toil but the judgment about reliability, incidents, and trade-offs stays human. It finishes on presenting yourself as the engineer, not the admin.

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