DevOps and cloud engineer
Learn to build, ship and run software on AWS the way a DevOps team does, working with AI coding tools from week 1 and running AI workloads by the end, in 24 weeks.
Coming soon · planned, not written yet
DevOps and DevSecOps both have their own role roadmaproadmap.sh
- 24
- weeks planned
- ~40 h
- a week
- 6
- milestone projects
- 1
- project, grown every week
These are planned figures. The weeks are written after we check the tools against current job postings and official documentation, so the final route may differ.
Built for the AI era
How AI fits this roadmap
AI coding assistants now write much of the pipeline code, Terraform and shell scripts that DevOps engineers used to type by hand. That moves the job toward reviewing, testing and owning what ships, so this roadmap teaches you to use an AI assistant every week and to check its output with plans, linters, scanners and tests. In the later weeks you also deploy and monitor a small AI service, because some DevOps postings now ask for AI-assisted tooling and for running AI services, and you can show you have done it.
The main project
ShipLine
A small web service with an AI-backed feature that you move from your laptop to a monitored, automatically deployed production setup on AWS.
What you will be able to do
- 01
Work in Linux, Git and the command line, and script routine jobs with an AI assistant while reading and fixing every line it writes.
- 02
Package the service with Docker and ship every change through a CI/CD pipeline that builds, tests and publishes it.
- 03
Define the AWS setup as code with Terraform, and review each plan before applying it, including plans an AI assistant drafted.
- 04
Run the service on Kubernetes with Git-driven, reversible deployments, and watch it with metrics, logs, traces and alerts.
- 05
Deploy and monitor a small AI-backed service, add scanning and least-privilege access, and write up one incident review.
01The route
Six months, one month at a time.
Each month ends in a milestone project, so you always have something to show for the work.
Month 1 · Weeks 1–4
Linux, Git, scripting and AI-assisted work
The command line, processes and networking, Git workflows and shell and Python scripting. You set up an AI coding assistant and learn to prompt it, read its diffs and test what it writes.
MilestoneA small service and its scripts, buildable and testable from one command, with a log of AI suggestions you accepted and rejected
Month 2 · Weeks 5–8
Containers and CI/CD
Docker images and Compose, then automated builds, tests and releases with GitHub Actions. You use AI to draft pipelines and Dockerfiles, then fix what is wrong with them.
MilestoneEvery push builds, tests and publishes a container image
Month 3 · Weeks 9–12
AWS and infrastructure as code
Core AWS services, networks and permissions, and Terraform to create all of it from code. You learn to review plans line by line and to spot AI-written config that is too open.
MilestoneThe service running on AWS, created entirely by Terraform and reviewed by plan
Month 4 · Weeks 13–16
Kubernetes and delivery
Run the service on Kubernetes, manage configuration and secrets, and deploy from Git with Argo CD. You practise rollbacks and use AI to explain failing pods, then confirm the cause yourself.
MilestoneAutomated, reversible deployments to a cluster, driven from a Git repository
Month 5 · Weeks 17–20
Observability, security and AI services
Metrics with Prometheus, traces and logs with OpenTelemetry, alerts, and image scanning with Trivy. You add an AI-backed feature to ShipLine and watch its cost, errors and slow calls.
MilestoneDashboards, alerts and security checks around the live service, including its AI feature
Month 6 · Weeks 21–24
Reliability, capstone and job search
Incident practice with an AI-assisted timeline you verify, cost control, a portfolio write-up, interview preparation and applications.
MilestoneA portfolio, one incident review and a working job-search pipeline
03What is inside
Everything a week comes with.
Every week is built the same way, so once you have done one you know how all of them work.
- 01
One project, ShipLine
You grow one service from laptop to production, with an AI feature inside it, so every tool lands in something real.
- 02
A day-by-day plan
Each week has a Learn part and a Do part, with a checklist so you know when you are done. Most weeks include a task to do with an AI assistant and a step to check its work.
- 03
A project in every milestone
Six milestones, each ending in something you can show and link to.
- 04
Reference topics
Short topic pages with check questions you can come back to.
- 05
A job track
Interview practice, portfolio and resume help, and an application plan.
- 06
Progress in your Study plan
Add weeks to your Study plan, give them dates, and finished days are counted for you.
04Is it for you
Who this is, and is not, for.
Better to know before you start than six weeks in.
It is for you if
- You can write small programs in some language and want to work on deployment and infrastructure.
- You are a developer, tester or system administrator moving into DevOps and want to be strong with AI tools.
- You can give about 40 hours a week for six months.
It is not for you if
- You have never written code or used a terminal. Do a beginner course first.
- You want a job guarantee. Nobody can promise that, and this roadmap does not.
- You want deep Kubernetes administration or a full security career. Separate roadmaps will cover them.
- You want to paste AI output into production without reading it. This roadmap trains you to check it.
?Questions
Before you start
- Is this roadmap ready?
- Not yet. This is the plan. The weeks are being written and checked against current job postings and official documentation. Leave your email and we will write to you when it opens.
- What will it cost?
- The price is not set. Roadmaps are bought once, with no subscription. We will announce it when this one opens.
- Will the plan change?
- It may. Before the weeks are written we check the tools against current job postings, so the lengths and months here are planned, not final.
- Do I need an AWS account and a paid AI tool?
- Later, yes for AWS. The cloud weeks will use a free or low-cost account, and the roadmap will show how to keep the bill small. For AI, the roadmap will use an AI coding assistant and will say which parts work on a free plan once the weeks are written.
- Will it get me a job?
- It will give you skills and proof of work. It cannot promise a job on a fixed date, because hiring depends on the market, your location and your past work.
Not open yet
Leave your email and we will write once, when it opens.