Become a job-ready DevOps Engineer in 4 months

By the end of this phase, every student can set up and SSH into a real EC2 Linux server, and understands exactly how requests travel across a network — the foundation every later phase builds on.

Every production incident starts with “can we SSH into the box?” — this is the phase that teaches you to set up, secure and troubleshoot that server before touching any higher-level tool.

By the end of this phase, every student can administer a real Linux server end to end and manage code with the same Git workflows professional engineering teams use daily.

Every CI/CD pipeline and every production server comes back to these two skills — a DevOps engineer who can't administer Linux or manage Git branches confidently can't do the job.

By the end of this phase, every student has containerized a real multi-service application end to end — from a Dockerfile to a Docker Compose stack pushed to Amazon ECR.

“It works on my machine” stops being a problem the moment an app is containerized — this is the exact skill every job posting means by “Docker experience”.

By the end of this phase, every student has built a real CI/CD pipeline, then deployed their first application onto a Kubernetes cluster they set up themselves.

This is the exact workflow behind every “push to deploy” setup — a Jenkins or GitLab pipeline that tests, builds and ships your app onto Kubernetes automatically, every time you commit.

By the end of this phase, every student can deploy a production-grade application on AWS EKS with automated security scanning built directly into the pipeline.

Modern hiring teams expect security scanning inside the pipeline, not bolted on afterward — this phase is what lets you say “DevSecOps” on a resume and back it up in an interview.

By the end of this phase, every student can provision real AWS infrastructure with a few lines of code, then configure it automatically — the exact skillset behind every “infrastructure as code” job listing.

Spinning up a server by hand in the AWS console doesn't scale past a handful of machines — Terraform and Ansible are how real teams provision and configure hundreds of servers identically, every time.

By the end of this phase, every student is fluent across the core AWS services real job postings ask for, with a full observability stack monitoring everything they've built.

A deployment that isn't monitored is a production incident waiting to happen — Prometheus, Grafana and Loki are the exact stack behind the alerts and dashboards every on-call DevOps engineer relies on.

Every student integrates their capstone work into one project — infrastructure provisioning, CI/CD implementation, containerization, Kubernetes deployment and monitoring integration, all combined — the same stack real DevOps teams run in production.