Build practical DevOps judgment across 30 challenge labs that move from everyday Linux operations to automation, service delivery, observability, CI/CD, infrastructure as code, Kubernetes, and Python operations. Each challenge gives you an operational target—such as recovering a failed service, securing a web server, or restoring a Kubernetes application—and asks you to reach and verify the required state.
This is an intermediate practice path, not a command-by-command tutorial. Early challenges reinforce essential Linux skills before later work combines configuration, troubleshooting, and automation across common DevOps tools.
What You Will Learn
By completing the six stages, you will learn to:
- Navigate and organize Linux systems while managing configuration files, pipelines, users, groups, and permissions.
- Diagnose runaway processes, disk pressure, network-versus-service failures, and broken systemd services using system evidence.
- Automate recurring operations with Bash scripts, archives, traps, cron, one-time jobs, and Git-managed configuration.
- Operate Docker, MySQL, Nginx, BIND DNS, and firewalld through deployment, migration, access-control, and hardening tasks.
- Improve service reliability with Ansible, HAProxy health checks, and Keepalived service-aware failover logic.
- Configure Prometheus metrics and alert rules, then use Promtail, Loki, and LogQL to investigate an application error spike.
- Define a GitHub Actions workflow, use Terraform modules, and deploy, update, roll back, and repair Kubernetes workloads.
- Write a Python health-check utility that combines disk and HTTP checks into a structured JSON report with error handling.
Who This Course Is For
This course is for learners who already know basic Linux commands and want scenario-based practice across the breadth of a DevOps or junior SRE role. It is especially useful if you have studied individual tools but need practice deciding what to inspect, change, and verify without a fully guided walkthrough.
Prerequisites: You should be comfortable navigating a Linux terminal, editing text files, using sudo, and reading basic command output. Familiarity with shell scripting, networking, Git, containers, and YAML will make the later challenges more approachable, but the course begins with simpler Linux operations before building toward them.
Learning environment: All challenges run in provided Ubuntu-based lab environments with the required services, binaries, starter files, and local infrastructure. You will work mainly in the terminal, with browser access available for the Prometheus and Node Exporter services where relevant.
Frequently Asked Questions
Is this a guided DevOps course or a challenge course?
It is a challenge course. Each lab supplies a scenario, tasks, requirements, hints, and validation, but you are expected to choose and apply the commands or configuration changes yourself. If you are completely new to Linux, a guided Linux or DevOps fundamentals course is a better first step.
Do I have to complete exactly one challenge per day?
No fixed calendar is enforced. The 30 challenges are arranged as a progressive 30-day practice route, so you can complete one per day or work at another pace. Following the stage order is recommended because later challenges combine skills introduced earlier.
Do the cloud-native challenges require a GitHub account or paid cloud resources?
No. You author a GitHub Actions workflow inside the lab, its deployment job is simulated, and the Terraform challenge uses a local module rather than provisioning a public cloud. Kubernetes work also runs in the supplied lab cluster, so no external cloud account or billable infrastructure is required.
Will this course make me an expert in every tool it covers?
No. The course is deliberately broad and uses focused operational scenarios to test transferable troubleshooting and delivery skills. It is best for building confidence across a DevOps workflow and identifying which areas—such as Kubernetes, observability, or automation—you want to study in greater depth next.
