Enhancing my DevOps skills by turning guided projects into production-style systems
I work hands-on with containerization, deployment, and Linux workflows, and I'm now extending those foundations into Kubernetes orchestration, CI/CD automation, and infrastructure as code.
- Linux: daily driver for navigation, observability, networking, and automation (see my fieldbook below)
- Containers: Docker (Node, Python Flask, Java, ML apps)
- Orchestration: Kubernetes (pods, deployments, services, cluster setup)
- Automation: CI/CD concepts, GitHub Actions (in progress), Bash scripting
- Cloud & IaC: AWS basics, Terraform (learning)
- Analytics side: Power BI dashboards
I got tired of hunting the same answers, so I wrote them down once, properly:
1. Linux Command Fieldbook Linux from first principles — not a command list, a map for operating a machine at 2am. Organized into 4 pillars: Navigation & Manipulation, System Observability, Networking & Security, Automation. Every command includes the GUI equivalent and why it matters in production. → github.com/rahul7528/linux-command-fieldbook
2. Kubernetes with Chai Kubernetes for absolute beginners, explained twice: once properly, once with a chai shop analogy. Covers Images, Containers, Pods, Nodes, Deployments, Services, ConfigMaps, Secrets, Ingress and how the control plane actually works. → github.com/rahul7528/kubernetes-with-chai
I built these because I struggled to find simple, real-world explanations. If they save you time, star them.
Kubernetes Cluster Demo — hands-on with pods, deployments, services → repo
Two-Tier Flask Application — structured backend, ready for DB integration → repo
Dockerized Apps — Node Todo, Flask, Java, ML Hello (multi-language packaging practice) → Node • Flask • Java • ML
- Connecting apps to Kubernetes with Helm and GitOps (ArgoCD)
- Building end-to-end CI/CD pipelines
- Terraform modules for AWS infrastructure
- Adding monitoring and log rotation to existing projects
Contact: LinkedIn • fd.rahulchawla@gmail.com