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In production we need to interact with Linux operating system mainly ubuntu so it would be good to get adapted to this ecosystems . I recommend you to use the Terminal more now even if you are on window Install WSL in your system you will get ubuntu and use the bash you can customise your shell as per your convience , personally i have been using zsh with oh my zsh it give nice and easy user experience
# Taking First Step
**Learning DevOps Tools in the Right Order**
There are hundreds of tools in the DevOps ecosystem. The challenge is not learning everything, but **learning in the right order** so your foundation stays strong.
Here’s a practical learning path that actually aligns with real engineering workflows:
### **1) Git + GitHub**
Start version-controlling every project you build.
> **Rule:** Push all your code to GitHub. Keep every project well-maintained.
Why it matters:
* Collaborating with code becomes easier
* You learn branching, merging, and pull requests
* It builds your portfolio naturally
**Key Skills to Learn**
* git init, git clone, git status
* git add, git commit, git push
* Branching & Pull Requests
### **2) Linux Basics + Shell**
Linux is the backbone of servers and cloud machines.
When you work inside the cloud, you interact through a terminal, so Linux knowledge is non-negotiable.
> **Recommendation:** Learn a terminal editor like `vim` or `nano`.
> When you SSH into a server, you won’t have VS Code waiting for you.
**Key Concepts**
* File system navigation (cd, ls, rm, mv, cp)
* Permissions & users
* System services & processes
* Networking basics (ping, curl, netstat)
### **3) Choose a Cloud Provider**
After Linux, pick one cloud to start with.
> For beginners, **AWS is highly recommended** because it’s widely used in the industry and has tons of documentation.
Use your Linux skills and start doing practical exercises, like:
* Creating EC2 instances
* SSH into instances using keys
* Hosting simple apps
The goal is to connect Linux knowledge with real cloud servers.
### **4) Docker (Containerization)**
Now that you can deploy on the cloud, learn how to deploy efficiently with containers.
Why Docker?
* Reproducible environments
* Works the same on local + cloud
* Makes CI/CD sooo much easier
**Learn**
* Dockerfile
* Images, containers, volumes, networks
* Tagging & pushing images to Docker Hub
### **5) CI/CD (GitHub Actions)**
Once you know Docker, automate builds and deployments.
> CI/CD is not theory. You must build pipelines that test and deploy your apps automatically.
Start with **GitHub Actions**, then explore others later.
**Important Concepts**
* Build pipelines
* Deploy pipelines
* Secrets management
### **6) Terraform (Infrastructure as Code) (this for now you can skip and can jumps back later after learning )**
Instead of manually creating servers on AWS, automate it.
**Terraform teaches you:**
* Declarative infra provisioning
* Reusability with modules
* Working with multi-cloud setups
You should be able to:
* Create VPC, EC2, IAM
* Use Terraform variables & outputs
* Store state securely (S3 + DynamoDB)
### **7) Kubernetes (Orchestration)**
Once you understand Docker, learn how to scale containers.
> Kubernetes = Running containers at scale.
Focus on:
* Pods, Deployments, ReplicaSets
* Services & Ingress
* ConfigMaps & Secrets
* Helm (bonus)
Make sure you run apps locally using kind kubectl or Kubernetes on cloud (EKS/GKE).
### **8) Observability (Prometheus + Grafana)**
If you deploy apps, you must monitor them.
**Observability includes:**
* Metrics
* Logs
* Tracing
Prometheus helps collect metrics
Grafana visualizes them
Learn how to:
* Monitor applications
* Create dashboards
* Set up alerts
### **9) DevSecOps Basics (Trivy + Vault)**
Security should never be an afterthought.
**Start with simple tools:**
* **Trivy** → Scan vulnerabilities
* **Vault** → Manage secrets
Use Trivy to scan:
* Docker images
* Kubernetes workloads
* Repositories
Use Vault to store secrets securely.
## TLDR
The article provides a comprehensive guide for learning DevOps, starting with understanding the reasons for choosing this path. It emphasizes the importance of coding skills, particularly in shell scripting and Python. The learning journey includes mastering Git and GitHub for version control, Linux basics, choosing a cloud provider like AWS, learning Docker for containerization, and setting up CI/CD pipelines with GitHub Actions. It also covers advanced topics like Terraform for infrastructure as code, Kubernetes for container orchestration, observability with Prometheus and Grafana, and DevSecOps basics with tools like Trivy and Vault.