Starting My GitHub Actions Journey with DevOps

🚀 Learning GitHub Actions & CI/CD in Public Today I practiced building CI/CD workflows using GitHub Actions as part of my DevOps learning journey. Here’s what I implemented: ✅ Created workflows triggered on push and pull requests ✅ Built a multi-stage CI/CD pipeline (Code → Build → Test → Deploy) ✅ Learned how job dependencies work using needs ✅ Added scheduled workflows using cron syntax ✅ Understood how PR checks help maintain code quality It feels great to move from theory to hands-on practice and understand how real automation pipelines work. Next goal: Integrating Docker build and deployment steps into the pipeline. #DevOps #GitHubActions #CICD #Docker #Automation #LearningInPublic #Cloud #Monitoring

30 Days DevOps Revision Challenge – Day 3 Day 3 of my DevOps revision challenge — and today I started revising Terraform. After spending the first two days deeply focused on Jenkins, I decided to shift towards Infrastructure as Code (IaC) — which is a very important part of building production-ready systems. 📌 Day 3 Focus: Terraform (Revision Started) Today was more about getting back into Terraform and rebuilding the foundation. I didn’t complete the full revision yet, but I made a solid start. Here’s what I covered: 🧱 Basics of Infrastructure as Code (IaC) Why IaC is important in modern DevOps Benefits like automation, consistency, and scalability 📂 Terraform Fundamentals Understanding providers, resources, and blocks Writing basic .tf configuration files ⚙️ Terraform Workflow terraform init terraform plan terraform apply terraform destroy 📦 Providers & Resources Explored how Terraform connects with cloud platforms (like AWS) Created and managed basic resources 🗂️ State Management (Intro) Understood what Terraform state is Why state file is important 🔄 Variables & Outputs (Basic Level) Started working with input variables Learned how to use outputs 💡 Current Status Today was not about finishing everything — it was about rebuilding the base. Terraform is a vast tool, and I want to make sure I understand it properly instead of rushing through it. 🎯 What’s Next (Day 4 Plan) Deep dive into state management (remote state, locking) Modules and reusable infrastructure Best practices for writing clean Terraform code Try some real-world infra setup This journey is helping me realize that real growth comes from consistent, step-by-step improvement, not rushing. I’ll continue sharing my progress daily 💯 If you’re also learning DevOps or Terraform, let’s connect 🚀 #DevOps #30DaysChallenge #Terraform #InfrastructureAsCode #AWS #LearningInPublic #Consistency #TechJourney

🚀 Day 7 of My DevOps Journey — GitHub Webhooks (Real-Time CI/CD) Until now, I was triggering Jenkins pipelines manually. Today, I automated the trigger itself. 👉 Push code → Pipeline runs automatically This is what real DevOps looks like. 🔹 What I Practiced: - Setting up GitHub Webhooks - Connecting GitHub → Jenkins - Configuring webhook triggers in pipeline - Testing end-to-end automation 🔹 Mini Project: I implemented a real-time CI/CD flow: ✔ Pushed code to GitHub ✔ Webhook triggered Jenkins build instantly ✔ Pipeline executed automatically ✔ Docker image built & deployed No manual steps. Fully automated 🔥 🔹 Real Issues I Faced: ❌ 403 error (No valid crumb included) ❌ 400 error (Bad webhook request) 🔹 How I Fixed It: ✔ Configured Jenkins security settings (CSRF / crumb issue) ✔ Verified webhook URL & payload ✔ Used tools like ngrok for local webhook testing 💡 Key Learning: “DevOps is not about speed — it’s about automatic reliability.” Now I understand: - Event-driven automation - How real CI/CD pipelines are triggered - Importance of secure integrations Next → AWS EC2 Deployment (taking pipelines to cloud ☁️) If you're building in DevOps, let’s connect 🤝 #DevOps #Webhooks #Jenkins #CICD #Automation #Cloud #AWS #LearningInPublic

Getting Started with GitHub Actions – My First Steps I recently started working with GitHub Actions and wanted to share a quick beginner-friendly overview for anyone getting started in DevOps or CI/CD. 🔹 What is GitHub Actions? GitHub Actions is a CI/CD tool that allows you to automate workflows directly from your repository. 🔹 Basic Concepts: • Workflow → Defined in .github/workflows/ • Events → Trigger (push, pull_request, etc.) • Jobs → Set of tasks running on a runner • Steps → Individual commands inside a job 🔹 Simple Example Workflow: name: CI Pipeline on: push: branches: [ "main" ] jobs: build: runs-on: ubuntu-latest steps: - name: Checkout code uses: actions/checkout@v3 - name: Run a script run: echo "Hello, GitHub Actions!" 🔹 Why use GitHub Actions? - Seamless GitHub integration - Easy automation - Supports multiple environments - Great for CI/CD pipelines This is just the beginning. The next step is integrating with Docker, AWS, and Terraform #DevOps #GitHubActions #CICD #Automation #Cloud #AWS

DevOps Journey - Week 9 🚀 This week learning session was intense. I spent the whole week deep in DevOps, and I can honestly say my understanding leveled up. I worked through real hands-on infrastructure automation and provisioning, including: Terraform state, outputs, and variables Git versioning for Terraform projects Provisioning AWS infrastructure from scratch Building a custom VPC, subnet, route table, internet gateway, and security groups Automating EC2 provisioning with Terraform SSH key automation Bootstrapping servers with user data scripts Installing Docker automatically and running Nginx on EC2 What I love most is that this is not just theory. It is real-world DevOps engineering work. A big highlight of this journey is learning through Nana Janashia’s DevOps Bootcamp. Her teaching style makes complex DevOps concepts practical, structured, and understandable, especially when moving from “just watching” to actually building. One of the biggest lessons for me this week: Terraform is powerful for provisioning infrastructure, but knowing where Terraform stops and where tools like Ansible begin is part of becoming a real DevOps engineer. Step by step, skill by skill, project by project. #DevOps #Terraform #AWS #EC2 #CloudComputing #InfrastructureAsCode #Docker #TechLearning #CloudEngineer #Jenkins #Kubernetes #NanaJanashia #DevOpsBootcamp #LearningJourney

🚀 Terraform Commands Explained for Beginners | My Learning Journey Starting my journey in DevOps & Infrastructure as Code, I recently explored the core Terraform commands that every beginner should know. Sharing this simple breakdown for anyone getting started 👇 🔹 terraform init Initialize your project – downloads providers & sets up the environment 🔹 terraform validate Checks your code – ensures syntax & structure are correct 🔹 terraform plan Preview mode – shows what changes Terraform will make 🔹 terraform apply Execution step – actually creates or updates infrastructure 💡 Simple Workflow: init → validate → plan → apply This flow helps avoid mistakes and gives full visibility before making any real changes to infrastructure. If you're starting with Terraform, always remember: 👉 Never skip plan before apply Let’s keep learning and growing together 💪 #Terraform #DevOps #CloudComputing #InfrastructureAsCode #LearningJourney #Azure #BeginnerFriendly

🚀 Stop Struggling with YAML — Learn It Once for Docker & Kubernetes Most DevOps beginners jump directly into Docker & Kubernetes… and then get stuck. Not because the tools are hard — but because YAML isn’t clear. I’ve created a practical, no-fluff guide to help you: ✅ Understand YAML with real DevOps examples ✅ Read Docker Compose files confidently ✅ Decode Kubernetes manifests easily ✅ Avoid common mistakes (indentation 😅) If YAML finally “clicks” for you, everything in DevOps starts making sense. 👉 Read here: https://lnkd.in/dDm74HHN 💡 Save this post — you’ll need it every time you work with YAML. And tell me in comments: What should I cover next — Docker or Kubernetes? #DevOps #YAML #Docker #Kubernetes #CloudComputing Atharva System

🚨 DevOps Lesson Learned the Hard Way: Terraform + Kubeconfig = Be Careful Today I ran into a situation that every DevOps engineer thinks won’t happen to them… until it does 😅 While troubleshooting federated credentials, I switched contexts between Stage and UAT environments in AKS. Everything looked fine — until I ran a terraform destroy for Stage… 👉 But my kubeconfig was still pointing to UAT 💥 Result: Terraform operated on the wrong cluster. What went wrong? Even though I passed Stage variables in Terraform: aks_name = stage rg_name = stage-rg 👉 Terraform didn’t care. It used the current-context from kubeconfig, which was still set to UAT. 🧠 Key takeaway Terraform Kubernetes provider follows kubeconfig context — NOT your variables 🛡 How I’m fixing this (and you should too) ✅ Use separate kubeconfig files per environment (e.g., uat-config, stage-config) ✅ Explicitly define context in Terraform: config_context = "aks-stage" ✅ Add a safety check before running destructive commands: kubectl config current-context ✅ Avoid using default ~/.kube/config in automation Final thought In DevOps, most failures are not tool issues — they’re context mistakes. This was a reminder that: “Automation is powerful… but only as safe as the context you run it in.” #DevOps #Terraform #Kubernetes #AKS #Cloud #SRE #LessonsLearned #Azure

🚀 My Latest Project Learning: Cloud DevOps Architecture on Azure with Kubernetes 🔷 Excited to share insights from my recent project where we are migrating applications from AWS to Azure using modern cloud-native and DevOps practices. 🔹 Architecture Overview: We are containerizing microservices and deploying them on Azure Kubernetes Service (AKS), enabling scalability, flexibility, and efficient resource utilization. 🔹 GitOps Approach: We follow a GitOps model where the entire source code, Helm charts, and configurations are maintained in a Bitbucket repository, ensuring version control and consistency. 🔹 CI Pipeline: Using Bamboo pipelines, every code push triggers: ✔️ Build with Apache Maven ✔️ Unit testing ✔️ Docker image creation Images are stored in Quay, while build artifacts (JAR files) are securely managed in JFrog Artifactory. 🔹 Deployment Strategy: We leverage Helm for Kubernetes templating with a reusable chart design. Each microservice has its own values.yaml, and currently, we manage ~20 microservices efficiently. 🔹 GitOps Deployment: Argo CD ensures automated, consistent, and drift-free deployments by pulling configurations from Bitbucket and deploying them to AKS. 🔹 Infrastructure as Code: Using Terraform, we provision and manage Azure infrastructure, including AKS clusters and networking components. 🔹 Security: We integrate HashiCorp Vault for secrets management. Secrets are dynamically fetched and injected into Kubernetes, ensuring sensitive data is never stored in code. 🔹 Monitoring & Reliability: ✔️ Datadog for observability ✔️ Kubernetes HPA for auto-scaling ✔️ Health probes for application reliability 💡 Outcome: This architecture provides a scalable, secure, and fully automated DevOps ecosystem, aligned with modern cloud-native and GitOps best practices. #Azure #DevOps #Kubernetes #AKS #GitOps #Terraform #ArgoCD #CloudComputing #Microservices #CI_CD #HashiCorpVault #Datadog #Automation #TechLearning

⚙️ Jenkins – Made Simple (DevOps Learning) If you’re starting in DevOps, you’ll hear about Jenkins everywhere - here’s a simple way to understand it 👇 👉 Jenkins = Automates your build, test, and deployment process 📌 What Jenkins does: Pulls code from Git Builds the application Runs tests Deploys to server or Kubernetes 🔄 In simple terms: Instead of doing everything manually, Jenkins creates a pipeline that does it for you automatically. 📦 Basic Flow: Developer pushes code Jenkins triggers pipeline Build + Test runs Application gets deployed 💡 Why it’s important: Saves time ⏱️ Reduces human error ❌ Enables faster releases 🚀 ⚡ Example (Pipeline Idea): Stage 1: Code checkout Stage 2: Build (Maven/Gradle) Stage 3: Test Stage 4: Docker build & push Stage 5: Deploy to Kubernetes 🚀 Key Learning: Jenkins is the backbone of many CI/CD pipelines in real-world projects. #Jenkins #DevOps #CICD #Automation #LearningJourney #Cloud