Automated CI/CD Pipeline with GitHub Actions and Docker

Most developers know how to write a Dockerfile. Fewer know how to wire it into a pipeline that actually ships software. In my latest blog post, I document the exact GitLab CI/CD setup I used to automate the full deployment of a Vite React app on Docker — from running tests in an isolated Node.js container, to building and pushing a Docker image, to deploying to a live Ubuntu server via SSH. A few things worth highlighting: → Docker-in-Docker (DinD) isn't magic — it's just the Docker daemon running as a service container inside your job → Never put credentials in your YAML. GitLab's CI/CD variable system exists for a reason. → Stage ordering is architecture. Test → Build → Deploy isn't arbitrary — it's a failure-isolation strategy. If your team is still deploying manually, this post is a starting point worth bookmarking. 🔗 https://lnkd.in/exJVzMN2 #DevOps #GitLab #Docker #CI_CD #EnterpriseArchitecture #SoftwareEngineering

I am excited to share my latest project: a fully automated, zero-downtime Kubernetes provisioning and upgrade solution built entirely with Ansible. As Kubernetes environments grow in complexity, ensuring consistent infrastructure setups and executing safe upgrades without impacting running applications becomes a critical challenge. I built this project to streamline that process, removing manual work and minimizing human error. The tool is designed to be straightforward and plug-and-play. Whether you need to bootstrap a brand new cluster from scratch or perform a delicate minor-version upgrade on a live environment, the playbook handles the heavy lifting. Simply define your target IP addresses in the inventory file, specify your desired Kubernetes version, and let Ansible do the rest. Key features of the project include: - Full Lifecycle Automation: Seamlessly handles OS preparation, Containerd configuration, Control Plane initialization, and Worker Node joining. - Zero-Downtime Upgrades: Implements a safe Cordon, Drain, Upgrade, and Uncordon sequence across all nodes to guarantee application availability during the process. - Cross-Platform Compatibility: Natively supports and adapts to both Debian/Ubuntu and RedHat/CentOS operating system families. - Idempotent Logic: Built-in validation checks query the API server and local Kubelet configurations to ensure tasks only execute when absolutely necessary, preventing accidental state changes. You can explore the full source code, architecture diagrams, and documentation in the repository here: https://lnkd.in/deWbZrbi #Kubernetes #Ansible #DevOps #Automation #PlatformEngineering #CloudNative #InfrastructureAsCode #K8s

Most CI/CD pipelines don’t fail because of tools — they fail because no one adapts them to real conditions. I took a GitLab CI pipeline from a demo project. It didn’t work as expected. The root cause wasn’t the tool itself — it was a mismatch between the pipeline logic and the actual build environment. Instead of just fixing errors, I focused on adapting the pipeline to reach a stable build process. Anyone can write a pipeline. But making it reliable — that’s a different level. 👉 Source code and full pipeline implementation: https://lnkd.in/dB3Mwgvq

Recently I worked on CI/CD pipeline project to understand how automated deployments actually work in practice. This was my first time practically implementing a CI/CD workflow, and it helped me understand how different tools integrate together. Instead of only learning the tools individually, I tried connecting them together in a small working setup. 🔹 Server Side Configuration • Used Ansible to configure the target Linux server • Installed Docker and Docker Compose using automation • Prepared the server environment for running containers • Ensured the server was ready for automated deployments 🔹 CI/CD Pipeline • Code pushed to GitHub • GitHub webhook triggers Jenkins pipeline • Jenkins pulls the latest code from the repository • Pipeline deploys the application using Docker Compose • Application runs inside an Nginx container 🔹 What I Learned • How a CI/CD pipeline works end-to-end • How GitHub webhooks trigger Jenkins pipelines • Using Ansible for server configuration and automation • Deploying containers using Docker Compose • Connecting multiple DevOps tools in a simple workflow Tech Stack: GitHub | Jenkins | Ansible | Docker | Docker Compose | Nginx | Linux This was a small but useful learning project that helped me understand how these tools work together in a real workflow. #DevOps #CICD #Jenkins #Docker #Nginx #LearningJourney #Infrastructure #SRE #Platform

Still deciding between GitHub Actions, GitLab CI, and Jenkins? We compared setup speed, pipeline syntax, self-hosted options, ecosystem, pricing, and security. Short version: GitHub Actions if you're already on GitHub. GitLab CI if you want everything in one place. Jenkins only if you have very specific build needs and the team to maintain it. Full breakdown on our blog: https://lnkd.in/eVYdWvUs

Just shared a new post on my blog. A practical look at how I design CI/CD pipelines with GitHub Actions — prioritizing clarity, fast feedback cycles, and maintainability over unnecessary complexity. These are patterns that have worked well for me in real projects, especially when scaling workflows and keeping deployments predictable. If you're refining your pipeline strategy, this might be worth a read :) https://lnkd.in/dKbd6zEa #DevOps #CICD #GitHubActions #SoftwareEngineering

🔧 Real DevOps problems I solved this week — and what I learned. Setting up a full CI/CD pipeline from scratch sounds simple until you hit the real-world issues nobody talks about in tutorials. Here's what broke and how I fixed it 👇 ❌ Issue 1 — Jenkins wouldn't start Root cause: My Docker container (Tomcat) was already occupying port 8080. Jenkins also defaults to 8080. Simple conflict, but it took reading journalctl logs to find it. ❌ Issue 2 — App deployed but returned 404 Root cause: Tomcat maps WAR filenames directly to URL paths. maven-web-app.war serves at /maven-web-app — not /. Spent 20 minutes on this one. ❌ Issue 3 — Jenkins couldn't run Docker commands Root cause: Jenkins user wasn't in the docker group. One command fixed it: sudo usermod -aG docker jenkins ✅ End result: A working Jenkins pipeline that — → Clones code from GitHub → Builds WAR with Maven → Builds Docker image → Pushes to DockerHub The biggest lesson? Read the logs first. Always. #DevOps #Jenkins #Docker #AWS #CI_CD #CloudEngineering #Linux

Sometimes the most frustrating CI/CD pipeline failures come down to the simplest directory contexts. I was recently migrating a massive batch of microservices from Jenkins to GitHub Actions. Everything looked perfect in the YAML, but the deployment step kept failing or timing out. The issue? The Docker container was building successfully, but it was missing critical environment variables. In our legacy Jenkins setup, the bash script explicitly navigated into the service directory (cd my-service) before copying the .env.prod file and running the Docker build. When translating that to GitHub Actions, that subtle path logic got lost. The runner was executing commands in the root directory, silently failing to copy the .env file into the build context. The fix was incredibly simple but easy to miss: explicitly setting the 𝘄𝗼𝗿𝗸𝗶𝗻𝗴-𝗱𝗶𝗿𝗲𝗰𝘁𝗼𝗿𝘆 𝗸𝗲𝘆 𝗮𝘁 𝘁𝗵𝗲 𝘀𝘁𝗲𝗽 𝗹𝗲𝘃𝗲𝗹 𝘁𝗼 𝗲𝗻𝘀𝘂𝗿𝗲 𝘁𝗵𝗲 𝗰𝗽 𝗰𝗼𝗺𝗺𝗮𝗻𝗱 and the docker build command ran in the exact same context as the Dockerfile. What I learned is that When migrating legacy pipelines to a modern CI tool, don't just copy-paste the shell commands - verify the execution context of every single step. What is the weirdest bug you have run into while migrating CI/CD platforms? #CICD #DevOpsEngineering #GitHubActions #Jenkins #PlatformEngineering #TechCareers

🚀 Stop wasting time on Docker CLI chaos — meet LazyDocker If you work with Docker daily, you already know the pain: Long container IDs Endless docker ps, logs, exec commands Constant tab switching just to debug something simple I recently started using LazyDocker, and it completely changed how I interact with containers. 🔥 What is LazyDocker? It’s a terminal UI for Docker and Docker Compose that gives you a clean, interactive view of: Containers Images Volumes Logs Stats (CPU / RAM usage) All in one place. ⚡ Why it matters (real productivity boost): No need to memorize long Docker commands Instant log viewing (no more copy-paste container IDs) One-click start/stop/restart containers Easy debugging inside a visual TUI Perfect for DevOps engineers and backend developers 🧠 Install in seconds: brew install lazydocker Then just run: lazydocker 💡 Final thought: Sometimes productivity isn’t about learning more tools — it’s about using smarter interfaces for the tools you already use. LazyDocker is one of those “why didn’t I use this earlier?” tools. #DevOps #Docker #LazyDocker #Containers #Linux #CloudComputing #DevOpsTools #BackendDevelopment #Terminal #Automation #ProductivityHacks #SoftwareEngineering

Ever wondered why your CI/CD pipeline feels fast at first… but starts struggling as projects grow? Let me tell you a simple story When I first started working with Jenkins, everything was running on a single server. Small builds, fewer users — life was easy. But as the team grew, builds increased, pipelines got heavier… and suddenly everything slowed down. Delays, queue issues, frustration That’s when I understood the real power of Jenkins Master-Agent Architecture Think of it like this: Master Node = Brain Handles UI, job scheduling, configurations, and controls everything. Agents = Muscles They do the actual heavy lifting — running builds, tests, deployments. API Layer = Communication Bridge Connects Jenkins with tools like Git, SonarQube, Slack, etc. Instead of one server doing all the work, Jenkins distributes tasks across multiple agents. Now imagine running builds on Linux, Windows, Docker… all at the same time That’s not just automation — that’s scalability. Lesson I learned If you want to grow in DevOps, don’t just learn tools… Understand how they scale. That’s where real engineering begins. #DevOps #Jenkins #CI_CD #Automation #Scalability #SystemDesign #CloudComputing