How to Automate Deployments with GitHub Actions and Vercel

Day 18: Automating Releases- Connecting My CI/CD Pipeline with GitHub🚀 After building my CI/CD pipeline (shared on Day 17), I added a Release workflow to make deployments even smarter. Now, every successful deployment automatically creates a GitHub Release with all the details. Why Need Releases? 🤔 1. Track Versions - Know which version is running (v1.0.0, v1.1.0, etc.) 2. Easy Rollback - Go back to old version if new one breaks 3. Team Updates - Everyone knows when new version is released 4. Docker Tags - Know exactly which Docker image to use 5. Professional Look - Makes your project look production-ready How It Works? ⚙️ Simple Flow: Day 17 → Build & Deploy → Save version info ↓ Day 18 → Read version info → Create Release The Process (5 Simple Steps): ✅ Step 1: Wait for Deploy - Waits for Day 17 workflow to finish - Only runs if deploy was successful ✅ Step 2: Download Data - Gets the artifact (version info) saved by Day 17 - Downloads it as a zip file ✅ Step 3: Read Version Info - Opens the zip file - Reads version number, Docker image name, and tags ✅ Step 4: Prepare Data - Saves all info as variables to use later ✅ Step 5: Create Release - Makes a new GitHub release - Adds version number, Docker tags, and description - Links back to the build workflow What's in the Release? 📦 - Version Tag: v1.0.0 - Docker Images: All tags (latest, v1.0.0) - Description: What was deployed - Build Link: Link to see build details - Change Notes: What changed since last release Why This is Great? ✨ 1. Automatic - No manual work needed 2. Safe - Only releases after successful deploy 3. Connected - Deploy and release always match 4. History - See all past versions easily 5. No Mistakes - Computer does it, so no human errors 🔗 Project Link: https://lnkd.in/gp4WETj2 Every successful deploy now gets a proper release automatically! 🎯 #DevOps #CICD #GitHubActions #Docker #Automation #SoftwareEngineering  #BackendDevelopment #NodeJS #CloudDeployment #DockerHub  #ProductionReady #VPS #BuildAndDeploy #TechJourney #LearningInPublic #Day18 #Automation #ReleaseManagement

Looks like my GitHub Action agilecustoms/release just got its first adopters! Yey 🎉 https://lnkd.in/e-bRTPWz A quick recap — this GitHub Action is for releasing software. Not building. Not deploying. And that’s exactly its strength. Build steps vary wildly, deployment processes differ everywhere… but every piece of software needs a version and a place to store its binaries Here’s what a typical CI pipeline looks like: - install dependencies - lint - test - package - generate a version and persist it durably in an artifact store ⟵ that’s where I come in! In the microservices world, a single system can produce multiple artifacts: binaries, Docker images, DB migration scripts, OpenAPI schemas, IaC templates — all often tied to a Git tag In every company I’ve worked for, enterprises keep reinventing this wheel — with random .sh or .py scripts to generate versions, authenticate with repos, and upload binaries Common pitfalls I’ve seen: - Versions always look like 1.234.0 — only the minor version ever changes - Long-lived, insecure credentials are the norm - Because release pipelines are so complex, teams often force everything into Docker images — even when a simple ZIP Lambda would be much easier I believe versioning, authentication, binary upload, and Git tagging are largely the same across projects (just with a few parameters) So if you adopt agilecustoms/release, you can reduce release management headaches, improve your security posture, and unlock more freedom for your teams! #GitHubActions #CICD #DevOps #ReleaseAutomation #SoftwareEngineering #DeveloperTools

𝗧𝗶𝗻𝘆 𝗖𝗵𝗮𝗻𝗴𝗲, 𝗕𝗶𝗴 𝗜𝗺𝗽𝗮𝗰𝘁 𝗶𝗻 𝗖𝗜/𝗖𝗗 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 🚀 Today, I made a small but critical improvement to my GitHub Actions workflow a great reminder that even one line of YAML can make your automation easy and smooth... 🔧 𝗪𝗵𝗮𝘁 𝘄𝗮𝘀 𝘁𝗵𝗲 𝗖𝗵𝗮𝗻𝗴𝗲? I tightened the workflow triggers to run only when relevant files change, cutting down unnecessary pipeline runs. And I added this small but impactful line: 𝘧𝘦𝘵𝘤𝘩-𝘥𝘦𝘱𝘵𝘩: 0 to my actions/checkout step, ensuring the full Git commit history is fetched during each run. 💡 𝗪𝗵𝘆 𝗧𝗵𝗶𝘀 𝗠𝗮𝘁𝘁𝗲𝗿𝘀 By default, GitHub Actions performs a shallow clone fetching only the latest commit. That means there’s no HEAD^ (previous commit) available, which breaks commands like: 𝘨𝘪𝘵 𝘥𝘪𝘧𝘧 𝘏𝘌𝘈𝘋^ 𝘏𝘌𝘈𝘋 or any workflow logic that compares the current commit with its parent. With fetch-depth: 0, we now get the complete Git history, enabling accurate diffs, changelogs, and versioning logic across our pipeline 🧠 𝗞𝗲𝘆 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆 Improving a CI/CD pipeline isn’t always about big refactors or something crazy, sometimes it is about understanding how your tools behave under the hood. One line, one insight, and you’ve just made your automation faster, leaner, and smarter! #DevOps #GitHubActions #CI/CD #Automation #SoftwareEngineering #GitTips #ContinuousIntegration #ContinuousDeployment #YAML #CloudNative #PlatformEngineering #DeveloperExperience #InfraAsCode #PipelineOptimization #BuildAutomation #EngineeringExcellence #TechLeadership #UAE #FeynmanLearns #LearningByDoing

Day 20/30 of 30days30projects GitHub webhooks From manual deployments to AUTOMATED everything! Today I built a complete CI/CD pipeline that builds, tests, and deploys containers automatically on every git push! What I Built: A production-ready CI/CD pipeline using Jenkins with GitHub webhooks that automatically: - Detects code changes - Builds Docker images - Pushes to Docker Hub - Triggers deployments All happening in seconds after a simple `git push` Architecture Overview: GitHub → Webhook → Jenkins → Docker Build → Docker Hub → Deploy Every code commit triggers the entire pipeline automatically. No manual intervention needed! Key Components: GitHub Webhook Integration Real-time push notifications Automatic pipeline triggers Payload validation Secure webhook secrets # Jenkins Pipeline Declarative pipeline as code Multi-stage build process Automated testing Docker image building Registry authentication # Docker Hub Integration Automated image versioning Tag management (latest + version) Private repository support Image scanning ready # The Magic of Webhooks: Before: - Manual git pull - Manual docker build - Manual docker push - Manual deployment - Time: ~15 minutes After: - `git push` - Everything's deployed! - Time: ~2 minutes (automated) # Technical Stack: • Jenkins - CI/CD automation server • GitHub Webhooks - Event-driven triggers • Docker- Containerization • Docker Hub - Container registry • Groovy - Pipeline scripting • Git - Version control • Shell Scripts - Automation glue #30Days30Projects #Jenkins #CICD #Docker #DockerHub #DevOps #Automation #GitHubWebhooks #ContinuousIntegration #ContinuousDeployment #CloudComputing #Containerization #Microservices #AgileDevelopment #TechTwitter #BuildInPublic

How Jenkins Made Me Rethink Automation 🚀 Automation isn’t just about speed — it’s about reliability. When I first started setting up CI/CD pipelines, Jenkins felt intimidating. So many plugins, configurations, and that classic UI that looked straight out of 2008. But once I truly understood it, I realized it’s one of the most powerful tools for orchestrating build, test, and deployment workflows. Here’s what clicked for me 👇 1️⃣ Pipelines as code — Jenkinsfiles changed everything. Version-controlled pipelines mean that CI/CD processes evolve with your repo. No more mystery jobs buried in the UI. 2️⃣ Agent flexibility — Whether you’re deploying to Docker, Kubernetes, or a local test environment, Jenkins agents make scaling and parallel execution effortless. 3️⃣ Integration power — With over a thousand plugins, Jenkins connects to almost any DevOps tool — from GitHub Actions to Slack alerts to AWS deployments. 💭 But the biggest lesson? Jenkins isn’t “old.” It’s battle-tested. If you treat it like an evolving platform instead of a legacy one, it can still rival any modern CI/CD solution out there. ⚙️ My current workflow: Trigger build on every pull request Automated test suite runs in parallel containers Artifacts deployed via Jenkins to staging Notifications go out to Slack and email It’s not flashy, but it works — and that’s the essence of good automation. 👋 Curious to hear from others: Are you still using Jenkins in your pipeline, or have you moved to newer CI/CD tools like GitHub Actions, CircleCI, or GitLab CI? What’s keeping you on (or away from) Jenkins? #DevOps #Jenkins #CICD #Automation #SoftwareEngineering #DevOpsTools

Did You Know #61 What Is Git and Why Developers Use It to Manage Code Like Pros Git is a version control system that helps developers track changes in their code, collaborate smoothly, and roll back mistakes when things go wrong — kind of like an “undo” button for entire projects. Here’s the simple idea: Every time a developer makes changes, Git records them as a snapshot called a commit. These commits build up a full history of the project, showing who changed what and when. If something breaks, you can easily go back to a previous version. Think of Git like a time machine for code. It lets multiple developers work on the same project without stepping on each other’s toes — then combines their work cleanly when ready. Git is the foundation of modern DevOps workflows, powering platforms like GitHub, GitLab, and Bitbucket. 💡It’s the reason developers can collaborate from anywhere in the world and still keep their code perfectly in sync. --- 👉 We post quick 1-minute reads like this on Facebook, Instagram, and LinkedIn — so no matter where you scroll, we’ve got your brain covered. Follow us on your favorite platform and get smarter with every scroll — 60 seconds at a time! 🔹 Facebook: https://lnkd.in/gnkvTpqA 🔹 Instagram: https://lnkd.in/gVE9DgDu 🔹 LinkedIn: https://lnkd.in/g2epRrRn #TechBasics #1minuteread #Syversoft

Day 17: I Designed My Own CI/CD Pipeline Using GitHub Actions Today, I successfully designed and implemented a complete Build → Test → Versioning → Docker → VPS Deployment pipeline for my LMS Backend project using GitHub Actions + Docker + SSH. This workflow helps me ship faster, reduce downtime, and eliminate manual deployment effort. Here’s how each stage works — step by step: ✅ Stage 0 — Build & Test - Checkout source code - Install Node.js dependencies using `npm ci` - Run ESLint to ensure code quality - Execute test suite (skips gracefully if no tests yet) - Compile TypeScript for production-ready output 📌 Goal: Ensure code is clean, stable & build-ready before going further. 🔢 Stage 1 — Auto Versioning If triggered manually → Takes version input Else → Automatically generates a new version (patch bump) Then updates `package.json` and pushes version commit to GitHub ✅ 📌 Every successful release gets a traceable version tag! 🐳 Stage 2 — Docker Build & Push ✅Configure Docker Buildx for multi-platform builds ✅ Login to Docker Hub using GitHub Secrets ✅Build and push Docker image with two tags: ✅ Selected version (example: `v1.2.3`) ✅`latest` tag for production auto updates ✅ Store metadata as artifact for release step 📌 Fast builds thanks to registry-based caching! 🚀 Stage 3 — Auto Deployment to VPS ✅ SSH into server securely using secrets ✅ Create `.env` if missing ✅ Pull new Docker image ✅ Stop & remove older container ✅ Run new container with: - Health checks enabled - Auto restart policy - Mounted logs & uploads  ✅ Prune unused old images 📌 Zero downtime & health-driven deployment success check ✅ 🏁 Stage 4 — Create Git Tag 📍 If deployment is successful ➡️ Create release tag ➡️ Push to GitHub 📌 Deployment must succeed before tagging — safe release guarantee! 🔥 What I Learned ✔️ Advanced GitHub Actions workflow design ✔️ Secure DevOps with secrets & SSH automation ✔️ Dockerized production environment management ✔️ CI/CD as a discipline for real-world reliability ✅ Project Link 🔗 GitHub Repository: 👉 https://lnkd.in/gxpiTNBR #DevOps #CICD #GitHubActions #Docker #Automation #SoftwareEngineering  #BackendDevelopment #NodeJS #CloudDeployment #DockerHub  #ProductionReady #VPS #BuildAndDeploy #TechJourney #LearningInPublic

𝗦𝘂𝗽𝗲𝗿𝗰𝗵𝗮𝗿𝗴𝗲 𝗬𝗼𝘂𝗿 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝘄𝗶𝘁𝗵 𝗚𝗶𝘁𝗛𝘂𝗯 𝗔𝗰𝘁𝗶𝗼𝗻𝘀 𝗔𝘂𝘁𝗼-𝗙𝗶𝘅𝗲𝗿! 🚀🔧✨ Agents that read failing GitHub workflows and propose fixes aim to streamline the process of identifying and resolving issues within GitHub workflows. This tool enhances efficiency and accuracy by automatically suggesting fixes for common problems, ultimately saving time and effort for developers. 𝗪𝗵𝘆 𝗗𝗼𝗲𝘀 𝗜𝘁 𝗠𝗮𝘁𝘁𝗲𝗿 ?🤔 - The search results showcase real-world examples of how GitHub Actions Auto-Fixer tools can address specific issues within workflows, aligning perfectly with the post's Topic, Description, and Category. - They illustrate the practical benefits of using automation to streamline development processes, highlighting the value of automated solutions in enhancing productivity and code quality. - By demonstrating the capabilities of auto-fixing tools in various scenarios, these results emphasize the importance of incorporating automation in workflow management for smoother and more efficient development cycles. 𝗜𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗟𝗶𝗻𝗸𝘀 🔗: Option to auto-fix rules? · Issue #80 · DavidAnson/markdownlint | https://lnkd.in/dYafm5JJ Finding and Auto-fixing Lint Errors with GitHub Actions | https://lnkd.in/dd-cAwp5 Warning or auto repair for flat bottom when simplifying model · Issue | https://lnkd.in/dXxQN8ee My Reusable GitHub Actions Workflows | https://lnkd.in/dAxp5MYY wearerequired/lint-action | https://lnkd.in/dWf6-EA2 #GitHubActions #Automation #DevOps #Productivity #CodingTools

Automating My Frontend App Deployment Using Jenkins, Docker & GitHub Webhooks Over the past few days, I’ve been deep-diving into CI/CD pipelines—and today, I finally achieved a fully automated Docker image build and deployment using Jenkins integrated with GitHub Webhooks! Here’s what I accomplished. 🔹 Configured Jenkins Pipeline (Declarative) to build, tag, push, and deploy Docker images automatically. 🔹 Integrated Docker Hub using secure Jenkins credentials for seamless image uploads. 🔹 Implemented GitHub Webhooks so every new code push triggers an automatic build & container deployment. 🔹 Deployed the containerized app on my custom port using Docker—with clean stages like Build, Push, Stop Old Container, Run New Container, and Verify Deployment. 🔹 Debugged several syntax and credential issues—learned the importance of correct withCredentials usage and environment variable handling in Groovy. 💡 Key Takeaway: Understanding the automation flow between GitHub → Jenkins → Docker Hub → Server gives a real sense of DevOps power. Seeing your container spin up instantly after a commit is pure satisfaction! #Jenkins #DevOps #Docker #CICD #GitHub #Automation #LearningJourney #AniketGaud #SoftwareEngineering #TechJourney

🔄 GitOps changed how I think about deployments. Here's a simple truth I wish I knew earlier: Your Git repository should be the single source of truth for EVERYTHING. Not your production server. Not your local machine. Not some random config file someone edited last year. Git. That's it. GitOps in 3 principles: 1️⃣ Declarative Describe your desired infrastructure state in code. No more "it works on my machine." 2️⃣ Versioned & Immutable Every change is tracked. Rollback is just a git revert. Your infrastructure has a complete audit trail. 3️⃣ Pulled Automatically Operators like ArgoCD and Flux watch your Git repo and automatically sync changes to production. The game-changer? → Push to Git → Automatic deployment → Merge conflict? Infrastructure conflict prevented → Want to rollback? Git history = deployment history → Need approval? Pull requests become deployment gates No more: ❌ SSH into servers ❌ Manual kubectl apply ❌ "Who deployed this?" mysteries ❌ Configuration drift Traditional CI/CD: Push-based (CI pushes to production) GitOps: Pull-based (Production pulls from Git) This shift matters more than you think. With GitOps: - Your infrastructure becomes self-documenting - Disaster recovery = clone repo + sync - New team members onboard faster (everything's in Git) Tools I'm using: → ArgoCD for Kubernetes deployments → Terraform for infrastructure provisioning → GitHub Actions for CI pipeline GitOps isn't just a tool—it's a mindset shift. Treat infrastructure like you treat code. Version it. Review it. Test it. Are you practicing GitOps yet? #GitOps #DevOps #InfrastructureAsCode #Kubernetes #ArgoCD #ContinuousDeployment #CloudNative #Automation