GitHub Enterprise Migration: 3000+ Repositories Automated

🎯 Day 58 – Canary Deployment Strategy and Progressive Delivery (Part 2) While Blue-Green provides instant switch,it does not test gradually. Production systems use Canary deployment to release changes to a small subset of users before full rollout. Today’s focus: implementing Canary deployment in Kubernetes. Implementation Overview: •Deployed stable and canary versions simultaneously •Routed small percentage of traffic to canary Pods •Monitored performance and error rates •Gradually increased traffic to new version •Rolled back automatically on failure detection Operational Workflow: User Traffic→Split Routing→Stable Pods + Canary Pods→Monitoring→Decision→Full Rollout/Rollback Commands Executed: kubectl apply -f stable-deployment.yaml kubectl apply -f canary-deployment.yaml kubectl get pods kubectl describe deployment kubectl logs <pod> Validation: •Verified partial traffic routed to canary •Monitored logs and metrics •Gradually increased traffic percentage •Tested rollback on simulated failure Engineering Impact: Reduced deployment risk,real-time validation,better user experience,controlled rollout Practice Tasks: 1.Deploy canary version with limited replicas 2.Route partial traffic to canary 3.Monitor application metrics 4.Increase traffic gradually and validate Expected Result: Only a small percentage should hit canary initially System should remain stable during rollout Rollback should be possible without impact Canary deployment enables safe and intelligent release strategies in modern production systems. #AWS #Azure #GCP #DevOps #Docker #Kubernetes #Terraform #Ansible #Jenkins #GitHubActions #GitLabCI #Prometheus #Grafana #ELK #Linux #CICD #InfrastructureAsCode #SRE #PlatformEngineering #DevOpsShack #ShubhamLondhe #GeeksforGeeks #TrainWithShubham #AbhishekVeeramalla #90DaysOfDevOps #Leadership #Management #Entrepreneurship #BusinessStrategy #FutureOfWork #AI #Technology #RemoteWork #JobSearch #Marketing #CareerGrowth #Innovation #PersonalBranding #ContentStrategy #Productivity #GrowthMindset #ProfessionalDevelopment #CloudComputing #GitHub #DevSecOps #CI_CD #Automation #Microservices #DevOpsEngineer #DevOpsCommunity #SysAdmin #CloudEngineer #TechJobs

Stop Managing Servers, Start Automating Workflows 🚀 Are you still manually deploying code or running tests on your local machine? It’s time to let GitHub Actions do the heavy lifting. GitHub Actions has evolved from a simple CI tool into a full-scale automation engine. Whether you are a DevOps Engineer or a Full-Stack Developer, it allows you to orchestrate your entire software development lifecycle directly from your repository. Why it’s a game-changer: ✅ Native Integration: No need for external CI/CD servers. ✅ Matrix Builds: Test across multiple OSs and versions simultaneously. ✅ Marketplace: Thousands of pre-built actions to plug and play. Some Use Cases of Github Actions: Automated CI/CD: Deploying to AWS/Azure/GCP the moment a PR is merged. Issue Management: Automatically labeling or closing stale issues. - Security Scanning: Running Snyk or Trivy scans on every push. - Scheduled Tasks: Backing up databases or generating weekly reports. Are you using GitHub Actions for anything unique? Let’s swap workflow ideas in the comments! 👇 #GitHubActions #DevOps #CICD #Automation #SoftwareEngineering #CloudComputing

From a local `localhost:8080` to a fully automated, scalable production system — that's the DevOps journey 🤔 . Imagine you build an app. It works on your laptop. Now what? Here's how the modern DevOps toolchain takes it all the way to production: 🔧 Git & GitHub — Version control so teams can collaborate without stepping on each other's toes. ⚙️ Jenkins / GitHub Actions — CI/CD pipelines that automatically build, test, and deploy every time code is pushed. 🐳 Docker — Package your app and all its dependencies into a container that runs the same everywhere. ☸️ Kubernetes — Orchestrate those containers at scale. Auto-scale up, auto-heal failures. 🌍 Terraform — Define your entire infrastructure as code. Provision 3 identical servers with a single `terraform apply`. 🔩 Ansible — Configure those servers post-provisioning. Install software, set up services — all automated via playbooks. 📊 Prometheus + Grafana — Monitor everything. CPU, memory, processes — visualized in real-time dashboards. The beauty of DevOps isn't any single tool. It's how they all fit together into one seamless pipeline — from idea to production. What tool in this stack took you the longest to click with? For me it was Kubernetes. Drop it below 👇 #DevOps #Docker #Kubernetes #Terraform #Ansible #CI_CD #SoftwareEngineering #CloudComputing DevOps Insiders

🚀 End-to-End CI/CD Pipeline using Jenkins, Docker, and DockerHub Excited to share my hands-on project where I built a complete CI/CD pipeline to automate the build, test, and deployment process of a containerized application. 🔹 What I Did Designed and implemented an end-to-end CI/CD pipeline using Jenkins to automate code integration, Docker for containerization, and DockerHub for image storage and distribution. 🔹 Tools & Technologies Used Jenkins (Automation Server) Docker (Containerization) DockerHub (Image Repository) GitHub (Source Code Management) Linux / EC2 (Execution Environment) 🔹 Key Highlights ✔️ Automated build and deployment process using Jenkins pipelines ✔️ Integrated GitHub with Jenkins for continuous integration ✔️ Built and pushed Docker images to DockerHub ✔️ Reduced manual deployment effort and improved efficiency ✔️ Implemented continuous delivery workflow 🔹 Workflow Code Push → Jenkins Build → Docker Image Creation → Push to DockerHub → Deployment 🚀 This project enhanced my practical knowledge of DevOps practices, automation, and container-based deployment pipelines. #DevOps #CICD #Jenkins #Docker #DockerHub #Automation #CloudComputing #GitHub #Learning #SoftwareEngineering

How to set up CI/CD for a .NET API using GitHub Actions Still deploying manually or relying on scripts? That approach breaks as your system grows. GitHub Actions gives you a simple, powerful way to automate build and deployment directly from your repo. Here’s a practical flow: 1. Push your code to GitHub Keep your main branch stable and production-ready. 2. Create a workflow file Create .github/workflows/dotnet.yml This defines your entire CI/CD pipeline. 3. Trigger on every push on: push: branches: [ "main" ] 4. Set up the runner Use a managed VM from GitHub: jobs: build: runs-on: ubuntu-latest 5. Install .NET - name: Setup .NET uses: actions/setup-dotnet@v4 with: dotnet-version: 8.0.x 6. Build and test - run: dotnet restore - run: dotnet build --configuration Release - run: dotnet test --no-build 7. Publish your app - run: dotnet publish -c Release -o ./publish 8. Deploy to Azure Use official actions like: azure/webapps-deploy azure/container-apps-deploy Authenticate using GitHub Secrets. 9. Manage secrets securely Store credentials in GitHub Secrets. Never commit them to code. Key Insight GitHub Actions turns your repository into your deployment engine. Every commit becomes: Code → Build → Test → Deploy No external tools required. If you're building .NET apps, this is one of the fastest ways to set up CI/CD with minimal friction. Are you using Azure DevOps pipelines or GitHub Actions for your workflows? #githubactions #cicd #dotnet #devops #azure #cloudcomputing #softwareengineering #automation #microservices #backenddevelopment

We talk a lot about GitOps but usually skip over what actually changes day-to-day when you run a hybrid setup with Azure DevOps handling infra and GitHub Actions driving app deployments. Here's what I keep coming back to: the biggest shift isn't the tooling. It's who initiates the change. In a traditional push-based pipeline, ADO reaches into your cluster and makes things happen. You need firewall rules, service principals with broad access, and hope that nothing drifts between runs. With a pull-based GitOps setup, a controller inside the cluster watches the repo and reconciles continuously. No inbound access needed. If someone manually deletes a pod or tweaks a setting in the portal, the system fixes itself within minutes. The other thing that changes is your relationship with "state." In a push model, the truth lives in pipeline variables, scripts, and whatever manual changes got made at 2am. In a GitOps model, if it isn't committed to Git, it doesn't exist. That sounds like a constraint. In practice it makes incident recovery much faster. ADO for infra (VPCs, AKS clusters, databases) still makes sense because those resources change slowly and need heavier orchestration. GitHub Actions for app deploys works well because those changes are frequent and should be fast and safe. Build this out as a working reference if you want to see how the pieces fit together: 👉 https://lnkd.in/gAN6wRfN What controller are you running on the pull side? ArgoCD, Flux, or something else ? #pushbasedpipeline #pullpipeline #deployments #ADO #GHActions #AgroCD #Gitops #Copilot #Vibecoding #Claudeopus4.7 #MCP

🚀 Scaling on GitHub: From Script to Enterprise Moving from a solo project to a large-scale enterprise environment isn’t just about more code—it’s about managing complexity. When hundreds of developers contribute, "git push" isn't enough. You need system-level governance. Here are the 10 pillars of GitHub at scale: Structure: Choose between a Monorepo (unified flow) or Polyrepos (team independence). Storage: Use Git LFS to keep your repository slim by offloading large binary files. Gates: Implement Branch Protection—no code hits production without passing CI/CD. Ownership: Define a CODEOWNERS file to automate review assignments to the right experts. Governance: Use Rulesets to apply security guardrails across every repo in your organization. CI/CD: Scale your automation with Matrix Builds to test multiple OS versions simultaneously. Performance: Deploy Self-hosted Runners for faster, more secure automation pipelines. Security: Leverage Dependabot and Secret Scanning to catch vulnerabilities before they’re exploited. Analysis: Use CodeQL to treat your code as data and find deep-seated logic flaws. Roadmaps: Align your team with GitHub Projects (v2) for high-level visibility beyond just code. The goal? Shift from "writing code" to "building systems." 🛠️ #DevOps #DevSecOps #GitHub #SoftwareEngineering #CloudNative #SystemDesign #OpenSource

Schedule GitHub Actions like a pro — with cron expressions. ⏰ GitHub Actions supports scheduled triggers via the on: schedule: node in your workflow YAML. Cron expressions (quoted in YAML) define when the workflow runs, and schedules are evaluated in UTC. You can add multiple cron entries and the minimum interval is every 5 minutes. Key takeaways: - Add a schedule: - cron: '15 5,17 * * *' to run at 05:15 and 17:15 UTC. 🕔 - Quote expressions in YAML (asterisk is special). " * " ➜ "'*'". - Schedules run on the latest commit of the default branch. 🔁 - Use */15 * * * * for every 15 minutes; shortest allowed is 5 minutes. Why read: if you automate builds, deployments, or maintenance tasks, this is the simplest way to run them on a cadence. Read the full guide → https://lnkd.in/erM7dqhh #GitHubActions #Cron #CI/CD #DevOps #YAML

🚨 Most teams think they are doing CI/CD. But they are still doing manual deployments just faster. Think of GitHub Actions like a diligent assistant 🧑✈️ who watches your mailbox 📬 (GitHub repository) 🏠 Your house (EC2 Instance) sits inside a gated community (VPC) 🛣️ The house is on a street (Public Subnet) 🚪 The main gate (Internet Gateway) connects you to the outside world 👮 A security guard at the gate (Route Table) directs visitors to the correct house 🔐 The front door lock (Security Group ports 22 and 80) controls who can enter ✅ Everything is structured, secure, and controlled 📬 Every time a new letter arrives in your mailbox (code merged to main): 🧑✈️📋 The assistant (GitHub Actions runner) reads instructions (deploy.yml) 🚗 Drives to your house (connects to EC2 via SSH) 🪑 Picks up the old furniture (stops and removes old container) 📦 Brings in the new furniture (pulls and runs new Docker image on port 80) 📱 Texts you when done (workflow success / green checkmark) ❌ You never have to: 👀 Watch the mailbox yourself 📬 Sort the mail yourself 🚚 Make the delivery yourself 🧑✈️ The assistant handles everything every single time 🔑 It uses a spare key (SSH key pair) stored safely in a secure lockbox (GitHub Secrets) so it can always access your house (EC2 Instance) securely 👉 This is what modern deployments should feel like. Not manual effort. Not repeated commands. A system that runs itself. 🏗️This is part of a DevOps lab I am building to explore real-world platform engineering patterns. 👉 📖🎥 Full breakdown in the article and video, links in the first comment 👇 💬 Question: Does your deployment feel like this or are you still driving to the house manually? #DevOps #GitHubActions #AWS #Terraform #InfrastructureAsCode #PlatformEngineering #CICD

🚨 Most teams think they are doing CI/CD. But they are still doing manual deployments just faster. Think of GitHub Actions like a diligent assistant 🧑✈️ who watches your mailbox 📬 (GitHub repository) 🏠 Your house (EC2 Instance) sits inside a gated community (VPC) 🛣️ The house is on a street (Public Subnet) 🚪 The main gate (Internet Gateway) connects you to the outside world 👮 A security guard at the gate (Route Table) directs visitors to the correct house 🔐 The front door lock (Security Group ports 22 and 80) controls who can enter ✅ Everything is structured, secure, and controlled 📬 Every time a new letter arrives in your mailbox (code merged to main): 🧑✈️📋 The assistant (GitHub Actions runner) reads instructions (deploy.yml) 🚗 Drives to your house (connects to EC2 via SSH) 🪑 Picks up the old furniture (stops and removes old container) 📦 Brings in the new furniture (pulls and runs new Docker image on port 80) 📱 Texts you when done (workflow success / green checkmark) ❌ You never have to: 👀 Watch the mailbox yourself 📬 Sort the mail yourself 🚚 Make the delivery yourself 🧑✈️ The assistant handles everything every single time 🔑 It uses a spare key (SSH key pair) stored safely in a secure lockbox (GitHub Secrets) so it can always access your house (EC2 Instance) securely 👉 This is what modern deployments should feel like. Not manual effort. Not repeated commands. A system that runs itself. 🏗️This is part of a DevOps lab I am building to explore real-world platform engineering patterns. 👉 📖🎥 Full breakdown in the article and video, links in the first comment 👇 💬 Question: Does your deployment feel like this or are you still driving to the house manually? #DevOps #GitHubActions #AWS #Terraform #InfrastructureAsCode #PlatformEngineering #CICD