{"slug": "from-a-simple-web-app-to-a-production-style-platform-my-devops-learning-journey", "title": "From a Simple Web App to a Production-Style Platform: My DevOps Learning Journey", "summary": "A developer transformed a simple web app called SystemCraft into a production-style platform by adopting Docker, Kubernetes, Helm, ArgoCD, Prometheus, and security scanning with Trivy. The project evolved from a system design interview tool into a full DevOps learning journey, emphasizing automation, GitOps, and monitoring.", "body_md": "**When I started building SystemCraft, my goal wasn't to learn Kubernetes, GitOps, monitoring, or cloud-native architecture.**\n\nI just wanted to build a system design interview platform.\n\nFast forward a few months, and that simple web application evolved into something much bigger:\n\nCI/CD Pipelines\n\nDockerized Deployments\n\nKubernetes\n\nHelm Charts\n\nArgoCD GitOps\n\nPrometheus Monitoring\n\nGrafana Dashboards\n\nAlertManager\n\nAuto Scaling\n\nSecurity Scanning\n\nThis article is the story of how that happened and what I learned along the way.\n\n**The Original Idea**\n\nSystemCraft was designed to solve a problem I noticed while preparing for system design interviews.\n\n**Most preparation resources are passive:**\n\nReading blogs\n\nWatching videos\n\nLooking at architecture diagrams\n\nBut real system design interviews are interactive.\n\nYou need to make decisions, justify trade-offs, adapt to changing requirements, and explain your reasoning.\n\nI wanted to create a platform where engineers could:\n\nDesign architectures visually\n\nReceive AI-powered feedback\n\nSimulate real interview scenarios\n\nLearn through iteration\n\n**The first version was straightforward:**\n\n*Next.js\n↓\nMongoDB\n↓\nGemini API*\n\n**The Docker Phase**\n\nMy first step was containerization.\n\nI created a Dockerfile and containerized the entire application.\n\nAt first, I thought Docker was the hard part.\n\nI quickly learned it wasn't.\n\nBuilding containers is easy.\n\nOperating containers reliably is the real challenge.\n\n**\n\nQuestions started appearing:\n\n**How do I deploy updates?\n\nHow do I manage multiple replicas?\n\nHow do I scale?\n\nHow do I monitor failures?\n\nDocker solved packaging.\n\nIt didn't solve operations.\n\n**Building a Real CI Pipeline**\n\nThe next step was automation.\n\nI didn't want deployments to depend on manual commands.\n\nI created a GitHub Actions pipeline that would automatically:\n\n*Lint & Typecheck\n↓\nPlaywright E2E Tests\n↓\nDocker Build\n↓\nTrivy Security Scan\n↓\nKubernetes Validation\n↓\nDeployment*\n\n**One lesson became obvious:**\n\nAutomation isn't about speed.\n\nIt's about consistency.\n\nThe pipeline catches mistakes long before they reach production.\n\n**Security Wasn't Optional**\n\nOne of the most valuable additions was Trivy.\n\nInitially I wasn't thinking much about container security.\n\nThen I started scanning images and realized how many vulnerabilities can exist inside dependencies you didn't even know you had.\n\n**Every build now goes through:**\n\n*Docker Build\n↓\nTrivy Scan\n↓\nDeployment*\n\nThis simple addition completely changed how I think about shipping software.\n\n**Enter Kubernetes**\n\nEventually a single container stopped being enough.\n\nI wanted:\n\nMultiple replicas\n\nSelf-healing workloads\n\nRolling updates\n\nHorizontal scaling\n\nKubernetes provided all of that.\n\n**But Kubernetes introduced new challenges:**\n\nYAML management\n\nService discovery\n\nResource limits\n\nHealth checks\n\nConfiguration management\n\nThe complexity increased significantly.\n\nAt the same time, I started understanding why Kubernetes became the industry standard.\n\n**Helm Changed Everything**\n\nManaging raw Kubernetes manifests quickly became painful.\n\nI introduced Helm charts to template deployments and environments.\n\nInstead of maintaining multiple copies of manifests, I could parameterize everything:\n\nImage versions\n\nReplica counts\n\nResource limits\n\nEnvironment variables\n\nDeployment became much more manageable.\n\n**Discovering GitOps with ArgoCD**\n\nThis was probably the biggest mindset shift.\n\nOriginally deployment looked like:\n\n_GitHub Actions\n\n↓\n\nkubectl apply\n\n**After learning GitOps:**\n\nGit Commit\n\n↓\n\nGit Repository\n\n↓\n\nArgoCD\n\n↓\n\nKubernetes Cluster_\n\nThe cluster state became fully declarative.\n\nGit became the source of truth.\n\nRollback became dramatically easier.\n\nAuditing changes became trivial.\n\nI finally understood why so many engineering teams are adopting GitOps workflows.\n\n**Monitoring: The Missing Piece**\n\nFor a long time I only cared whether the application worked.\n\n**Then I realized:**\n\nIf something breaks in production, how would I know?\n\nThat question led me to Prometheus and Grafana.\n\nI instrumented the application and started tracking:\n\nAPI latency\n\nRequest volume\n\nError rates\n\nResource utilization\n\nApplication health\n\nSuddenly I could see what the system was actually doing.\n\nMonitoring transformed troubleshooting from guessing into observing.\n\nAdding Alerting\n\nMonitoring is useful.\n\nAlerting is essential.\n\n**I integrated AlertManager so that operational issues could be detected automatically.**\n\nThis forced me to think about:\n\nError thresholds\n\nSLOs\n\nAvailability targets\n\nIncident response\n\nTopics I previously associated only with large companies.\n\nTesting Scalability\n\nEventually I wanted to understand how the platform behaved under load.\n\nI simulated 500 concurrent users.\n\n**The results were revealing.\n\nSingle Container\n\nMetric Value\n\nRequests 23,381\n\nThroughput ~155 req/s\n\nP95 Latency 3.33s\n\nThe Node.js process became saturated.\n\nPerformance degraded rapidly.\n\nKubernetes with HPA\n\nMetric Value\n\nRequests 61,026\n\nThroughput ~351 req/s\n\nP95 Latency 861ms**\n\nBy distributing traffic across multiple pods, latency dropped dramatically while throughput more than doubled.\n\nThis was the first time I could actually see the benefits of horizontal scaling in practice.\n\n**Current Architecture**\n\nToday the deployment flow looks like this:\n\n*Developer\n↓\nGitHub\n↓\nGitHub Actions\n↓\nDocker Build\n↓\nTrivy Scan\n↓\nGHCR\n↓\nArgoCD\n↓\nKubernetes\n↓\nPrometheus\n↓\nGrafana\n↓\nAlertManager*\n\nWhat started as a simple web application became a complete cloud-native platform.\n\n**What I Learned\nA few lessons stood out throughout this journey.**\n\n**What's Next**\n\nThe next phase of my learning journey involves:\n\n**AWS\nTerraform\nInfrastructure as Code\nDistributed Load Testing\nPlatform Engineering**\n\n**I'm currently building an open-source load testing tool called Loadster, inspired by the challenges I encountered while testing SystemCraft.\n**\n***\n\n**Check out the site Live:** [https://system-craft-kohl.vercel.app/](https://system-craft-kohl.vercel.app/)\n\nIf you like the article make sure to drop a like and maybe even checkout the github repo and help me contribute and make it even better", "url": "https://wpnews.pro/news/from-a-simple-web-app-to-a-production-style-platform-my-devops-learning-journey", "canonical_source": "https://dev.to/shashank0701byte/from-a-simple-web-app-to-a-production-style-platform-my-devops-learning-journey-29km", "published_at": "2026-06-13 22:40:57+00:00", "updated_at": "2026-06-13 22:50:31.007160+00:00", "lang": "en", "topics": ["developer-tools", "mlops"], "entities": ["SystemCraft", "Docker", "Kubernetes", "Helm", "ArgoCD", "Prometheus", "Trivy", "GitHub Actions"], "alternates": {"html": "https://wpnews.pro/news/from-a-simple-web-app-to-a-production-style-platform-my-devops-learning-journey", "markdown": "https://wpnews.pro/news/from-a-simple-web-app-to-a-production-style-platform-my-devops-learning-journey.md", "text": "https://wpnews.pro/news/from-a-simple-web-app-to-a-production-style-platform-my-devops-learning-journey.txt", "jsonld": "https://wpnews.pro/news/from-a-simple-web-app-to-a-production-style-platform-my-devops-learning-journey.jsonld"}}