Removing Large Files in Git: Impact on Repository Performance

🔧 DEVOPS UNLOCK #001 🔧 Your pod is stuck in CrashLoopBackOff at 3am. Your on-call alert just fired. Here's the exact runbook that saves you every time. Most engineers waste 20 minutes on "kubectl describe pod" when the real answer is already in the previous container logs. Here's the battle-tested triage sequence: Step 1 — Get the LAST crash logs (not just current): kubectl logs <pod> --previous -n <namespace> Step 2 — Decode exit codes: • Exit 1: App crashed — check stdout carefully • Exit 137: OOMKilled — your memory limits are too tight • Exit 143: SIGTERM unhandled — fix graceful shutdown • Exit 0: App exited cleanly — missing restart policy or loop logic Step 3 — Cross-check resource pressure: kubectl top pod <pod> -n <namespace> kubectl describe node <node> | grep -A 5 "Allocated resources" Step 4 — Catch config & scheduling issues: kubectl get events -n <namespace> --sort-by='.lastTimestamp' | tail -20 Step 5 — If still stuck, exec into a debug sidecar: kubectl debug -it <pod> --image=busybox --target=<container> ⚡ Pro Tip: Add "terminationMessagePolicy: FallbackToLogsOnError" to your pod spec. When containers crash before writing to /dev/termination-log, Kubernetes pulls the last 80 lines of stderr instead. Saved me during a silent OOM crash that left zero traces in termination logs. What's your go-to CrashLoopBackOff survival move? Drop it below 👇 #DevOps #Kubernetes #SRE #PlatformEngineering #K8s #Containers #CloudNative #DevOpsUnlock

GitOps: Why I Stopped Running kubectl Manually A while back I made a rule for myself: no more manual kubectl apply in production. Ever. It felt uncomfortable at first. Like giving up control. But the reality is — it was the opposite. Once we moved to a full GitOps workflow with ArgoCD, every change became: — Versioned in Git — Reviewed via pull request — Automatically synced to the cluster — Fully auditable Rollbacks went from a 30-minute fire drill to a simple git revert. Deployment confidence went through the roof. And the best part? Teams that previously depended on the "infra guy" could now self-serve their own deployments safely. GitOps is not just a deployment strategy. It's a cultural shift — from "who did what and when" to "the repo is the single source of truth." If you're still doing manual deployments, try this: pick one non-critical service and move it to GitOps. See how it feels. You probably won't go back. #GitOps #ArgoCD #Kubernetes #DevOps #ContinuousDelivery #SRE

🚀 Day 82 – Environment Configuration in Docker Today I explored how environment variables are managed in Docker to keep applications flexible across different environments like development, testing, and production. 🐳 Instead of hardcoding configuration values inside the application, Docker allows us to manage them externally using environment variables. 🔹 Key Things I Learned • Using environment variables to store configuration values • Managing configs with .env files • Defining variables in Dockerfile using ENV • Passing variables during container runtime 🔹 Why This Matters Good configuration management helps to: ✅ Keep sensitive data separate from code ✅ Simplify deployment across environments ✅ Improve security and maintainability ✅ Build scalable and production-ready applications Step by step, this journey is helping me understand modern backend development and DevOps practices. 🚀 #Docker #DevOps #BackendDevelopment #SoftwareEngineering #LearningJourney

There’s a common pattern I’ve seen across production environments. Your pipeline shouldn't be the source of truth. Your Git repo should. That’s GitOps. 🔄 I've worked across financial and healthcare platforms — and the pattern is always the same: Someone SSH'd into prod. Nobody knows what changed. The incident takes longer than it should. GitOps fixes this completely. GitOps isn't a tool. It's a philosophy — and teams that get it right ship faster with fewer incidents. Here’s what makes GitOps fundamentally different: 📁 Git as the single source of truth Every infra change, every config update, every deployment — lives in Git 🔄 Pull-based deployments Tools like ArgoCD or Flux pull from your repo and keep systems in sync 🔐 Security by design Everything happens via PRs — reviewed, audited, reversible ⏱️ Rollback in seconds Bad deployment? git revert → done The GitOps stack winning in 2025/2026: → ArgoCD → Flux → Crossplane → Sealed Secrets / Vault What teams are seeing: ✅ 80% fewer configuration drift issues ✅ Deployment frequency 2–3× higher ✅ Full audit trail — zero “who deployed this?” GitOps doesn't just improve deployments. It changes how teams own infrastructure. Is your team GitOps-first yet? What’s blocking the shift? 👇 #GitOps #Kubernetes #DevOps #SRE #PlatformEngineering #CloudNative #ArgoCD #Flux #CI_CD #CareerGrowth #LetsConnect #OpenToWork

I watched a $2M system go dark at 3 AM because one engineer skipped revisionHistoryLimit. He tried to roll back. Kubernetes said: error: no rollout history found There was no undo button. There was no history. There was nothing. here's the deployment checklist I never skip: 1 kubectl apply -f only. Never kubectl set image in prod. The YAML is truth. The cluster is a mirror. 2 Always set revisionHistoryLimit. That command only works if you configured history to exist. kubectl rollout undo deployment/app --to-revision=3 3 Never walk away from a rollout restart. 10% bad build caught early beats 100% crashed traffic. kubectl rollout status deployment/app Senior engineering isn't knowing every command. It's designing for the moment everything breaks. What production scar permanently changed how you deploy? Drop it below. #Kubernetes #SRE #DevOps #CloudNative #EngineeringLeadership

I built a GitHub Action that reviews pull requests before a human has to. In most CI/CD workflows, a significant amount of time is spent reviewing pull requests that contain avoidable issues - unclear descriptions, missing tests, leftover debug code, or even risky patterns. To address this, I developed truepr, a lightweight GitHub Action that automatically analyzes pull requests and provides a structured quality assessment. It evaluates four key areas: - The code diff (for security risks, bad practices, and missing tests) - The pull request description (clarity, completeness, and intent) - The linked issue (context, reproducibility, and quality) - Contributor history (to provide additional context) Based on this, it generates: - A score from 0 to 100 - A grade (A to F) - A clear recommendation (approve, review, request changes, or flag) The goal is not to replace human review, but to reduce time spent on low-quality pull requests and help teams focus on meaningful feedback. truepr runs entirely within GitHub Actions, requires no external services or API keys, and can be set up in minutes. This is particularly useful for teams and maintainers working with high pull request volumes, where early signal and consistency in review standards are critical. I would welcome feedback from developers, maintainers, and DevOps professionals working in CI/CD environments. Repository: https://lnkd.in/eWRdxEF7 I strongly believe in automation, and that even small, focused tools can significantly reduce friction and save valuable time. #github #opensource #devops #cicd #softwareengineering

You updated your code… now are you manually building, testing, and deploying every time? 😬 CI/CD automates your entire pipeline: 𝗖𝗜 (𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻) → Build + test your code automatically 𝗖𝗗 (𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁) → Deploy to Kubernetes without manual steps 👉 Tools like GitHub Actions or Jenkins handle this flow Typical flow: Code push → Build Docker image → Push to registry → Deploy to Kubernetes Result: faster releases, fewer human errors Think of it like a factory assembly line 🏭 Raw material (code) enters Machines (CI/CD) build & test Finished product is automatically shipped (deployed) Would you trust manual deployments in production… or rely on an automated pipeline every time? 🤔 #Kubernetes #Docker #DevOps #CloudComputing #Containers #Microservices #LearningInPublic #TechLearning #SoftwareEngineering #CloudNative

GitOps changed how I think about deployments forever. Two years ago, our team was manually applying Kubernetes manifests, praying nothing drifted in production. Sound familiar? Then we adopted GitOps — Git as the single source of truth for infrastructure state. The result: ✅ Deployments became auditable (every change = a PR) ✅ Rollbacks took 30 seconds, not 30 minutes ✅ Drift detection caught misconfigurations before they became incidents Here's the mental model that clicked for me: Traditional CI/CD = push-based. Your pipeline pushes changes to the cluster. GitOps = pull-based. An agent (ArgoCD, Flux) watches Git and pulls changes to match desired state. That inversion is everything. The cluster always converges toward what's in Git. No more "it works in staging but not prod" mysteries. Getting started checklist: 1. Store ALL manifests in Git (Helm charts, Kustomize overlays) 2. Set up ArgoCD or Flux in your cluster 3. Lock direct kubectl apply access 4. Add branch protection + PR reviews for infra changes The learning curve is real, but the operational calm on the other side is worth it. What's your GitOps stack? Drop it below 👇 #GitOps #ArgoCD #Flux #Kubernetes #DevOps #CI_CD

Ever had your entire project architecture almost destroyed the day before the final review? That was me today with CodeRunner, where I am building a scalable contest hosting site and remote code execution engine. I spent weeks designing it with microservices, but a teammate accidentally refactored the whole thing into a monolith and tried to push it directly to the repo. The only reason our work survived is because I had locked down the main branch. By blocking force pushes and requiring mandatory PR reviews, the system automatically rejected their changes. You should also use GitHub rulesets in your repos to avoid such situations and protect your code! It provides many options to save your branches, as you can see in the pic below where I created a ruleset for main branch protection. #BuildInPublic #SystemDesign #DevOps #Microservices #CodeRunner

Git doesn’t store “changes” the way you think. It stores snapshots of reality over time. And when nothing changes? It simply points to what already exists. That one idea is why massive histories don’t explode in size. A simple concept… with huge impact. Dive deeper 👇 https://lnkd.in/gDgzdUcf #Git #DevOps #SystemThinking #Engineering #TechInsights #SoftwareEngineering #CloudNative #VersionControl #TechCuriosity #OpenSource #TechTrends