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Managing multiple Kubernetes clusters shouldn’t feel like this. Switching contexts. Checking logs. Running commands. Debugging issues. It adds up fast. So I built AutoKube. Now you can: - switch clusters instantly - see pods in real-time - check logs immediately - run commands in one place - analyze issues with AI No more kubectl chaos. 👉 GitHub in comments Curious what you think 👇 If this saves you time, a ⭐ would mean a lot 🙏 #kubernetes #devops #cloudnative #platformengineering #opensource #docker #k8s

I spent more time than I want to admit staring at Kubernetes YAML wondering how a config file gets inside a running container. ConfigMap. Volume. VolumeMount. Three things. No one explains how they actually connect. Here is what clicked for me. The ConfigMap is the letter. Your config data lives here. The Volume is the envelope. It wraps the ConfigMap and gives it a name Kubernetes can carry. The VolumeMount is the delivery address. It tells Kubernetes exactly where inside the container to place that file. By the time your container starts, the file is already sitting there waiting. The container has no idea any of this happened. It just sees a file at a path and reads it. The three things that need to match exactly: 1) The ConfigMap name must match what the Volume points to. 2) The Volume connector name must match what the VolumeMount references. 3) The file path in the VolumeMount must match what your app expects to find. Get those three right and it just works every time. What Kubernetes concept took you the longest to understand? 👇 Follow me, I am documenting everything I build and learn in my home lab. #Kubernetes #DevOps #CloudNative #Homelab #DevOpsLearning

𝙃𝙚𝙧𝙚 𝙞𝙨 𝙩𝙝𝙚 𝘿𝙤𝙘𝙠𝙚𝙧𝙛𝙞𝙡𝙚 𝙩𝙝𝙖𝙩 𝙛𝙞𝙭𝙚𝙙 𝙨𝙡𝙤𝙬 𝙗𝙪𝙞𝙡𝙙𝙨. Image bloat was killing my 𝘾𝙄/𝘾𝘿 𝙥𝙞𝙥𝙚𝙡𝙞𝙣𝙚 𝙨𝙥𝙚𝙚𝙙. Here is how I optimized the Flask containerization: • Used 𝙢𝙪𝙡𝙩𝙞-𝙨𝙩𝙖𝙜𝙚 𝙗𝙪𝙞𝙡𝙙𝙨 to drop dev dependencies • Cached Docker layers to reduce rebuild times • Stripped the final image to a 𝙡𝙞𝙜𝙝𝙩𝙬𝙚𝙞𝙜𝙝𝙩 𝙧𝙪𝙣𝙩𝙞𝙢𝙚 Optimizing the Dockerfile saves hours of deployment time over a month. 𝙒𝙝𝙖𝙩’𝙨 𝙮𝙤𝙪𝙧 𝙨𝙩𝙧𝙖𝙩𝙚𝙜𝙮 𝙛𝙤𝙧 𝙠𝙚𝙚𝙥𝙞𝙣𝙜 𝙞𝙢𝙖𝙜𝙚𝙨 𝙨𝙢𝙖𝙡𝙡? #DevOps #Docker #CICD #Kubernetes #ShreyasTech

🐳 Learning Docker… I’ve been using Docker for a while, but recently started understanding the basics more clearly. Things like: 1. Images vs Containers 2. Layers and how they affect build time 3. What a registry does 4. Why tags matter Still learning, but it’s starting to make more sense now. I wrote a short blog to capture my understanding: 🔗 https://lnkd.in/gxSG4v_p Would love to hear — what helped you understand Docker better? #Docker #LearningInPublic #DevOps

We just published a new blog post on our GitOps journey - and how it led us to building our own operator: Espejote. From Ansible playbooks to a jungle of operators, bash reconcilers and plenty of lessons learned along the way - this is the story of how we ended up building something that finally fits our needs. Espejote combines GitOps principles with in-cluster state, powered by Jsonnet and native server-side apply. Built for flexibility, reliability and real-world operations at scale. If you're working with Kubernetes, GitOps or platform engineering, this might resonate 🙂 👉 Read the full story: https://lnkd.in/d29EEvtT #Kubernetes #GitOps #PlatformEngineering #DevOps #CloudNative #OpenSource

We just published a new blog post on our GitOps journey - and how it led us to building our own operator: Espejote. From Ansible playbooks to a jungle of operators, bash reconcilers and plenty of lessons learned along the way - this is the story of how we ended up building something that finally fits our needs. Espejote combines GitOps principles with in-cluster state, powered by Jsonnet and native server-side apply. Built for flexibility, reliability and real-world operations at scale. If you're working with Kubernetes, GitOps or platform engineering, this might resonate 🙂 👉 Read the full story: https://lnkd.in/d29EEvtT #Kubernetes #GitOps #PlatformEngineering #DevOps #CloudNative #OpenSource

I spent 3 years confused about Kubernetes. Here's everything you need in my next 7 posts. Most tutorials jump straight into YAML. That’s where confusion starts. 🔵 What is Kubernetes? Kubernetes is a container orchestration platform. You tell it what you want — like “run 3 replicas” — and it handles everything. If a server crashes → it restarts pods If traffic increases → it scales automatically You define the goal → Kubernetes manages the system 🐳 Why not just Docker? Docker runs containers on one machine Kubernetes runs them across multiple machines with: Auto scaling Self healing Load balancing Zero downtime deployments 📦 4 concepts you must know: Pod → Smallest unit (container wrapper) Node → Machine running pods Cluster → Group of nodes Namespace → Logical separation (dev, test, prod) ⚡ Most used commands: kubectl get pods kubectl describe pod my-app kubectl logs my-app kubectl exec -it my-app -- bash kubectl apply -f pod.yaml kubectl delete pod my-app kubectl get all kubectl get events The K8s learning curve is steep but the payoff is huge. Which concept confused you most when starting with Kubernetes? Drop it below 👇 #Kubernetes #DevOps #CloudNative #Docker #SRE #PlatformEngineering #LearningInPublic

Most people rebuild containers. I tried fixing one. Another step in building in public. This week I ran into a Docker issue where a container was in an exited state. Instead of deleting and recreating, I stopped and checked what was actually wrong. Looked into volume mapping and port configs using docker inspect, then simply restarted it with docker start. The service came back and was accessible on port 8085. Biggest lesson: troubleshooting matters more than just knowing how to build. Follow along — more coming next week #backend #docker #devops #buildinpublic

K8s + the ecosystem = Unstoppable. Here’s a quick cheat sheet on how external tools plug in to give Kubernetes new superpowers. What's your go-to K8s combo? 👇 #Kubernetes #CloudNative #DevOps

🚀 Day 15/30 – Docker + CI/CD Integration Today, I successfully integrated Docker with CI/CD using GitHub Actions 🐳⚙️ 🔹 Created a Dockerfile to containerize my application 🔹 Integrated Docker build into CI pipeline 🔹 Triggered automated Docker image build on code push 🔹 Explored how CI/CD works with containerization in real-time 💻 Initially, I faced errors like a missing Dockerfile, but I was able to debug and resolve them successfully. This helped me understand the importance of correct configuration and file structure in DevOps workflows. 💡 Key Takeaway: Combining Docker with CI/CD enables automated, consistent, and reliable application builds and deployments 🚀 📸 Attached: Successful Docker build via GitHub Actions 👉 Learning and improving step by step! #DevOps #Docker #CICD #GitHubActions #AWS #Automation #LearningInPublic #Day15