90DaysOfDevOps with Shubham Londhe

🚀 My First Step into Kubernetes (K8s) Today I started learning Kubernetes, and I finally understood why it’s called the backbone of modern DevOps. Before this, I thought Docker was enough — but I realised Docker alone is not sufficient at scale. Here’s what I learned 👇 🔹 Docker helps in creating containers, but it works on a single host 🔹 Kubernetes solves real-world problems like: ✅ Auto-healing (restarts failed apps automatically) ✅ Auto-scaling (handles traffic spikes) ✅ Load balancing ✅ Running apps across multiple machines (cluster) 💡 The most important concept: Kubernetes doesn’t manage containers directly — it manages Pods, which are the smallest deployable units. I also explored the architecture: 🧠 Control Plane (API Server, Scheduler, etcd) 💪 Worker Nodes (Kubelet, Kube-proxy, Container Runtime) 📌 Biggest takeaway: Kubernetes ensures your application is always running in the desired state — even if things fail. This is just the beginning of my DevOps journey, and I’m excited to go deeper into: 🔹 Deployments 🔹 Services 🔹 Networking Here is my GitHub Repo Link Pasted here 👇 https://lnkd.in/eVBcQ4wJ #Kubernetes #SRE #AWS Cloud #DevOps #Docker #CloudComputing #LearningJourney #Tech #Abhishek Veeramalla

I’m excited to share the launch of my Kubernetes Zero to Hero series — a practical, step-by-step learning journey focused on building strong Kubernetes and DevOps foundations. This series is designed for: • DevOps Engineers • Cloud Professionals • Kubernetes Beginners • IT professionals preparing for real-world infrastructure roles Topics covered so far include: • Monolithic vs Microservices • Kubernetes Architecture (Control Plane & Worker Nodes) • Kubernetes Cluster Creation Methods • Quorum & RAFT Concepts • Containers, Pods & Namespaces • Minikube on AWS EC2 • K3s on AWS EC2 My focus is to simplify Kubernetes through: • Hands-on implementation • Real AWS environments • Production-oriented concepts • Practical DevOps use cases The objective is to make Kubernetes more accessible for professionals looking to strengthen their cloud and infrastructure expertise. If you're currently learning Kubernetes, DevOps, or cloud technologies, I hope this series adds value to your journey. Playlist: https://lnkd.in/eQieZjYi #Kubernetes #DevOps #AWS #CloudComputing #K8s #Infrastructure #PlatformEngineering #Containers #SRE

🚀 Hands-on Kubernetes Troubleshooting Journey Recently, I’ve been diving deep into Kubernetes troubleshooting through a structured learning approach. Covered real-world failure scenarios like: - ImagePullBackOff (container image issues) - CrashLoopBackOff (application crashes & restart loops) - Node Selector, Node Affinity, Taints & Tolerations (scheduling issues) - StatefulSet & Persistent Volume related challenges 🔍 Focus areas: - Diagnosing pod lifecycle failures - Understanding scheduling behavior and constraints - Debugging stateful applications and storage issues - Using "kubectl" effectively for cluster-level insights 💡 Key takeaway: Troubleshooting in Kubernetes is all about understanding how different components (Pods, Nodes, Scheduler, Storage) interact — most issues come down to misconfigurations or resource constraints. This hands-on practice is helping me build a stronger foundation in Kubernetes and DevOps. #Kubernetes #DevOps #Containers #Cloud #LearningByDoing

💡 Understanding DevOps Flow (Simple Breakdown) When I started learning DevOps, everything felt confusing. Now I see it like this: 👨💻 Developer writes code ⬇️ 📁 Code pushed to GitHub ⬇️ 🤖 Jenkins builds & deploys ⬇️ 📦 Docker runs the application in containers ⬇️ ☸️ Kubernetes manages containers ⬇️ ☁️ AWS provides the infrastructure 🔁 All of this is connected through a CI/CD pipeline. The biggest realization for me: DevOps is not about learning tools separately — it’s about understanding how they work together. Still learning, but things are starting to make sense 🔥 #DevOps #CI_CD #Docker #Kubernetes #AWS #LearningInPublic

🚨 Most DevOps Beginners Focus on Tools — I Did Too When I started learning DevOps, I focused on: Docker Kubernetes Terraform CI/CD But after building and debugging real deployments, I realized something important. Most failures were NOT because of tools. They were because of: • Wrong configurations • Missing readiness checks • Poor understanding of system behavior • Not checking logs properly For example: A pod can be Running but not Ready A deployment can look successful but still fail traffic A pipeline can pass but deployment can still break That changed how I approach DevOps. Now I focus more on: Understanding failures Reading logs Observing system behavior Debugging step by step Tools are important. But understanding systems is what makes you reliable. Still learning by breaking and fixing real scenarios. #DevOps #Kubernetes #Learning #Cloud #Engineering

While learning DevOps, one tool that keeps coming up again and again is Docker — and now I understand why it’s so important. Docker helps you package an application with everything it needs (code, dependencies, environment) so it runs the same everywhere — no more “it works on my machine” problem. Why Docker Matters: Consistent environments across development, testing, and production Lightweight and fast compared to virtual machines Easy to deploy and scale applications Works perfectly with CI/CD pipelines Makes collaboration between teams much smoother Key Topics to Learn in Docker: Docker basics (images, containers) Writing Dockerfile Docker Compose (multi-container apps) Image optimization & best practices Volumes & networking Docker Hub / container registries Basic troubleshooting & debugging My Thought: Docker feels like a foundation skill for DevOps. Without it, managing environments and deployments becomes messy and time-consuming. Still learning, but understanding Docker is already making things much clearer #Docker #DevOps #Cloud #Containerization #LearningJourney

Kubernetes feels hard… until someone explains it the right way. Most people struggle with Kubernetes not because it’s complex — but because it’s usually taught in a confusing way. I faced the same problem. So I built a Kubernetes guide from scratch based on: • Real production experience • Actual failures (OOMKilled, CrashLoopBackOff, scaling issues) • How systems behave under load — not just theory Instead of memorizing concepts, this document focuses on: ✔ How Kubernetes actually works internally (Control Plane, Worker Nodes) ✔ Why things break in production and how to fix them ✔ Clear mapping: Pod → Deployment → Service → Ingress ✔ Real use cases like scaling, auto-healing, rollout strategies For example: Most tutorials say “Pods restart automatically” But in reality → ReplicaSet ensures desired state and recreates pods instantly That’s the difference between learning Kubernetes and understanding it. If you're: 🔹 Starting Kubernetes 🔹 Working in DevOps / SRE 🔹 Preparing for real production environments This will simplify things a lot. Kubernetes is not hard. It’s just badly explained in most places. 📄 Sharing my complete guide — built to make Kubernetes finally “click” #Kubernetes #DevOps #SRE #Cloud #AWS #Containers #Docker #PlatformEngineering #Microservices #InfraAsCode #Tech #Learning #CareerGrowth #Engineering

🚀 DevOps Cheat Sheet – From Code to Production After diving deeper into my DevOps journey, I created this cheat sheet to simplify the full flow from development to deployment — with a strong focus on automation, scalability, and security. 💡 What’s inside: • End-to-end DevOps workflow (Code → Terraform → Ansible → Docker → Kubernetes → CI/CD → Monitoring → Security) • Essential commands for daily use • Troubleshooting quick fixes 🔧 • Security best practices at every stage 🔐 DevOps is not just about tools — it’s about building a reliable, automated, and secure pipeline that connects everything together. This cheat sheet is designed for: ✔️ Beginners who want to understand the big picture ✔️ Engineers transitioning into DevOps/Cloud ✔️ Anyone looking for a quick reference in daily work 📌 I’d love your feedback — what would you add or improve? #DevOps #Cloud #AWS #Docker #Kubernetes #Terraform #Ansible #CICD #DevSecOps #Learning #Te

Most developers are using Kubernetes WRONG… 🙊🙉 I was wasting hours using Minikube and cloud clusters just to test small changes 😓 Then I found Kind (Kubernetes in Docker) And everything changed 👇🥹 ⚡ Starts in seconds 💻 Runs locally (no cloud needed) 💸 Zero cost 🧪 Perfect for testing before production Now I can: → Spin up clusters anytime → Test deployments instantly → Use it inside CI/CD pipelines But here’s the truth 💔👇 Kind is NOT for production ❌ It’s for: ✔ Learning ✔ Local development ✔ CI/CD testing If you’re learning Kubernetes or doing DevOps… You NEED to know this. 📌 Swipe through the slides to understand it simply Follow me for more real DevOps content 🚀😌 #kubernetes #devops #docker #backend #softwareengineering #cloud #learning #programming

🚀 I recently built an end-to-end DevOps pipeline, and here are 5 lessons that changed how I think: 1️⃣ Automating everything is tempting—but observability matters more than automation. If you can't see it, you can't fix it. 2️⃣ CI/CD is not just tools like Jenkins or GitHub Actions—it's a culture of fast feedback. 3️⃣ Docker made things consistent, but Kubernetes made me understand distributed systems deeply. 4️⃣ Failures in production are inevitable—designing rollback strategies is more important than avoiding failure. 5️⃣ Monitoring is not an afterthought—tools like Prometheus & Grafana are as critical as deployment tools. 💡 DevOps is not about tools. It’s about reducing friction between development and operations. #DevOps #Cloud #CI_CD #Docker #Kubernetes #LearningJourney