Debugging Kubernetes Deployment Issues with ImagePullBackOff and Port Fix

I broke my laptop's Python environment 3 times in one month. Different projects needed different versions. One pip install would quietly destroy another project. Then I learned Docker — and everything changed. Here's what Docker actually does (no jargon): → It wraps your app + its dependencies into a box called a container → That box runs the same on your laptop, your teammate's Mac, and a Linux server → You stop saying "it works on my machine" — because it works everywhere My first Dockerfile was 5 lines: ``` FROM python:3.11 WORKDIR /app COPY . . RUN pip install -r requirements.txt CMD ["python", "app.py"] ``` That's it. No more environment disasters. I'm a CS student learning DevOps in public — this was my week 1 win. Have you had your environment broken by dependency conflicts? How did you fix it? #Docker #DevOps #LearnInPublic #CS #BackendDev

🚀 Day 18 – Shell Scripting Level Up! Today I focused on writing cleaner, safer, and reusable shell scripts — a big step from basic scripting to real-world usage 💻 What I learned: ✔️ Writing and calling functions for reusable code ✔️ Using set -euo pipefail for safer scripts ✔️ Handling return values & local variables ✔️ Building a complete system info script One important takeaway: Using set -euo pipefail makes your scripts more reliable and production-ready by preventing silent failures. Key Learnings: Functions = Cleaner & reusable code Strict mode = Safer & error-free scripts Check out my work:https://lnkd.in/g4TvriXU #90DaysOfDevOps #DevOpsKaJosh #TrainWithShubham #DevOps #ShellScripting #Linux #Automation #Scripting #LearningInPublic #TechJourney #Cloud #Programming #CareerGrowth #ITJobs #Developers #CodeNewbie

🐳 Getting Hands-On with Docker! Over the past few days, I've been diving deep into Docker — and honestly, it's been a game-changer in how I think about building and deploying applications. From pulling images to running containers, managing volumes to pushing to Docker Hub — every command I learned made me realize how powerful containerization really is. 💡 So I put together this Docker Cheat Sheet covering all the essential commands — images, containers, networks, volumes, Dockerfile, and more — in one place! Whether you're just starting out or need a quick reference, I hope this helps your DevOps journey too. 🚀 📌 Save this post so you never forget these commands! 💬 Drop a comment if you found this helpful or if I missed any command! 🔁 Repost to help others in the community! #Docker #DevOps #Linux #Containers #CloudNative #Programming #LearningInPublic #TechCommunity #OpenSource

📜Learning bash scripting taught me something I didn't expect: The gap between understanding something and using something is massive. You can read about variables and functions all day. But the real progress happens when you: → Apply the theory in isolation (write the function, test it, break it) → Connect the concepts (pass parameters, capture input, handle logic) → Build something end-to-end (a real script that solves a real problem) 👇Below is a script I put together that sorts all .txt files in a directory by size, smallest to largest, with input validation built in. Is it the most efficient script? Probably not. But that's the point, efficiency comes with practice, and you can't refine what you haven't built yet! Most people stop at step one and wonder why it's not sticking. Build something, even something small. That's where it lands. What's a skill you learned by just building with it? 💻 #Bash #Scripting #Linux #Tech #DevOps

Before containers, we had a machine. Three services. Three different Python versions. Three different opinions about what should be in /tmp. The solutions were bad. Separate VMs were expensive and slow to spin up. Config management was fragile, Chef and Puppet could get you to "probably right" but not "reliably reproducible." Manual isolation wasn't isolation at all. Docker in 2013 didn't invent anything. cgroups were in the kernel in 2006. Namespaces existed before that. What Docker built was a well-designed interface on top of things Linux already knew how to do, and packaged it in a way developers could actually use. Understanding that history matters for one reason: if you know why containers were invented, you know what they're actually solving, and what they're not. They're excellent at process isolation and dependency management. They're not a security boundary by themselves. The tool is the solution to a specific problem. Know the problem. Tell me, What’s a time when understanding namespaces or cgroups would’ve saved you hours? #Docker #Linux #DevOps #Containers #Infrastructure #CloudNative #SoftwareEngineering #History #opensource

Bash scripting is humbling. I’ve spent the last week feeling like I’m trying to learn a foreign language from a textbook written in 1978. One missed space or a slightly wrong bracket and the whole thing dies with a cryptic error message. It’s a grind. But then I pivoted into Docker this week, and I could actually breathe again. The difference? Context. I’ve been messing with containers in my home lab for a couple of years now—running services like Nextcloud and Valheim. Because I had that "hands-on" history, the theory finally had a place to land. Bash feels like abstract math; Docker feels like building with Legos I already own. The Golden Rule of the Lab: If you’re doing this at home, keep your "Experimental" and "Production" environments strictly separate. There is no faster way to have a household mutiny on your hands than nuking the DNS or the Wi-Fi while you're testing a new script. My "Production" stack (Pi-hole, pfSense, etc.) stays stable so the house stays happy, while the "Experimental" nodes are where I’m allowed to break things. The takeaway: Theoretical study is necessary, but the home lab is where the actual "clicking" happens. If you’re pivoting careers like I am, don't just read the documentation—break something in your own rack. It’s the only way the "foreign language" starts making sense. #DevOps #HomeLab #Linux #Docker #CareerPivot #kubecraft #k8s #kubernetes

💡 Most people learn DevOps… I decided to build one from scratch. So I created my own self-hosted homelab infrastructure 🏠⚙️ --- 🚀 What’s inside? - 🐧 Ubuntu Server - ⚙️ Kubernetes (k3s) for orchestration - 🌐 Nginx as reverse proxy - 📺 Jellyfin (media server) - ☁️ Nextcloud (self-hosted storage) - 🤖 CI/CD using webhooks + bash scripts - 🧠 Custom Python tool to automate media ingestion --- 📊 The architecture (attached below) shows how everything connects — from networking → compute → storage → automation. --- 🔥 What I learned: - Real DevOps is not just tools — it’s how systems interact - Debugging > Tutorials (mount failures, permissions, streaming issues 😅) - Automation makes everything 10x smoother --- 🔗 Project Repo: https://lnkd.in/gZ9G9peh --- Would love to hear your thoughts or suggestions to improve this setup 👇 #DevOps #Kubernetes #Homelab #Linux #Automation #SelfHosted #SRE #Backend

Unpopular opinion (learned this the hard way): You don’t really understand Kubernetes or Docker… if you don’t understand Linux. I used to focus on tools first: Kubernetes. Docker. Terraform. I could deploy things. Scale things. Monitor things. But when something broke? I was stuck. Because here’s the truth most people skip: 👉 Docker is just Linux containers (namespaces, cgroups) 👉 Kubernetes is just an orchestrator sitting on top of Linux systems 👉 And most automation around it? Powered by Python That realization changed everything for me. So I went back to basics: 🖥️ Linux — processes, memory, networking, permissions 🐍 Python — scripting, automation, control No dashboards. No abstractions. Just fundamentals. And suddenly: ⚡ Debugging Kubernetes issues made sense ⚡ Docker errors weren’t “random” anymore ⚡ I could automate instead of copy-pasting commands Now I don’t just “use” tools — I understand what they’re doing under the hood. That’s the real leverage. 👉 Tools make you productive 👉 Fundamentals make you dependable If you’re serious about SRE / DevOps: Don’t just learn Kubernetes. Learn what Kubernetes is built on. #Linux #Python #Kubernetes #Docker #SRE #DevOps #TechCareers

🚀 Most Used Linux Commands Every Developer Should Know If you’re working in backend, DevOps, or AI… Linux isn’t optional. It’s your daily toolkit. Here’s a quick breakdown of the commands that actually matter 👇 📂 File Handling Navigate and manage files like a pro → ls, cd, pwd, mkdir, rm 📖 File Viewing Read logs and files efficiently → cat, less, head, tail 🔍 Text Processing (Game Changer) Find and manipulate data fast → grep, awk, sort, find ⚙️ Process Management Control running applications → ps, top, kill, pkill 🌐 Networking Debug APIs & connect to servers → curl, ping, ssh, scp 💾 System Monitoring Know what’s happening inside your machine → df, du, free, uname 📦 Package Management Install tools in seconds → apt, dnf, yum 🔐 Permissions Control access and security → chmod, chown 🧰 Pro Tip: Don’t try to memorize everything. Think in actions: ◾ Search → grep ◾ Navigate → cd ◾ Debug → top Master these, and you can handle 90% of real-world tasks in Linux. 🔥 Reality check: 90% of dev work = just ~10 commands used daily. 💬 Which Linux command do you use the most? 🎯 Follow Virat Radadiya 🟢 for more..... #Linux #DevOps #BackendDevelopment #SoftwareEngineering #Programming #Developers #Coding #CloudComputing #TechSkills #LearnToCode

Backend looks invisible to users. But when it fails, everyone feels it ⚙️ That’s why strong backend skills are not just about writing code. They’re about building systems that can: ✅ handle real data ✅ survive errors ✅ respond fast ✅ stay secure ✅ grow without breaking Good backend is quiet. Reliable. Predictable. And absolutely essential. 🚀 #progerito #ittraining #backend #springboot #linux #devops #softwareengineering #programming #learncoding #systemdesign #developerlife #careergrowth