Jenil Gohel’s Post

🚀 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗹𝗼𝗼𝗸𝘀 𝗰𝗼𝗺𝗽𝗹𝗲𝘅... 𝘂𝗻𝘁𝗶𝗹 𝘆𝗼𝘂 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝘁𝗵𝗲 𝗰𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀. Most beginners try to learn Kubernetes by memorizing commands. Smart engineers learn the 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗳𝗶𝗿𝘀𝘁. That’s where real confidence starts. 💡 Here’s a clean breakdown of 𝟯𝟬 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗰𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀 every DevOps Engineer should know. 🔹 𝗣𝗼𝗱 – Smallest deployable unit 🔹 𝗡𝗼𝗱𝗲 – Machine where Pods run 🔹 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 – Manages updates & replicas 🔹 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 – Stable networking for Pods 🔹 𝗜𝗻𝗴𝗿𝗲𝘀𝘀 – HTTP/HTTPS routing 🔹 𝗖𝗼𝗻𝗳𝗶𝗴𝗠𝗮𝗽 – Non-sensitive configs 🔹 𝗦𝗲𝗰𝗿𝗲𝘁 – Passwords / keys 🔹 𝗣𝗩 / 𝗣𝗩𝗖 – Persistent storage 🔹 𝗦𝗰𝗵𝗲𝗱𝘂𝗹𝗲𝗿 – Assigns Pods to Nodes 🔹 𝗘𝘁𝗰𝗱 – Stores cluster state 🔹 𝗛𝗲𝗹𝗺 – Kubernetes package manager …and many more inside this cheat sheet 👇 📌 If you understand these 30 components, you’ll already be ahead of many Kubernetes learners. 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀:  • ✅ Better troubleshooting  • ✅ Strong interview answers  • ✅ Real production understanding  • ✅ Faster learning path  • ✅ Confidence in DevOps roles 𝗔𝗱𝘃𝗶𝗰𝗲:  • Don’t just learn 𝗸𝘂𝗯𝗲𝗰𝘁𝗹 𝗰𝗼𝗺𝗺𝗮𝗻𝗱𝘀.  • Learn 𝗵𝗼𝘄 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝘁𝗵𝗶𝗻𝗸𝘀. 𝗧𝗵𝗮𝘁’𝘀 𝗵𝗼𝘄 𝗲𝘅𝗽𝗲𝗿𝘁𝘀 𝗴𝗿𝗼𝘄. 🚀 💬 Which Kubernetes component confused you the most when starting? #Kubernetes #DevOps #CloudComputing #Docker #AWS #Azure #GoogleCloud #PlatformEngineering #SRE #Containers #Helm #K8s #DevOpsEngineer #TechLearning #VyomanantAcademy #Vyomanant

🚨 "It works on my machine." Probably the most dangerous sentence in software development. Not for me yet — I’m still in my learning phase, so please consider me… just kidding 😁 But jokes aside, when software works locally and fails in production, teams lose time, money, and trust. Debugging environment issues can slow down releases and frustrate developers. That’s exactly why Docker, Inc exists. 🐳 Docker changed how we build, ship, and run applications by introducing containers — lightweight, portable environments that ensure software runs the same way everywhere. From a developer’s laptop to staging servers to cloud production systems — Docker makes applications scalable, consistent, fast, and portable. As part of my DevOps learning journey, I’m currently working on a hands-on project using Docker to better understand containerization, deployment workflows, and real-world development practices. Sharing what I learn along the way. More to come. 🚀 Follow for more content on: Docker • DevOps • Kubernetes • Cloud Computing #Docker #DevOps #LearningInPublic #CloudComputing #SoftwareDevelopment #TechJourney

🚀 – DevOps Learning Journey Today I explored important Kubernetes concepts that help manage and scale applications 🔥 📌 Topics Covered: 🔹 Deployment Used to manage and deploy applications declaratively. Supports scaling, updates, and rollbacks. 🔹 ReplicaSet Ensures a specified number of Pod replicas are always running. 🔹 StatefulSet Used for stateful applications (like databases) with stable identity and storage. 🔹 Labels & Selectors Labels are key-value pairs used to organize resources. Selectors help Kubernetes identify and manage specific Pods. 🔹 Rolling Updates Update applications gradually without downtime 🚀 🔹 DaemonSet Ensures one Pod runs on every node (useful for monitoring, logging agents). 📌 Key Learning: Kubernetes is powerful because it provides self-healing, scaling, and automated deployment features. Excited to continue learning more advanced concepts 💯 #DevOps #Kubernetes #Deployment #CloudComputing #LearningJourney #Containers

Something I’ve realised over time: When I first started learning DevOps, my approach was simple. Pick a tool. Follow a tutorial. Move to the next one. Kubernetes. Terraform. GitHub Actions. At one point, I even started picking tools straight from interview JDs. If a role mentioned something, I’d go learn it. For a while, it felt good. It felt relevant. It gave me confidence. Until the interviews happened 😅 I could talk about the tool… but struggled with the basics behind it. And this didn’t happen just once. That’s when it hit me a bit hard. It wasn’t about effort. It was about direction. I took a step back and started looking at the bigger picture. Instead of focusing on tools, I started focusing on learning the fundamentals of the domains behind them. 👉 networking 👉 security 👉 cost 👉 system design 👉 reliability 👉 observability 👉 IaC 👉 CI/CD And that’s when things started to change. Once CI/CD concepts made sense, switching between Jenkins, Azure DevOps, or GitLab felt more like translation than learning. Same with infrastructure. Understanding the fundamentals made it easier to work across Terraform, Bicep, or CloudFormation… The syntax changes. The thinking doesn’t. That’s when this clicked for me: DevOps doesn’t really grow vertically. ➡️ It grows horizontally. Not as one role to “level up” in… but as multiple domains to grow across. And the tools? They just sit on top. #DevOps #CloudComputing #LearningJourney #TechLearning #ContinuousLearning #SystemDesign #CICD #InfrastructureAsCode

📢 DevOps - Step By Step Learning: Networking for DevOps 📢 Do you want to know and learn "DevOps Fundamentals" from a software professional point of view? I am happy to share my writings about "DevOps—Step By Step Learning." In this post, I'd like to share the fundamental networking concepts that every IT professional should know. Please check out the following blogs and feel free to share your feedback in the comments. - Part 14 (Why Need Networking, What Theoretical and Practical Knowledge Should Know): https://lnkd.in/g-j6Punw - Part 15 (Learn Fundamental Networking Theoretical Knowledge): https://lnkd.in/gXd79mDj - Part 16 (How DNS and DHCP Operates in Application Layer): https://lnkd.in/gUs4m_3U - Part 17 (ARP Is The Bridge Between Data Link and Network Layer): https://lnkd.in/gawsU3d4 - Part 18 (NAT, PAT For Inner Private with Outer Public Network Handshaking): https://lnkd.in/gGSSesf6 - Part 19 (TCP and UDP Are The Backbone of Transport Layer): https://lnkd.in/gACdCgv4 - Part 20 (Hands On Networking Commands, Practically Connect The Theory): https://lnkd.in/gwK7WXsa Feel free to share with ones who you think can benefit from it. #learning #sharingknowledge #medium #blog #programming #software #engineering #devOps #networking

How I Debug Errors Step-by-Step – My Approach While learning development and DevOps, I realized one important skill: 👉 Debugging is more important than coding. Whenever I face an error, instead of getting stuck, I follow a simple process: 🔹 Step 1: Understand the error Carefully read the error message (it usually gives hints) 🔹 Step 2: Check logs Look into logs to find where exactly the issue is happening 🔹 Step 3: Break the problem Divide the issue into smaller parts and test one by one 🔹 Step 4: Search & Learn Use documentation and resources to understand the issue better 🔹 Step 5: Fix & Test again Apply the fix and re-test to confirm it's working While working with platforms like Amazon Web Services and using version control in GitHub, I understood how important debugging is in real-world projects. 💡 One thing I learned: Errors are not problems — they are opportunities to learn. Still improving my debugging skills every day 🚀 #Debugging #DevOps #AWS #LearningJourney #ProblemSolving #TechGrowth

Learning Kubernetes won’t make you a better engineer. And that’s where most people go wrong. --- Everyone is doing this: ✔ Learning Pods ✔ Learning Deployments ✔ Learning Helm And thinking: “I’m becoming a DevOps expert.” --- ❌ But here’s the problem: You’re learning Kubernetes in isolation. --- 🔥 Reality: Kubernetes is just a tool. Not a system. --- 🚨 The Kubernetes trap: ❌ Memorizing commands ❌ Copying YAML files ❌ Deploying without understanding --- 👉 What you SHOULD be learning: ✔ System design ✔ Platform architecture ✔ Observability ✔ Debugging real systems --- 🚀 The shift: Kubernetes Engineer ❌ Platform Engineer ✅ --- 💡 Top engineers don’t just deploy apps. They build platforms. --- If you’re only learning Kubernetes, You’re limiting your growth. --- 👇 Be honest: How are you learning? 1️⃣ Just Kubernetes 2️⃣ Learning systems 3️⃣ Moving to Platform Engineering --- Save this. Follow for daily DevOps & Cloud content. #Kubernetes #PlatformEngineering #DevOps #CloudComputing #Career

🚀 Struggling to understand Kubernetes? Watch this 👇 Most people learn Kubernetes like this: ❌ Random docs ❌ Confusing tutorials ❌ No real structure I changed that. 💡 🎥 In this video, I’ve broken down Kubernetes from ZERO → ADVANCED Using: 📝 Handwritten-style notes 📊 Clean diagrams & flows ⚡ Real DevOps concepts (not theory) ☸️ What You’ll Learn ☸️ Cluster Architecture (Control Plane vs Nodes) 📦 Pods, Namespaces, Labels ⚙️ Deployments, StatefulSets, Jobs 🌐 Services, Ingress, Networking 💾 Storage (PV, PVC) 🔐 RBAC & Security 📈 Autoscaling (HPA, VPA) 📊 Monitoring & Observability 🚀 Advanced (Helm, CRDs, Service Mesh) 🔁 Real DevOps Flow Developer 💻 → Docker 🐳 → Kubernetes ☸️ → Scaling 📈 → Monitoring 📊 💡 Why this video is different? ✔ Visual learning (not boring text) ✔ Beginner → Advanced in one flow ✔ Real-world DevOps perspective ⚠️ Don’t just learn Kubernetes… understand how it works in production. 💬 Tell me in comments: What’s the hardest part in Kubernetes for you? 🤔 🚀 #Kubernetes ☸️ #DevOps ⚙️ #AWS ☁️ #Docker 🐳 #CICD 🔁 #CloudComputing #K8s #DevOpsEngineer #LearnInPublic #Automation 🚀

🚀 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐂𝐡𝐞𝐚𝐭 𝐒𝐡𝐞𝐞𝐭 𝐭𝐡𝐚𝐭 𝐞𝐯𝐞𝐫𝐲 𝐃𝐞𝐯𝐎𝐩𝐬 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 𝐦𝐮𝐬𝐭 𝐬𝐚𝐯𝐞 If you're working with Kubernetes, this is your daily survival kit 👇 💡 𝐖𝐡𝐚𝐭 𝐲𝐨𝐮 𝐠𝐞𝐭 𝐢𝐧 𝐨𝐧𝐞 𝐩𝐥𝐚𝐜𝐞: ⚙️ 𝐂𝐥𝐮𝐬𝐭𝐞𝐫 & 𝐂𝐨𝐧𝐟𝐢𝐠 → kubectl version, cluster-info, contexts 📦 𝐏𝐨𝐝𝐬 & 𝐋𝐨𝐠𝐬 → get pods, describe, logs, exec 🚀 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭𝐬 → apply, scale, rollout, restart 🌐 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬 & 𝐈𝐧𝐠𝐫𝐞𝐬𝐬 → ClusterIP, NodePort, LoadBalancer 🗂️ 𝐂𝐨𝐧𝐟𝐢𝐠𝐌𝐚𝐩𝐬 & 𝐒𝐞𝐜𝐫𝐞𝐭𝐬 → manage configs securely 📊 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 & 𝐇𝐏𝐀 → autoscaling, metrics, events 🧠 𝐓𝐫𝐨𝐮𝐛𝐥𝐞𝐬𝐡𝐨𝐨𝐭𝐢𝐧𝐠 → CrashLoopBackOff, ImagePull errors 🔥 𝐖𝐡𝐲 𝐭𝐡𝐢𝐬 𝐦𝐚𝐭𝐭𝐞𝐫𝐬? Because Kubernetes is powerful… but also complex. And having this cheat sheet = faster debugging + better deployments 💬 𝐓𝐢𝐩: Don’t just read commands ❌ 👉 Practice them 👉 Break things 👉 Fix them That’s how real DevOps engineers grow 🚀 📌 Save this post if you’re learning DevOps / Cloud / Kubernetes Follow me for more practical tech content 👇 #Kubernetes #DevOps #CloudComputing #Docker #SoftwareEngineering #TechCareers #Learning #Programming #AI #CareerGrowth

🚀 DevOps Journey – From Basics to Cloud-Native Engineer Every journey starts with curiosity… mine started with learning Linux commands and understanding how systems work behind the scenes. 💡 Step 1: Strong Foundation I began with Linux, networking basics, and scripting. This helped me understand how applications run in real environments. 🐙 Step 2: Version Control & Collaboration Learned Git & GitHub to manage code efficiently and collaborate with teams. ⚙️ Step 3: CI/CD Automation Built pipelines using Jenkins to automate build, test, and deployment processes. This was a game changer! 🐳 Step 4: Containerization Worked with Docker to package applications and ensure consistency across environments. ☸️ Step 5: Orchestration Explored Kubernetes to manage containerized applications at scale. Learned deployments, services, autoscaling, and more. ☁️ Step 6: Cloud Platforms Hands-on experience with AWS & GCP: EC2, S3, IAM VPC, Load Balancers Cloud-native deployments 📊 Step 7: Monitoring & Logging Implemented monitoring using Grafana and logging using ELK stack to ensure system reliability. 🔐 Step 8: Security & Best Practices Integrated security into pipelines and infrastructure (DevSecOps mindset). 🌱 What I Learned DevOps is not just tools — it’s a culture of automation, collaboration, and continuous improvement. 📸 (Visual Journey Representation) 🟢 Linux → 🔵 Git → 🟣 Jenkins → 🐳 Docker → ☸️ Kubernetes → ☁️ Cloud → 📊 Monitoring → 🔐 Security 🔥 Still learning, still growing… Excited for what’s next in this DevOps journey! #DevOps #CloudComputing #AWS #Kubernetes #Docker #Jenkins #Automation #DevOpsJourney #Learning #Growth