Kubernetes from Scratch - Kubernetes Resource Requests & Limits Explained in Tamil | CPU & Memory Control

Welcome to the channel! 👋 📄 Documentation & Resources Kubernetes Resource Limit and Resource Request: GitHub Link - https://github.com/simplybyte1266/documentation/blob/main/kubernetes/resource-limit-and-request/guide.md ▶️ Kubernetes from Scratch Playlist Watch the full playlist for more tutorials and hands-on examples. https://www.youtube.com/playlist?list=PL1yVd92q9OP6305trQ-7q0fyI_sRM9tZa 🔗 Connect with Me Instagram: @simply_byte [https://www.instagram.com/simply_byte] LinkedIn: Simply Byte [https://www.linkedin.com/in/simplybyte] In this video, we will understand Kubernetes Resource Requests and Resource Limits with a real-world production scenario explained in Tamil. 🔹 Many times in Kubernetes, applications suddenly become slow even though they were working fine earlier. 🔹 This video explains why that happens and how Resource Requests & Limits solve this problem. 🔍 Scenario Explained in This Video 👉 We have: One Spring Boot Java application One Python application Both deployed in the same Kubernetes cluster Initially, everything works fine. Suddenly, the Python application becomes very slow. ❓ Why? Java application starts consuming more CPU & Memory Possible memory leak Python pod doesn’t get enough resources Kubernetes scheduler still schedules new pods on the same node 🤯 🛠 Solution: Resource Requests & Resource Limits ✅ Resource Requests Minimum CPU & Memory required for a Pod Scheduler checks availability before scheduling Prevents Pods from being scheduled on overloaded nodes ✅ Resource Limits Maximum CPU & Memory a Pod can use If memory exceeds → Pod gets Killed & Restarted Protects other Pods from disturbance 🚀 Why This Is Important? ✔ Prevents one Pod from affecting others ✔ Avoids unexpected slowdowns ✔ Mandatory for production-grade Kubernetes applications ✔ Very important for DevOps & Kubernetes interviews 📌 Topics Covered Kubernetes Resource Requests Kubernetes Resource Limits CPU & Memory Management Scheduler Behavior Real-time Production Issue Best Practices