Day 16/40 - Kubernetes Requests and Limits - CKA Full Course 2025

About this video

### Summary of the Video Content: 1. **Introduction**: - The video is part of the CK 2024 series, specifically video number 16. - The topic focuses on **resource requests and limits** in Kubernetes, a key concept used by the scheduler to allocate pods to nodes. 2. **Objective**: - The video aims to explain how resource requests and limits work, why they are important, and what happens when pods exceed their allocated resources. - The creator sets a target of **180 likes and 180 comments** for the video to upload the next one within 24 hours. 3. **Key Concepts**: - **Nodes and Pods**: Nodes have specific CPU and memory capacities (e.g., 4 CPUs and 4 GB memory). Pods consume these resources for execution. - **Scheduling Process**: - The scheduler checks available nodes and assigns pods based on resource availability and other constraints like taints, tolerations, node selectors, and affinity. - If a node runs out of resources, the scheduler attempts to place the pod on another node. If no nodes have sufficient resources, the pod remains unscheduled with an "insufficient resources" error. - **Requests and Limits**: - **Requests**: The amount of CPU/memory a pod guarantees to use. - **Limits**: The maximum CPU/memory a pod can consume. - Without specifying these, a pod may consume all available resources, leading to node instability or crashes (OOM - Out of Memory errors). 4. **Demonstration**: - **Scenario 1**: A pod with specified requests (100 Mi) and limits (200 Mi) operates within bounds. Metrics show it uses 150 Mi, which is acceptable. - **Scenario 2**: A pod exceeds its memory limit (250 Mi vs. 100 Mi limit), resulting in the pod being OOM-killed. - **Scenario 3**: A pod requests more memory than available on any node (1000 Gi), causing it to remain in a pending state with an "insufficient memory" error. 5. **Metric Server**: - The Metric Server is introduced as a tool to expose CPU and memory utilization metrics for nodes and pods. - It is essential for features like auto-scaling (HPA, VPA) and monitoring resource usage. 6. **Importance of Requests and Limits**: - Prevents resource overconsumption by individual pods, ensuring cluster stability. - Avoids scenarios where a single pod monopolizes node resources, causing other pods to fail. 7. **Practical Exercises**: - Demonstrated using YAML files to define resource requests and limits for pods. - Showed how overriding limits or requesting excessive resources impacts pod scheduling and execution. 8. **Assignment and Resources**: - An assignment task is provided in the GitHub repository for viewers to practice. - Encourages viewers to refer to Kubernetes documentation (`kubernetes.io/docs`) for syntax and commands. 9. **Conclusion**: - The video emphasizes understanding and implementing resource requests and limits to manage Kubernetes clusters effectively. - Viewers are encouraged to engage with the content through likes, comments, and community support on Discord or YouTube. 10. **Call to Action**: - Complete the like and comment target to unlock the next video. - Continue practicing and exploring Kubernetes concepts to gain proficiency.

Course: Certified Kubernetes Administrator Full Course For beginners | CKA 2025

This playlist contains the complete CKA series for beginners, based on the latest 2025 curriculum. It includes 40+ videos with hands-on demos, assignments, and exam-based scenarios. We will cover everything from the basics to the Advanced, including fundamental concepts such as Docker, containers, Docker storage and networking, DNS, etc.