Скачать или смотреть Autonomous Optimization for Kubernetes Applications and Clusters

Kubernetes resource configuration, the complexities of optimization and management, and the role of autonomous and machine learning solutions in this process. The session covers container resource requests and limits, CPU and memory distribution in Kubernetes and best practices for setting resources in a Kubernetes environment.

Speakers:
Pooja Malik - Principal Engineer Sedai
Vinod Sethumadhavan - Principal Engineer Sedai


00:00 Introduction
00:22 Speaker and Session
01:18 Understanding Requests and Limits in Kubernetes
02:35 Understanding CFS Shares and Quota
05:52 Best Practices for Setting Resources
07:03 Challenges in Managing Kubernetes
08:54 Auto Scaling Solutions in Kubernetes
10:07 Complexities Requiring Machine Learning and Autonomous Systems
12:01 Comparison of Tools and Approaches in the Industry
14:14 Rightsizing Workloads and Performance Optimization
20:50 Node Optimization and Selection
23:26 Monitoring-based Optimization
24:37 Application Performance and Memory Optimization
26:14 Cost Reduction through Workload Optimization
28:23 Hybrid Approach for Predictive and Reactive Scaling
31:12 AI Engines and Anomaly Detection
33:23 Autonomous Approach in Kubernetes

Learn more about Sedai: sedai.io
You can also see the autocon/23 videos on Sedai's website: sedai.io/autocon23
Follow Pooja Malik on LinkedIn:   / pooja-malik-792b1710   and Vinod Sethumadhavan on LinkedIn:   / vinod-sethumadhavan  

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