High Availability & Low Latency in Distributed Systems Using K8s
summary
Kubernetes plus an AI layer collects live metrics and runs LSTM forecasting for proactive autoscaling, isolation forest for anomaly detection, PPO placement RL to optimize scheduling and random forests to predict failures. The system enacts decisions in sub‑second to mitigate threats under 3 seconds, keeps RTO under 15 minutes and RPO under 5 minutes, and reports an 18% resource improvement, 31% infrastructure cost reduction and reduced incidents by 45% while maintaining 99.99% uptime.
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chapters (11)
- 0:00Introduction and Overview
- 0:41Challenges in Distributed Systems
- 2:07Kubernetes Foundations
- 3:23Integrating AI with Kubernetes
- 4:19AI Models for Optimization
- 5:17Real-Time Scaling and Resource Allocation
- 6:12Enhancing Security with AI
- 7:51Disaster Recovery and Fault Tolerance
- 9:07Real-World Applications and Results
- 10:50Future of Autonomous Infrastructure
- 12:05Conclusion and Q&A
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