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Duration 21 hours
Course Outline
Introduction to AI-Augmented Kubernetes Operations
- The significance of AI in modern cluster management
- Constraints of conventional scaling and scheduling methods
- Core ML concepts for resource administration
Basics of Kubernetes Resource Management
- Essentials of CPU, GPU, and memory distribution
- Comprehending quotas, limits, and requests
- Pinpointing bottlenecks and inefficiencies
Machine Learning Techniques for Scheduling
- Supervised and unsupervised models for workload positioning
- Predictive algorithms for resource demand estimation
- Incorporating ML features into custom schedulers
Reinforcement Learning for Smart Autoscaling
- How RL agents adapt based on cluster behavior
- Creating reward functions for enhanced efficiency
- Developing RL-based autoscaling strategies
Predictive Autoscaling via Metrics and Telemetry
- Leveraging Prometheus data for forecasting
- Applying time-series models to autoscaling processes
- Assessing prediction accuracy and model tuning
Deploying AI-Powered Optimization Tools
- Integrating ML frameworks with Kubernetes controllers
- Implementing intelligent control loops
- Enhancing KEDA for AI-assisted decision-making
Strategies for Cost and Performance Optimization
- Lowering compute expenses through predictive scaling
- Boosting GPU utilization via ML-guided placement
- Balancing latency, throughput, and efficiency
Practical Scenarios and Real-World Applications
- Autoscaling high-load applications with AI
- Optimizing heterogeneous node pools
- Applying ML in multi-tenant environments
Summary and Future Steps
Requirements
- A solid grasp of Kubernetes fundamentals
- Experience in deploying containerized applications
- Knowledge of cluster operations and resource management
Target Audience
- SREs managing large-scale distributed systems
- Kubernetes operators handling high-demand workloads
- Platform engineers focused on optimizing compute infrastructure
Testimonials (2)
As i said before , for a person like me (no exp. ) this was a gateway to understanding features and functions with these programs/tools & etc. .
Patrick V. Duylovski - UBB + DZI (KBC GROUP)
Course - Docker and Kubernetes
basic understanding of container/kubernetes and how they interact features of the openshift plattform
