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Duration 21 hours
Course Outline
Introduction to AI-Enhanced Kubernetes Operations
- The significance of AI in modern cluster operations
- Constraints of conventional scaling and scheduling logic
- Core ML concepts applied to resource management
Basics of Kubernetes Resource Management
- Fundamentals of CPU, GPU, and memory allocation
- Understanding quotas, limits, and requests
- Detecting bottlenecks and inefficiencies
ML Techniques for Workload Scheduling
- Supervised and unsupervised models for workload placement
- Predictive algorithms for anticipating resource demand
- Incorporating ML features into custom schedulers
Reinforcement Learning for Advanced Autoscaling
- How RL agents adapt based on cluster behavior
- Designing reward functions to drive efficiency
- Creating autoscaling strategies guided by RL
Predictive Autoscaling Using Metrics and Telemetry
- Leveraging Prometheus data for forecasting
- Applying time-series models to autoscaling processes
- Assessing prediction accuracy and tuning models
Deploying AI-Driven 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 costs via predictive scaling
- Boosting GPU utilization through ML-driven placement
- Balancing latency, throughput, and overall efficiency
Real-World Scenarios and Practical Applications
- AI-based autoscaling for high-load applications
- Optimizing heterogeneous node pools
- Applying ML in multi-tenant environments
Conclusion and Future Steps
Requirements
- A solid grasp of Kubernetes fundamentals
- Practical experience with deploying containerized applications
- Knowledge of cluster operations and resource management
Target Audience
- SREs managing large-scale distributed systems
- Kubernetes administrators 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
