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Duration 21 hours
Course Outline
Introduction to AI-Enhanced Kubernetes Operations
- The significance of AI in modern cluster operations
- Limitations inherent in traditional scaling and scheduling logic
- Core concepts of ML applied to resource management
Foundations of Kubernetes Resource Management
- Fundamentals of CPU, GPU, and memory allocation
- Comprehending quotas, limits, and requests
- Identifying system bottlenecks and inefficiencies
Machine Learning Approaches for Scheduling
- Supervised and unsupervised models for workload placement
- Predictive algorithms for estimating resource demand
- Incorporating ML features into custom schedulers
Reinforcement Learning for Intelligent Autoscaling
- How RL agents adapt from cluster behaviour
- Designing reward functions for maximum efficiency
- Constructing RL-driven autoscaling strategies
Predictive Autoscaling with Metrics and Telemetry
- Utilising Prometheus data for forecasting
- Applying time-series models to autoscaling processes
- Assessing prediction accuracy and tuning models
Implementing AI-Driven Optimisation Tools
- Integrating ML frameworks with Kubernetes controllers
- Deploying intelligent control loops
- Extending KEDA for AI-assisted decision-making
Cost and Performance Optimisation Strategies
- Reducing compute costs through predictive scaling
- Enhancing GPU utilisation via ML-driven placement
- Balancing latency, throughput, and efficiency
Practical Scenarios and Real-World Use Cases
- Autoscaling high-load applications with AI
- Optimising heterogeneous node pools
- Applying ML to multi-tenant environments
Summary and Next Steps
Requirements
- A solid grasp of Kubernetes fundamentals
- Experience deploying containerised applications
- Competency in cluster operations and resource management
Audience
- SREs managing large-scale distributed systems
- Kubernetes operators overseeing high-demand workloads
- Platform engineers focused on optimising 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
