Course Outline
Introduction to AI-Enhanced Kubernetes Operations
- The role of AI in modern cluster operations
- Limitations of traditional scaling and scheduling logic
- Core ML concepts for resource management
Foundations of Kubernetes Resource Management
- Fundamentals of CPU, GPU, and memory allocation
- Understanding quotas, limits, and requests
- Identifying bottlenecks and inefficiencies
Machine Learning Approaches for Scheduling
- Supervised and unsupervised models for workload placement
- Predictive algorithms for resource demand
- Incorporating ML features into custom schedulers
Reinforcement Learning for Intelligent Autoscaling
- How RL agents learn from cluster behavior
- Designing reward functions for efficiency
- Building RL-driven autoscaling strategies
Predictive Autoscaling with Metrics and Telemetry
- Using Prometheus data for forecasting
- Applying time-series models to autoscaling
- Evaluating prediction accuracy and tuning models
Implementing AI-Driven Optimization Tools
- Integrating ML frameworks with Kubernetes controllers
- Deploying intelligent control loops
- Extending KEDA for AI-assisted decision-making
Cost and Performance Optimization Strategies
- Reducing compute costs through predictive scaling
- Improving GPU utilization with ML-driven placement
- Balancing latency, throughput, and efficiency
Practical Scenarios and Real-World Use Cases
- Autoscaling high-load applications with AI
- Optimizing heterogeneous node pools
- Applying ML to multi-tenant environments
Summary and Next Steps
Requirements
- A solid understanding of Kubernetes fundamentals
- Experience with deploying containerized applications
- Familiarity with cluster operations and resource management
Target Audience
- SREs managing large-scale distributed systems
- Kubernetes operators overseeing high-demand workloads
- Platform engineers focused on optimizing compute infrastructure
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 4800 € + VAT*
Contact us for an exact quote and to hear our latest promotions
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
