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Duration 21 hours
Course Outline
Introduction to AI-Enhanced Kubernetes Operations
- The importance of AI in modern cluster management
- Limitations of conventional scaling and scheduling methods
- Core ML concepts applicable to resource management
Foundations of Kubernetes Resource Management
- Basics of CPU, GPU, and memory allocation
- Navigating quotas, limits, and resource requests
- Identifying system bottlenecks and inefficiencies
Machine Learning Approaches for Scheduling
- Supervised and unsupervised models for workload placement
- Predictive algorithms for estimating resource demand
- Integrating ML features into custom schedulers
Reinforcement Learning for Intelligent Autoscaling
- How RL agents adapt to cluster behavior
- Designing reward functions to drive efficiency
- Developing RL-based autoscaling strategies
Predictive Autoscaling with Metrics and Telemetry
- Leveraging Prometheus data for forecasting
- Applying time-series models to autoscaling decisions
- Assessing 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
- Lowering compute expenses through predictive scaling
- Enhancing GPU utilization via ML-driven placement
- Balancing latency, throughput, and operational efficiency
Practical Scenarios and Real-World Use Cases
- Managing high-load application autoscaling with AI
- Optimizing heterogeneous node pools
- Applying ML in multi-tenant environments
Summary and Next Steps
Requirements
- Working knowledge of Kubernetes core concepts
- Practical experience deploying containerized applications
- Proficiency in 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
