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Duration 21 hours
Course Outline
Introduction to AI-Enhanced Kubernetes Management
- The role of AI in modern cluster administration
- Constraints of conventional scaling and scheduling methodologies
- Fundamental ML concepts applied to resource governance
Basics of Kubernetes Resource Governance
- Core principles of CPU, GPU, and memory allocation
- Mastering quotas, limits, and resource requests
- Detecting system bottlenecks and operational inefficiencies
ML Strategies for Workload Scheduling
- Employing supervised and unsupervised models for optimal placement
- Predictive algorithms for anticipating resource demand
- Integrating ML features into custom scheduler logic
Reinforcement Learning for Intelligent Autoscaling
- How RL agents derive insights from cluster dynamics
- Constructing reward functions to drive efficiency
- Developing RL-based autoscaling frameworks
Predictive Autoscaling via Metrics and Telemetry
- Leveraging Prometheus data for accurate forecasting
- Applying time-series models to autoscaling decisions
- Assessing prediction reliability and model tuning
Deploying AI-Driven Optimization Tools
- Integrating ML frameworks with Kubernetes controllers
- Implementing intelligent control loops
- Enhancing KEDA for AI-assisted decision processes
Cost and Performance Refinement Strategies
- Lowering compute expenses via predictive scaling
- Boosting GPU utilization through ML-guided placement
- Optimizing the balance between latency, throughput, and efficiency
Real-World Scenarios and Use Cases
- Scaling high-traffic applications with AI assistance
- Optimizing heterogeneous node pools
- Applying ML techniques in multi-tenant environments
Summary and Future Pathways
Requirements
- Core understanding of Kubernetes principles
- Proven experience in deploying containerized applications
- Proficiency in cluster administration and resource governance
Target Audience
- SREs overseeing large-scale distributed systems
- Kubernetes specialists managing high-intensity workloads
- Platform engineers focused on optimizing compute resources
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
