Course Outline
Introduction to AI-Enhanced Kubernetes Operations for Government
- The Importance of AI in Modern Cluster Operations
- Limitations of Traditional Scaling and Scheduling Methods
- Key Concepts of Machine Learning 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
- Utilizing ML Features in 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 for Government
Requirements
- A solid understanding of Kubernetes fundamentals
- Practical experience with deploying containerized applications
- Knowledge of cluster operations and resource management
Audience for Government
- Site Reliability Engineers (SREs) working with large-scale distributed systems
- Kubernetes operators responsible for managing high-demand workloads
- Platform engineers focused on optimizing compute infrastructure
Testimonials (5)
The HPA and VPA
Iulian Popov
Course - Kubernetes Advanced
he was patience and understood that we fall behind
Albertina - REGNOLOGY ROMANIA S.R.L.
Course - Deploying Kubernetes Applications with Helm
The training was more practical
Siphokazi Biyana - Vodacom SA
Course - Kubernetes on AWS
Learning about Kubernetes.
Felix Bautista - SGS GULF LIMITED ROHQ
Course - Kubernetes on Azure (AKS)
It gave a good grounding for Docker and Kubernetes.