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Course Outline
Introduction to AI-Enhanced Kubernetes Operations
- Why AI matters for modern cluster operations
- Limitations of traditional scaling and scheduling logic
- Key concepts of ML for resource management
Foundations of Kubernetes Resource Management
- CPU, GPU, and memory allocation fundamentals
- 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
- Using 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
Requirements
- An understanding of Kubernetes fundamentals
- Experience with containerized application deployments
- Familiarity with cluster operations and resource management
Audience
- SREs working with large-scale distributed systems
- Kubernetes operators managing high-demand workloads
- Platform engineers optimizing compute infrastructure
21 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €6840 online delivery, based on a group of 2 delegates, €2160 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
Please see our public courses
Testimonials (5)
Interactivity, no reading slides all day
Emilien Bavay - IRIS SA
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.
