Course Outline
Introduction to AI-Enhanced Kubernetes Operations
- The role of AI in modern cluster operations
- Constraints of conventional scaling and scheduling logic
- Core ML concepts for resource management
Foundations of Kubernetes Resource Management
- Basics of CPU, GPU, and memory allocation
- Comprehending quotas, limits, and resource requests
- Recognizing bottlenecks and operational inefficiencies
Machine Learning Approaches for Scheduling
- Supervised and unsupervised models for workload placement
- Predictive algorithms for estimating resource demand
- Incorporating 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-driven autoscaling strategies
Predictive Autoscaling with Metrics and Telemetry
- Leveraging Prometheus data for forecasting
- Applying time-series models to autoscaling logic
- 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 costs through predictive scaling
- Enhancing GPU utilization via ML-driven placement
- Striking a balance between latency, throughput, and efficiency
Practical Scenarios and Real-World Use Cases
- Autoscaling high-load applications using AI
- Optimizing heterogeneous node pools
- Applying ML techniques to multi-tenant environments
Summary and Next Steps
Requirements
- A solid grasp of Kubernetes fundamentals
- Hands-on experience with deploying containerized applications
- Proficiency in 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 3900 € + VAT*
Contact us for an exact quote and to hear our latest promotions
Testimonials (4)
basic understanding of container/kubernetes and how they interact features of the openshift plattform
Eric Scholze - NOW IT GmbH
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Yufri Isnaini Rochmat Maulana - Bank Indonesia
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How trainer deliver knowledge so effectively
Vu Thoai Le - Reply Polska sp. z o. o.
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The knowledge and exchanges with Augustin
