Course Outline
Introduction to AI-Powered Kubernetes Operations
- The significance of AI in contemporary cluster management
- Constraints of conventional scaling and scheduling mechanisms
- Fundamental ML concepts for resource administration
Core Principles of Kubernetes Resource Management
- Basics of CPU, GPU, and memory provisioning
- Navigating quotas, limits, and requests
- Detecting performance bottlenecks and inefficiencies
Machine Learning Strategies for Scheduling
- Supervised and unsupervised models for optimal workload placement
- Predictive algorithms for estimating resource requirements
- Incorporating ML features into custom schedulers
Reinforcement Learning for Smart Autoscaling
- How RL agents interpret cluster dynamics
- Crafting reward functions for peak efficiency
- Developing autoscaling strategies guided by RL
Predictive Autoscaling via Metrics and Telemetry
- Utilizing Prometheus data for future demand forecasting
- Implementing time-series models in autoscaling processes
- Assessing forecast accuracy and refining model parameters
Deploying AI-Driven Optimization Tools
- Integrating ML frameworks with Kubernetes controllers
- Implementing intelligent control loops
- Expanding KEDA capabilities for AI-assisted decision-making
Strategies for Cost and Performance Enhancement
- Cutting compute costs through proactive scaling
- Boosting GPU efficiency via ML-guided placement
- Harmonizing latency, throughput, and operational efficiency
Practical Scenarios and Real-World Applications
- Managing high-load application scaling with AI
- Optimizing diverse node pools
- Applying ML techniques in multi-tenant settings
Conclusion and Future Steps
Requirements
- A solid grasp of core Kubernetes principles
- Hands-on experience in deploying containerized applications
- Proficiency in cluster administration and resource governance
Target Audience
- SREs managing extensive distributed systems
- Kubernetes administrators handling high-load workloads
- Platform engineers focused on compute infrastructure optimization
Testimonials (3)
basic understanding of container/kubernetes and how they interact features of the openshift plattform
Eric Scholze - NOW IT GmbH
Course - Introduction to Containers, Kubernetes & OpenShift
About the microservices and how to maintenance kubernetes
Yufri Isnaini Rochmat Maulana - Bank Indonesia
Course - Advanced Platform Engineering: Scaling with Microservices and Kubernetes
The training met expectations with its clear explanations, real-world examples, and hands-on labs that made complex topics easy to understand. It provided valuable insights into container orchestration, security, scaling and many other advanced topics.
