Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Kubeflow
- Understanding the Kubeflow mission and architecture
- Core components and ecosystem overview
- Deployment options and platform capabilities
Working with the Kubeflow Dashboard
- User interface navigation
- Managing notebooks and workspaces
- Integrating storage and data sources
Kubeflow Pipelines Fundamentals
- Pipeline structure and component design
- Authoring pipelines with Python SDK
- Executing, scheduling, and monitoring pipeline runs
Training ML Models on Kubeflow
- Distributed training patterns
- Using TFJob, PyTorchJob, and other operators
- Resource management and autoscaling in Kubernetes
Model Serving with Kubeflow
- Overview of KFServing / KServe
- Deploying models with custom runtimes
- Managing revisions, scaling, and traffic routing
Managing ML Workflows on Kubernetes
- Versioning data, models, and artifacts
- Integrating CI/CD for ML pipelines
- Security and role-based access control
Best Practices for Production ML
- Designing reliable workflow patterns
- Observability and monitoring
- Troubleshooting common Kubeflow issues
Advanced Topics (Optional)
- Multi-tenant Kubeflow environments
- Hybrid and multi-cluster deployment scenarios
- Extending Kubeflow with custom components
Summary and Next Steps
Requirements
- An understanding of containerized applications
- Experience with basic command-line workflows
- Familiarity with Kubernetes concepts
Audience
- ML practitioners
- Data scientists
- DevOps teams new to Kubeflow
14 Hours
Testimonials (3)
About the microservices and how to maintenance kubernetes
Yufri Isnaini Rochmat Maulana - Bank Indonesia
Course - Advanced Platform Engineering: Scaling with Microservices and Kubernetes
How trainer deliver knowledge so effectively
Vu Thoai Le - Reply Polska sp. z o. o.
Course - Certified Kubernetes Administrator (CKA) - exam preparation
The knowledge and the patience from the trainer to answer to our questions.