Course Outline
Foundations of MLOps on Kubernetes
- Core principles of MLOps
- Distinguishing MLOps from traditional DevOps
- Primary challenges in managing the ML lifecycle
Containerization of ML Workloads
- Packaging models and associated training code
- Optimizing container images for machine learning
- Managing dependencies to ensure reproducibility
CI/CD for Machine Learning
- Structuring ML repositories to facilitate automation
- Incorporating testing and validation stages
- Triggering pipelines for retraining and model updates
GitOps for Model Deployment
- Understanding GitOps principles and workflows
- Leveraging Argo CD for model deployment
- Managing version control for models and configurations
Pipeline Orchestration on Kubernetes
- Constructing pipelines using Tekton
- Managing complex, multi-step ML workflows
- Handling scheduling and resource allocation
Monitoring, Logging, and Rollback Strategies
- Tracking data drift and assessing model performance
- Integrating alerting and observability tools
- Implementing rollback and failover mechanisms
Automated Retraining and Continuous Improvement
- Designing effective feedback loops
- Automating scheduled retraining processes
- Integrating MLflow for tracking and experiment management
Advanced MLOps Architectures
- Deployment models for multi-cluster and hybrid-cloud environments
- Enabling team scaling through shared infrastructure
- Addressing security and compliance requirements
Summary and Next Steps
Requirements
- A solid grasp of Kubernetes fundamentals
- Practical experience with machine learning workflows
- Proficiency in Git-based development practices
Target Audience
- ML Engineers
- DevOps Engineers
- ML Platform Teams
Testimonials (4)
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
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.
