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Duration 14 hours
Course Outline
Foundations of MLOps on Kubernetes
- Core principles of MLOps
- Distinguishing MLOps from traditional DevOps
- Primary challenges in managing the ML lifecycle
Containerizing ML Workloads
- Packaging models and associated training code
- Optimizing container images specifically for ML workloads
- Managing dependencies to ensure reproducibility
CI/CD for Machine Learning
- Structuring ML repositories to facilitate automation
- Incorporating testing and validation stages into the pipeline
- Automating triggers for retraining and model updates
GitOps for Model Deployment
- Key principles and workflows of GitOps
- Utilizing Argo CD for streamlined model deployment
- Implementing version control for models and configurations
Pipeline Orchestration on Kubernetes
- Constructing pipelines using Tekton
- Managing complex, multi-step ML workflows
- Optimizing scheduling and resource allocation
Monitoring, Logging, and Rollback Strategies
- Tracking data drift and monitoring model performance
- Integrating alerting systems 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
- Scaling teams through shared infrastructure
- Addressing security and compliance requirements
Summary and Next Steps
Requirements
- A solid understanding 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 (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.
