Course Outline
Introduction
- Introduction to Kubernetes for government use
- Overview of Kubeflow Features and Architecture for government applications
- Kubeflow on AWS vs on-premise vs on other public cloud providers for government environments
Setting up a Cluster using AWS EKS for government operations
Setting up an On-Premise Cluster using Microk8s for government infrastructure
Deploying Kubernetes using a GitOps Approach for government workflows
Data Storage Approaches for government data management
Creating a Kubeflow Pipeline for government projects
Triggering a Pipeline for government processes
Defining Output Artifacts for government compliance
Storing Metadata for Datasets and Models for government record-keeping
Hyperparameter Tuning with TensorFlow for government research
Visualizing and Analyzing the Results for government decision-making
Multi-GPU Training for government high-performance computing
Creating an Inference Server for Deploying ML Models for government services
Working with JupyterHub for government collaboration
Networking and Load Balancing for government network architecture
Auto Scaling a Kubernetes Cluster for government resource optimization
Troubleshooting for government IT support
Summary and Conclusion for government stakeholders
Requirements
- Familiarity with Python syntax for government applications
- Experience with TensorFlow, PyTorch, or other machine learning frameworks
- An AWS account equipped with the necessary resources
Audience
- Developers for government projects
- Data scientists for government initiatives
Testimonials (1)
I enjoyed participating in the Kubeflow training, which was held remotely. This training allowed me to consolidate my knowledge for AWS services, K8s, all the devOps tools around Kubeflow which are the necessary bases to properly tackle the subject. I wanted to thank Malawski Marcin for his patience and professionalism for training and advice on best practices. Malawski approaches the subject from different angles, different deployment tools Ansible, EKS kubectl, Terraform. Now I am definitely convinced that I am going into the right field of application.
