Container Orchestration for Research Workflows
Overview of the Workshop
This workshop provides researchers with a comprehensive guide on containerizing and orchestrating data pipelines. Participants will gain hands-on experience with Docker, Docker Compose, and Kubernetes, and will learn to build and deploy a UI for visualizing data. The workshop focuses on practical applications of container orchestration to enhance research workflows.
Agenda
1. Overview of the Workshop
- Introduction to the goals and structure of the workshop
- Explanation of key concepts and technologies
2. Use Case: Containers for Research
- Benefits of using containers for research purposes
- Detailed use case: Containerizing data pipelines
3. Introduction to Containers and Kubernetes
- Understanding the basics of containers
- Overview of Kubernetes and its components
4. Data Processing with Jupyter Notebooks
- Review and understand the data processing Jupyter notebook
5. Building ETL Containers
- Create containers for the Extract, Transform, and Load (ETL) processes
6. Deploying ETL Containers
- Use Docker Compose to deploy ETL containers
7. Building a UI Container
- Build a containerized UI application to visualize transformed data
8. Deploying the UI Container
- Deploy the UI container using Kubernetes
9. Customization Section
- Deploying to different cloud providers: AWS, GCP, and Azure
Repo Folder Structure
Container-Orchestration-for-Research-Workflows/
├── README.md
├── Dockerfile
├── docker-compose.yml
├── k8s/
│ ├── deployment.yaml
│ ├── service.yaml
│ ├── ingress.yaml
│ ├── configmap.yaml
│ ├── secret.yaml
├── notebooks/
│ ├── data_processing_notebook.ipynb
├── scripts/
│ ├── extract.py
│ ├── transform.py
│ ├── load.py
│ ├── ui/
│ │ ├── app/
│ │ │ ├── package.json
│ │ │ ├── package-lock.json
│ │ │ ├── src/
│ │ │ │ ├── index.js
│ │ │ │ ├── components/
│ │ │ │ │ ├── VisualizationComponent.js
│ │ │ │ ├── public/
│ │ │ │ │ ├── index.html
