ESP32-S3 Bench Guide
ESP32-S3 N16R8 bench guide: live pinout, lessons, simulators and the bench log.
On-demand, isolated workshop environments (RStudio, JupyterLab) on Kubernetes.
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EducationPython · TypeScriptGitHub @orchestraplatformOnlineOwner unconfirmed
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The orchestra platform
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Taken from the repository README
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Orchestra Platform is a cloud-native, Kubernetes-based learning environment designed specifically for bioinformatics and data science education. It provides instructors and students with on-demand, isolated workshop environments that can be quickly provisioned and automatically managed.Read the full README ↗Orchestra Platform is a cloud-native, Kubernetes-based learning environment designed specifically for bioinformatics and data science education. It provides instructors and students with on-demand, isolated workshop environments that can be quickly provisioned and automatically managed.
Orchestra Platform enables educational institutions, research organizations, and training companies to deliver hands-on bioinformatics and data science workshops without the complexity of manual infrastructure management. Each workshop runs in its own isolated environment with dedicated resources, ensuring a consistent and reliable learning experience.
Orchestra Platform consists of four main components:
Each workshop gets its own unique subdomain and runs in complete isolation from other workshops.
Ready to start using Orchestra Platform? Check out our Installation Guide to set up your own instance, or jump to the User Guide to learn how to create your first workshop.
Orchestra Platform is open source and welcomes contributions from the community. Visit our GitHub repository to:
For questions and support, please check our documentation or open an issue on GitHub.
Orchestra is a cloud-native platform for managing self-service RStudio workshops on Kubernetes.
This monorepo contains all the components of the Orchestra platform:
docs/: Documentation website powered by Starlight/Astro.frontend/: React (TypeScript) dashboard for managing workshops.operator/: Kubernetes operator (Python/Kopf) that manages workshop lifecycles.server/: FastAPI backend that provides the API for the frontend and interacts with Kubernetes.brew install helm)brew install just)brew install uv)brew install node)Run once per machine to install Traefik and the Orchestra CRDs into your local cluster:
just dev-setup
This will:
kubectl context to docker-desktopWorkshop CRDjust setup
This installs frontend/docs packages and syncs Python projects with their dev
dependency groups, so commands like just test work without extra setup.
just dev
This starts the server, frontend, and operator in parallel as local processes (with hot-reload):
| Component | URL |
|---|---|
| Frontend | http://localhost:3000 |
| API | http://localhost:8080 |
| API docs | http://localhost:8080/docs |
| Docs site | run just dev-docs separately |
Note: Ports 8000 and 8001 are occupied by Docker Desktop on Mac; 8080 is used instead.
Workshops created via the UI will be reachable at http://<name>.127.0.0.1.nip.io:30080. No DNS configuration required — *.127.0.0.1.nip.io resolves to 127.0.0.1 automatically via the public nip.io service.
If you're working on the API or frontend only and don't need workshops to actually reconcile:
just dev-stack # server + frontend only
just dev-setup copies these automatically on first run:
server/.env.example → server/.env # API settings (gitignored)
frontend/.env.local.example → frontend/.env.local # VITE_API_URL etc (gitignored)
Edit them as needed after copying.
Refer to the README.md in each subdirectory for component-specific instructions.