Nectar Jupyter Notebook Service

Modified on Mon, 8 Jan at 3:35 PM

The ARDC Nectar Cloud is now hosting a managed Jupyter Notebook service.


What are the specifications?


Users will receive 10GB storage, and up to 4 vCPUs and 7.5GB RAM for their Jupyter Notebook workspace.


How do I access it?


You can log in with your Institutional/University credentials (via the AAF, Australian Access Federation) to access this service. If you do not have access via AAF/your institution, click here for more information.

Upon logging in you will have a choice of which type of environment you would like including: 


1. Minimal (adds command line tools useful when working in Jupyter applications)

2. Data science (includes libraries for data analysis from the Julia, Python, and R communities)

3. SciPy environment (includes popular packages from the scientific Python ecosystem)

4. R environment (includes popular packages from the R ecosystem)


Once selected you will then see a launcher area, with options for the particular notebook you would like (Python, Julia etc). You will also see a file navigation area on the right hand side.


How long can I use it for?


Your session will remain active for approximately one hour after you close your browser tab, or you can manually terminate your session by clicking the 'Stop My Server' button from the JupyterHub control panel. At any time you can log back in and start a new session with your notebooks available as they were, but any notebook cells will need to be re-run as you'll be starting a new kernel.


I need more resources to run my Jupyter Notebook, is that available?


Yes. However, you need to access the application service via the Nectar Dashboard to do this. If you do not already have one, you will also need to apply for a Project with allocation of Cloud resources to use within the dashboard. For information about setting up the Jupyter Notebook, view this article. 


Can I access the service via SSH? 


No, but you can access a terminal session via the Jupyter Notebook main page. 


I want to learn more about Jupyter Notebook, where can I find resources?


To start with, here are a few resources which may be useful: 



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