HDFLab is a JupyterHub/JupyterLab workspace that is managed by The HDF Group. HDFLab enables members of the HDF community to run Python, Julia, and R codes in the cloud just using their browser.
When you sign into HDF Lab, you have access to a compute environment that is setup for you to start using HDF immediately—no need to install software, download data, or otherwise wrestle with your system (see: https://xkcd.com/1987/). In HDF Lab you have access to the equivalent of a powerful desktop computer running in the cloud that is available whenever you need it.
Key aspects of HDF Lab are the JupyterLab interface, pre-installed software, and access to the cloud:
HDF Lab access starts off with a 30-day free trial, and thereafter is just $10/month or $100/year. This gives you access to 8GB RAM for running your Jupyter Notebooks, 10GB local disk, and 200GB of storage on HDF Server.
|Convenience||Computer environment is setup with all software needed to start using HDF. immediately|
|Learn||HDF Tutorial and examples enable you to quickly develop and understanding of HDF and related tools|
|Cloud Access||Run code in the cloud without needing to set up (and pay for) an account with a cloud provider|
|Data||Access Petabytes of data that are available in the cloud|
|Experiment||Try out using HDF5 and HSDS in HDF Lab. If it’s suitable for your application, but you need more capacity then is available with HDF Lab, you can setup a similar environment in your own cloud account or on-premise system|
|Performance||Harness power of a computer cluster using HSDS|
|Scalability||Any number of users can use HDF Lab simultaneously (let us know if you plan on hosting a class on HDF Lab so we can properly scale the system)|
|Sharing||Share HDF data with other HDF Lab users (you control exactly what and who you share with)|
HDF Lab runs as a set of components (pods) on a Kubernetes cluster in AWS. When a user signs in to HDF Lab, they are authenticated using their HDF Group credentials, then a new pod is spun up that will host their virtual computing environment. Each user pod is linked with a virtual disk drive of 10 GB that can be used to store notebooks, code, or data files. Any information you store on the drive will be available to you next time you log in.
In addition, you will have access to the HSDS service (which itself is running as a set of pods). HSDS enables high performance read/write access to content stored on AWS S3. Since your compute environment, HSDS, and S3 are all located in the same AWS Region, and share a high-speed network, you get much better performance compared with accessing cloud data from your desktop computer.
On HSDS there are example data files under “/shared/” that all HDF Lab users have access too. In addition, the folder /home/<username>/ will be available for you to host whatever data you like—up to 200 GB.
Visit the HDF Lab FAQs on our support site.
Content the Help Desk or post on question on the HSDS forum.