## Before the 30th of July (TBD) - [ ] Accelerate the first time startup of the QeApp (and full-stack if possible) - [ ] Use a light weight scheduler for running calculations on the container with limited amount of resource. - [ ] Understand how Kubernetes manages the load: - [ ] Is it able to move a pod from one node to another - [x] Understand the scaling mechanism - [ ] Understand how the scaling works in the JupyterHub context. - [ ] Understand the culling mechanism implemented in JupyterHub ## Before the 4th of March (Mon) - [x] #14 * Guaranteed: 1 CPU and 4 GB * Max: 2 CPU, 8 GB - [x] #15 - [x] Send a link to @cpignedoli and @giovannipizzi, make sure they have access. ## Before the next meeting 9th of April (Tue) * Reduce the startup time of both AiiDAlab and QE containers. * Enable persistent storage * Configure storage lifetime * Text for different pages on AiiDAlab (by @cpignedoli and @giovannipizzi) ## Further developments * For the aiidalab-demo to investigate the Materials Cloud Archive data some interface (probably in the Home app) needs to be implemented. * A new user should see a quick demo on how to use the server. * Communicate to the user the limitations of the demo server.
Before the 30th of July (TBD)
Before the 4th of March (Mon)
Before the next meeting 9th of April (Tue)
Further developments