Fix Version/s: None
This epic focuses on metric monitoring and visualisation both through the SQuaSH harness and the JupyterLab-based Notebook Environment of the LSST Science Platform.
This epic includes a migration to the Flask API to eliminate DJANGO from our toolchain and make SQuaSH technically consistent with other SQuaRE services
A major deliverable for S18 is to provide a document or tutorial of the current capabilities of the platform and seek input from the DM teams on priorities for further development.
(Note this epic will start late as the epics behind it are not closed yet).
As a result of this epic, we have a new implementation fo the SQuaSH RESTful API in Flask, compatible with lsst.verify and uploading data blobs to AWS S3. It is deployed at https://squash.lsst.codes and have been collecting data from CI runs for ~2 weeks now.
SQR019 was updated to demonstrate its use with lsst.verify and a sandbox instance of SQuaSH was deployed as requested by the System Verification group.
The DJANGO to flask migration is done in in production.
Further input will be provided via the QA working group.
Moving the stories related to the API migration from Django to Flask into this epic.