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Subject Moderation Interface (SMI)

This page gives an overview of the Subject Moderation Interface (SMI), describing its current status, where and how it's developed and deployed, and who is responsible for maintaining it.

Warning

This is a prototype service that is not fully supported. See the FAQ for Subject Moderation Interface alpha for more details.

Service Description

The Subject Moderation Interface (SMI) service provides a web application for moderating undergraduate applications as part of the admissions process.

Service Status

The SMI is currently alpha.

Contact

Technical queries and support should be directed to servicedesk@uis.cam.ac.uk and will be picked up by a member of the team working on the service. To ensure that you receive a response, always direct requests to servicedesk@uis.cam.ac.uk rather than reaching out to team members directly.

Issues discovered in the service or new feature requests should be opened as GitLab issues here.

Environments

The SMI is currently deployed to the following environments:

Name Main Application URL Django Admin URL Backend API URL
Production https://alpha.subjectmoderationinterface.apps.cam.ac.uk/ https://alpha.subjectmoderationinterface.apps.cam.ac.uk/admin https://alpha.subjectmoderationinterface.apps.cam.ac.uk/api/
Staging https://staging.subjectmoderationinterface.apps.cam.ac.uk/ https://staging.subjectmoderationinterface.apps.cam.ac.uk/admin https://staging.subjectmoderationinterface.apps.cam.ac.uk/api/
Development https://webapp.devel.uga.gcp.uis.cam.ac.uk/ https://webapp.devel.uga.gcp.uis.cam.ac.uk/admin https://webapp.devel.uga.gcp.uis.cam.ac.uk/api/

The GCP console pages for managing the infrastructure of each component of the deployment are:

Name Main Application Hosting Database Synchronisation Job Application Hosting
Production GCP Cloud Run GCP Cloud SQL (Postgres) GCP Cloud Scheduler
Staging GCP Cloud Run GCP Cloud SQL (Postgres) GCP Cloud Scheduler
Development GCP Cloud Run GCP Cloud SQL (Postgres) GCP Cloud Scheduler

All environments share access to a set of secrets stored in the meta-project Secret Manager.

Source code

The source code for the SMI is spread over the following repositories:

Repository Description
Main Application The source code for the main application Docker image
Synchronisation Job Application The source code for the synchronisation job application Docker image
Infrastructure Deployment The Terraform infrastructure code for deploying the applications to GCP

Info

The synchronisation job application repository is named the "Pool Applicant Document Management" repository but the name is misleading as the application manages synchronisation with CamSIS, Google Drive and Google Sheets, and not just for applicant pooling purposes.

Technologies used

The following gives an overview of the technologies the SMI is built on.

Category Language Framework(s)
Web Application Backend Python 3.7 Django 2.2
Web Application Frontend JavaScript React 16.13.1
Synchronisation Job Application Python 3.8 Flask
Database PostgreSQL 11 n/a

Operational documentation

The following gives an overview of how the SMI is deployed and maintained.

How and where the SMI is deployed

Database for undergraduate applicant data is a PostgreSQL database hosted by GCP Cloud SQL. The main web application is a Django backend with React frontend, hosted by GCP Cloud Run. The synchronisation job application (which provides an API with end-points for synchronising the SMI database with other services) uses the Flask library, is hosted by GCP Cloud Run and invoked by GCP Cloud Scheduler.

The SMI infrastucture is deployed using Terraform, with releases of the main application and synchronisation job application deployed by the GitLab CD pipelines associated with the infrastructure deployment repository.

Deploying a new release

The README.md files in each of the source code repositories explain how to deploy the SMI.

Monitoring

  • GCP Cloud Monitoring
    • For tracking the health of applications in the environments and sending alert emails when problems are detected.
  • Cloud Logs (production, test (staging), development)
    • For tracking individual requests/responses to/from the web application and the synchronisation job application.

Debugging

The README.md files in each of the source code repositories provide information about debugging both local and deployed instances of the applications.

Operation

Applicant data is initially retrieved from CamSIS via a synchronisation job (managed by GCP Cloud Scheduler which periodically calls the synchronisation job API). Additional annotations are later added by manually importing the subject master spreadsheet (SMS) and subject-specific variants (using the Django admin application page (staging) for the appropriate environment).

Periodic synchronisation jobs ensure that each applicant has an associated folder on Google Drive (for storing additional documents). They also ensure that applicant data is consistent between the SMI and several linked Google Sheets spreadsheets: the expression of interest master list (EoIML) and poolside meeting outcome spreadsheets (PMOSs). A manually invoked process on CamSIS uses the SMI web application API to retrieve pooling decisions about applicants, and update the CamSIS database as necessary.

The flow of applicant data to/from the SMI and other services is summarised by the diagram below.

Flow of applicant data to/from the SMI

Further information is available in the Operational Documentation for the Undergraduate Admissions process.

Service Management and tech lead

The service owner for the SMI is TBD.

The service manager for the SMI is TBD.

The tech lead for the SMI is Dave Hart.

The following engineers have operational experience with the SMI and are able to respond to support requests or incidents: