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Integrated Threat Assessment Platform

Create an application using a multi-cloud approach that epidemiologists can use to upload health-related data and generate weekly reports based on the outcome of the data.

Description: There was previously no well-known way for epidemiologists across the country to be able to report and escalate their findings about public health data (such as outbreaks) on the federal level and this basic functionality needed to be built into PHAC. Therefore there was a small initial team creating a Django App on Azure and GCP which would act as a data repository for this information and be able to create reports based on the information to determine what warranted further investigation/discussion. Since this was a novel approach, there were many options and many things considered and we wanted some flexibility so although the tool we decided was a Django app, the multi-cloud approach gave us some flexibility in where we could house the app.

Roles and Responsibilities: Full-stack and Cloud Developer

  • As one of the Lead Developers on the project it was on me to onboard junior and intermediate developers to the project and answer any questions they might have about the code base while ensuring deadlines were met and overseeing/reviewing all their Pull Requests
  • Later on, I became the Scrum Master for the project and needed to teach and lead my team to continue development in an Agile approach (Scrum) while also ensuring that the business/client side also followed this method to have the ability for CI/CD and incremental improvements to the application
  • To streamline a lot of the deployment and keep code quality, I created multiple different layers of CI/CD pipelines from linting of the code to ensure code quality before they got merged to the production code base, there were multi-cloud automated CI/CD pipelines built for each cloud provider (Azure/GCP) for both a ‘dev’ and ‘prod’ instances with the appropriate locks/checks in place depending on where the code was being pushed to.
  • Developed a small test suite for further testing of the code (regression and smoke testing) before it could be pushed to production

Project Duration: 2 years

Environment:

  • Git Bash
  • Python
  • Django
  • GCP Cloud SQL
  • GCP Container Registry
  • GCP Kubernetes clusters
  • GCP IAM
  • GCP GenAI
  • GCP DocAI
  • Azure
  • Azure Pipelines
  • Azure Repo
  • Azure Ticketing System
  • HTMX
  • JINJA2
  • Docker
  • CI/CD pipelines
  • GitHub Actions
  • GitHub Projects
  • git
  • .docx
  • .xlsx
  • .csv
  • PostgreSQL