Optimizing Supply Chain Processes with Real-Time Analytics Platform

Applications and Data

• Microsoft stack: C#, ASP. NET Core 
  - Implementing the backend API and serverless functions
• Distributed Services Architecture
• Azure Data Factory 
  - Automating ETL data processing of supply chain data
• Azure SQL 
  - Enabling near real-time operational analytics scenarios: using column store indexes, memory-optimized tables, dynamic stored procedures
• Databricks 
  - PySpark application for scenario cost calculation and simulation
  - Spark, PySpark, DevOps
  - Azure Function to orchestrate job execution

Frontend Technologies

Angular

• Modular design paired with lazy loading for fast load time
• Implementation of the custom component library using core Angular features like reactive forms, content projection, and Angular templates with a focus on performance, reusability, and developer experience.
  - All components apply On push change detection strategy for maximum performance
  - By focusing on reusability we were able to streamline the development of the client’s other projects
  - We took inspiration for component structure design from the Angular Material library to enhance developers' experience
• Async pipe subscription pattern to minimize the risk of memory leaks
• Sass style preprocessor with BEM naming for scope control

Mapbox

• Integration with wrapper Angular library using directives and components
• Mapbox Geocoding API for forward and reverse geocoding

AG-Grid

• Displaying and editing data directly from tables
• Custom field types and restrictions
• Exporting data from the tables

DevOps

• Git
  - Version control and a multi-repository project structure were used. Each component of the MFO system had its own repository and CI/CD pipelines.
• Azure DevOps
  - The one-stop shop for all the MFO agile processes. We used it to plan, collaborate and deploy our solution.
• Docker
  - Our solution was containerized with Docker and Docker Compose so that developers could have the whole microservice architecture up locally and with one command.
• IaaC Terraform, Terragrunt (GitOps)
  - Provisioning the infrastructure on Azure with a combination of terraform and terragrunt. Resources were defined in terraform modules and configured with terragrunt.

Microsoft Azure Cloud

• Azure SQL Database
  - Storing application-related data
• Azure CosmosDB 
  - Storing authorization system data
• Azure Queue Storage 
  - Storing messages that are used for updating the authorization system
• Azure Blob Storage 
  - Used by Azure Functions, for storing terraform state files and table storage
• Azure Functions 
  - Hosting the custom authorization system and orchestrating the Pyspark application job executions
• Azure Active Directory, Microsoft identity platform 
  - Implementing single sign-on authentication
• Azure App Service 
  - Hosting the backend APIs
• Azure Container Registry 
  - Storing container images for deploying the backend APIs
• Application Insights, Log Analytics 
  - Monitoring the application