Cyclops
An integrated, full-stack application designed for the remote analysis and tracking of forest health. The platform empowers forest custodians to validate carbon sequestration efforts, which is essential for the carbon credit market.
Technologies Used
Project Description
Cyclops is a comprehensive, cloud-native platform built to address the critical need for reliable and remote monitoring of forest ecosystems. The primary objective is to provide forest custodians with a powerful tool to prove their forests are healthy and sequestering carbon effectively, a key requirement for participating in the carbon credit economy.
The system employs a sophisticated microservices architecture, ensuring scalability and maintainability. The architecture consists of three main components:
- A dynamic React frontend offers a rich, interactive user experience. Its core feature is a Mapbox-powered interface that allows users to draw custom regions of interest and visualize complex geospatial data through charts and reports.
- A robust NestJS backend API serves as the central hub for the application. It handles user management, authentication (JWT-based), data orchestration, and manages a Redis-based background job queue for asynchronous tasks.
- A high-performance FastAPI Data API, written in Python, is dedicated to the heavy lifting of climate data processing. It fetches data from multiple satellite sources (Landsat and Sentinel-2), processes it to calculate metrics like Above-Ground Biomass (AGB) and deforestation, and caches the results for rapid retrieval.
The entire platform is deployed on AWS and managed using an Infrastructure as Code (IaC) approach with Terraform. The development workflow is fully automated with a CircleCI pipeline for continuous integration and deployment, and the system's health is constantly monitored using Datadog and Sentry.
Key Achievements
- Scalable Microservices Architecture: Successfully designed and implemented a distributed system with distinct frontend, backend, and data processing services, ensuring separation of concerns and enhanced scalability.
- Advanced Geospatial Data Processing: Developed a sophisticated data pipeline integrating multiple satellite sources (Landsat, Sentinel-2) to perform complex analyses of Above-Ground Biomass (AGB) and deforestation.
- Interactive Map-Based UI: Created a highly interactive and intuitive user interface using Mapbox GL JS, enabling users to define custom analysis regions by drawing directly on a map and visualizing results through dynamic charts.
- Comprehensive DevOps Automation: Established a robust, fully automated CI/CD workflow with CircleCI and managed the entire cloud infrastructure declaratively using Terraform, from networking to service deployment.
- Real-Time User Notifications: Integrated a WebSocket gateway to provide users with real-time notifications and private messaging, significantly improving user experience and engagement.
- Full-Stack Observability: Implemented a comprehensive monitoring suite using Datadog for infrastructure health and performance (APM) and Sentry for real-time error tracing across all application layers.
- High-Load Resiliency: Engineered the Data API with an asynchronous, semaphore-based request queue to gracefully manage high traffic and prevent system overloads during intensive processing tasks.
- Quality-Driven Development: Enforced a rigorous testing strategy encompassing unit, integration, end-to-end, and load testing, complemented by extensive documentation (API specs, component libraries, and architecture diagrams) to ensure code quality and maintainability.
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