GreenEarthConnect – Sustainability Engagement Platform

Community sustainability hub: track environmental impact metrics, surface local initiatives, and drive collaborative eco‑actions.

Problem

Communities lacked a unified, data‑driven hub to aggregate local sustainability initiatives, quantify impact metrics (e.g. events hosted, trees planted), and surface collaboration opportunities. Existing tools were siloed, limiting momentum & transparency.

Solution Overview

• Modular GraphQL API with strict typing & validation for consistent client contracts.
• Impact aggregation layer generating snapshot metrics & trend data.
• Componentized React dashboard with lazy‑loaded feature zones for perceived speed.
• Containerized workflow for reliable dev/prod parity; CI enforcing lint & test gates.

Architecture Highlights

• API Layer: Apollo GraphQL (schema‑first, future subscriptions/websocket events prepared).
• Data Model: Users, Initiatives, Events, ImpactSnapshots (compound indexes for query hot paths).
• Dataloaders: Batching & caching to eliminate N+1 resolver overhead.
• Separation: Domain logic decoupled from transport; resolvers map to services.
• Deployment Path: Docker image → CI pipeline → (future) K8s/ECS scaling layer.

Security & Quality

• Schema validation & centralized error normalization for predictable client responses.
• ESLint + Prettier + TypeScript strict mode maintain code consistency & safety.
• Jest test scaffolding for resolvers & utility modules (coverage growth planned).
• Dependency scanning & minimal base image target (future hardening).

Performance & Optimization

• Indexed queries for initiative & event lookups (compound indexes reduce scan cost).
• Dataloader caching slashes duplicate DB round trips inside a single request.
• Lazy route/component splits minimize initial JS payload.
• Potential metrics (to record): median resolver latency, cache hit ratio, p95 response time.

Deployment & Operations

• Docker multi‑stage build trims image size & enforces deterministic layer caching.
• CI pipeline: install → lint → type check → tests → build; blocking on failures.
• Environment‑driven config (12‑factor alignment) for future cloud portability.
• Planned observability: structured logs + lightweight metrics (Prometheus / OpenTelemetry).

Timeline (Condensed)

• ProblemFragmented visibility into local environmental initiatives; no unified impact dashboard.
• DesignModular GraphQL API + typed schema + React dashboard for initiative browsing & impact aggregation.
• Data LayerMongoDB collections with compound indexes for initiative activity & time‑series snapshots.
• DeploymentContainerized (Docker) with CI lint/test gates enabling predictable dev/prod parity.
• OptimizationAdded dataloaders and targeted indexes to reduce N+1 and accelerate aggregate queries.