Case Study
Sisu Saviya Initiative
A mission-critical humanitarian platform connecting donors with disaster victims in real-time during Sri Lanka's most challenging moments.
The Challenge
Understanding the Problem
Our Approach
The Solution
Optimized ISR (Incremental Static Regeneration) and service-worker based PWA caching. The app loads in under 2 seconds even on 2G networks and works fully offline.
- 50K+ Families Reached
- <2s Load Time
- 100% Crisis Uptime
The Outcome
Successfully coordinated relief efforts reaching 50,000+ affected families. The platform maintained 100% uptime during the 2023 flood crisis when traditional systems failed.
Impact: 50K+ Families Helped
Technical Deep Dive
Engineering Excellence
A comprehensive look at the technical architecture and implementation details that power this solution.
features
Real-time resource mapping with GPS integration, intelligent donor-recipient matching algorithm, automated SMS alerts via Twilio for non-smartphone users.
scalability
Serverless lambda functions architected to handle 100k+ concurrent users. Auto-scaling infrastructure with zero cold-start latency.
System Architecture
PWA Client
Next.js + Service Worker
CloudFlare CDN
Edge Caching
Serverless API
AWS Lambda Functions
SMS Gateway
Twilio Integration
DynamoDB
NoSQL Database
Development Journey
From Concept to Launch
Crisis Analysis
Conducted field interviews with relief workers and disaster victims to map workflow bottlenecks, identified critical 2G network constraints, and established core requirements for offline-first architecture.
Offline-First Architecture
Implemented Progressive Web App with aggressive service worker caching strategies, configured Incremental Static Regeneration for dynamic donor data, and built fallback mechanisms for zero-connectivity scenarios.
Real-time Features
Integrated Mapbox for GPS-based resource mapping, developed intelligent donor-recipient matching algorithm using geospatial indexing, and connected Twilio API for SMS alerts to feature phones.
Load Testing
Simulated 100K concurrent users with k6 load testing framework, optimized serverless lambda cold starts to <100ms, and fine-tuned auto-scaling policies for crisis traffic spikes.
Deployment & Training
Executed phased rollout starting with pilot district, conducted comprehensive volunteer training sessions, and created multi-language documentation for field workers.
Measurable Impact
Key Results
Direct business value delivered.
Impact Analysis
Page Load Time
Before
10s
After
1.8s
Crisis Uptime
Before
85%
After
100%
Network Tolerance
Before
3G+
After
2G/Edge
Technology Stack
Tools & Frameworks
Implementation
Service Worker Caching Strategy
Aggressive caching with network fallback for 2G reliability.
1self.addEventListener('fetch', (event) => {2 event.respondWith(3 caches.match(event.request).then((cached) => {4 // Return cached response immediately5 if (cached) return cached;6 7 // Fetch from network with timeout8 return fetch(event.request, {9 signal: AbortSignal.timeout(5000)10 })11 .then((response) => {12 // Cache successful responses13 if (response.ok) {14 const clone = response.clone();15 caches.open('v1').then((cache) => {16 cache.put(event.request, clone);17 });18 }19 return response;20 })21 .catch(() => {22 // Return offline fallback23 return caches.match('/offline.html');24 });25 })26 );27});Performance
Performance Audits
"This platform saved lives. When everything else failed, Sisu Saviya kept working."
