Public Health · Performance Engineering
WHO Disease Analytics & Visualization Platform
We built a high-performance analytics platform for a WHO initiative that generates thousands of disease-trend charts server-side — engineering a virtual-DOM SVG rendering pipeline that cut report generation from weeks of manual effort to about 30 minutes.
Client: World Health Organization Initiative·Healthcare / Public Health Analytics
Weeks → 30 min
report generation time
1000s
of SVG charts server-side
60%
lower infrastructure cost
Azure
serverless at scale
The Challenge
Thousands of charts, without a browser in sight
A World Health Organization initiative needed to receive webhook events, pull disease statistics from MySQL, generate year-wise visualizations, and surface everything through monitoring dashboards. The core engineering problem was brutal: generating thousands of SVG graphs on the backend using Node.js.
Traditional chart libraries depend on a full browser engine like Chromium via Puppeteer. At this scale, that meant excessive CPU and memory usage, painfully slow execution, and instability under heavy workloads — the kind of fragility you can't afford in a public-health reporting system.
Generating disease-trend visualizations at massive scale.
Objectives
What success looked like
Automate end-to-end report generation
Generate scalable SVG charts entirely on the backend
Reduce infrastructure cost
Improve reliability and deployment scalability
Provide operational dashboards for engineering teams
Technical Innovation
A virtual-DOM SVG pipeline that skips the browser entirely
Instead of rendering charts inside a real browser, we implemented a lightweight virtual-DOM approach in Node.js that generates SVG elements directly. This eliminated all browser overhead while keeping rendering quality perfectly consistent.
The result was dramatic: a process that had taken months of manual effort and unstable automation now completes bulk generation in roughly 30 minutes — reliably, at scale, and at a fraction of the infrastructure cost.
Server-side SVG rendering via a virtual DOM — no headless browser required.
Architecture
The end-to-end pipeline
Role & Contributions
What we engineered
Designed the backend workflow in Node.js
Integrated webhook-based event processing
Built API integration with MySQL datasets
Created the server-side SVG rendering pipeline
Optimized memory and CPU utilization
Built a React operational dashboard for logs & maintenance
Deployed on Azure with serverless services and WebJobs
Insights delivered in minutes, not months
Decision-makers get reliable disease-trend visualizations fast, while engineers monitor everything from one dashboard.
Impact
Performance engineering that changed the game
Weeks → 30 min
bulk report generation
1000s
of charts rendered reliably
60%
lower infrastructure consumption
24/7
stable backend rendering at scale
Capabilities
Capability to client value
Fast, browser-free chart generation
Lower cost and higher reliability
Scalable background processing
Operational visibility and monitoring
Reliable data pipelines from MySQL
Technology
Built with
Removing unnecessary runtime dependencies produced a bigger win than any amount of scaling — reports that once took weeks now take minutes.
Engineering Lead · WHO Analytics Initiative
Want results like this for your business?
Start Your ProjectThis case study describes the engineering approach and outcomes at a high level, without disclosing sensitive data or proprietary implementation details.