> Markdown version of [/videos/337-covid-19-a-crowdsourced-map-for-checking-supermarket-wait-times-worldwide?t=1211](https://www.wearedevelopers.com/videos/337-covid-19-a-crowdsourced-map-for-checking-supermarket-wait-times-worldwide?t=1211). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

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# Covid-19 - A crowdsourced map for checking supermarket wait times worldwide

A viral Covid-19 map started on a single Raspberry Pi before scaling to millions of users. Discover the lean Redis architecture that kept peak monthly costs under $25.

- **Speakers:** Miki Lombardi
- **Event:** WeAreDevelopers LIVE
- **Published:** December 7, 2021
- **Duration:** 45:26
- **URL:** https://www.wearedevelopers.com/videos/337-covid-19-a-crowdsourced-map-for-checking-supermarket-wait-times-worldwide

## Summary

At the onset of the 2020 COVID-19 pandemic, unpredictable and unsafe supermarket queues prompted the creation of a crowdsourced web application to track wait times worldwide. To minimize global contagion risk and public frustration, the progressive web app leveraged real-time reporting to populate a live map displaying estimated line durations for local stores. Initially hosted on a single Raspberry Pi 3B using port forwarding for a local network of beta testers, the application rapidly validated the viability of simple, low-budget infrastructure solving immediate public crises.

As the application went viral—scaling from forty to over a thousand concurrent users and millions of sessions—the underlying architecture transitioned from a monolithic local setup to a distributed cloud model. The frontend was seamlessly migrated to Netlify using the JAMstack approach to ensure fast, static distribution. Simultaneously, the backend shifted across cost-effective OVH and DigitalOcean virtual private servers, virtually simulating a global CDN. This lean infrastructure kept peak operational costs to merely $25 per month, primarily because the API layer was optimized to transmit only minimal JSON data payloads, successfully avoiding expensive cloud bandwidth limits.

To ensure reliable real-time geospatial processing under heavy traffic, the backend utilized Python, Flask, and extensive multithreading. However, the true architectural breakthrough was the full integration of Redis. By utilizing Redis for robust caching layers and running lightweight native geospatial commands to filter locations by distance, the app sidestepped traditional relational database bottlenecks entirely. Ultimately, the project's success underscores the immense power of open-source collaboration, demonstrating how community-driven UI/UX and web accessibility contributions can rapidly scale a localized developer experiment into a globally adopted platform.

**Keywords:** crowdsourced queue tracking, raspberry pi local hosting, python flask multithreading, redis geospatial caching, progressive web app scaling, jamstack frontend deployment, low-budget VPS infrastructure, JSON payload optimization, open source web accessibility, API load balancing architecture, dynamic DNS configuration, high-traffic geolocation apps, virtual private server migration, multithreaded backend performance

## Chapters

1. **Managing grocery store wait times during global lockdowns** (02:36) — How sudden pandemic lockdowns created unmanageable lines and high infection risks at local supermarkets.
1. **Building a crowdsourced map for tracking wait times** (05:59) — Leveraging crowdsourced user feedback tracks and visualizes real-time local grocery store line durations.
1. **Hosting a full stack application on a Raspberry Pi** (11:28) — Utilizing a local hardware setup with port forwarding directly deploys the initial backend and cache layer.
1. **Migrating from local hardware to virtual private servers** (13:32) — Moving backend operations to a cloud environment effectively handles increased traffic volume beyond hardware capabilities.
1. **Architecting caching layers for high concurrent user traffic** (17:12) — Implementing a robust API rotation and caching mechanism ensures system availability without requiring expensive load balancers.
1. **Managing geospatial queries and analytical endpoints with Redis** (20:11) — Processing mapped coordinates and executing geospatial filtering helps users discover less crowded alternative destinations.
1. **Analyzing cloud hosting costs and bandwidth telemetry limitations** (27:07) — Optimizing API data constraints keeps external server operational expenses minimal despite servicing millions of routine requests.
1. **Launching open source projects and integrating accessibility updates** (31:40) — Collaborating with external contributors introduces substantial user interface improvements alongside comprehensive web accessibility standards.
1. **Exploring traffic correlations and alternative technical caching architectures** (34:47) — Evaluating adoption usage patterns reveals structural infrastructure revisions that could demonstrably improve data delivery workflows.
1. **Achieving viral traction and unexpected professional networking outcomes** (39:55) — Capitalizing on immediate consumer necessities translates organic engagement metrics into substantive career networking and recruitment scenarios.

## Related Moments

- [Managing high-traffic infrastructure without chasing technology hype](https://www.wearedevelopers.com/videos/1817-how-to-avoid-tech-hype-traps-josip-stuhli) (from "How to Avoid Tech Hype Traps - Josip Stuhli")
- [Deploying a progressive web app during crisis response](https://www.wearedevelopers.com/videos/45-progressive-web-apps-the-next-big-thing) (from "Progressive Web Apps - The next big thing")
- [Building serverless REST and GraphQL APIs for COVID-19 data](https://www.wearedevelopers.com/videos/208-40-minutes-to-build-a-serverless-covid-19-rest-and-graphql-apis) (from "40 Minutes to Build a Serverless COVID-19 REST and GraphQL APIs")
- [Overcoming network unreliability in grocery store picking applications](https://www.wearedevelopers.com/videos/747-challenges-for-omnichannel-applications-at-aldi-data-distribution-and-offline-capabilities) (from "Challenges for omnichannel applications at ALDI: Data distribution and offline capabilities")
- [Managing server costs and application clones after viral growth](https://www.wearedevelopers.com/videos/1237-creating-games-to-make-the-web-fun-again) (from "Creating games to make the web fun again")
- [Community engagement, open-source resources, and audience Q&A discussions](https://www.wearedevelopers.com/videos/797-cloud-as-the-new-mainframe-why-the-cloud-hype-does-not-reflect-the-dev-reality) (from "Cloud as the new mainframe: why the cloud hype does not reflect the dev reality")

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