Scaling ipify to 30 Billion Requests and Beyond on Heroku

Summary

ipify began as a free API that returns a caller’s public-facing IP address, created to help discover cloud instances’ external addresses without management APIs. Its initial implementation was a sub-50-Loc Node service deployed on one Heroku dyno for about $7/month; rising usage caused slow responses and 503s. Investigation showed roughly 10 rps, while one Node process and string manipulation around X-Forwarded-For limited throughput; clustering doubled capacity, and the implementation later used Go. Heroku supplied load balancing, automatic restarts, and horizontal dyno scaling as traffic expanded through bursty demand and malicious use; the operator chose manual capacity rather than paid autoscaling. The service surpassed 30B requests per month, routinely serving 2k–20k RPS with 1–20ms average response times at $150–$200 monthly; ownership later passed to whoisxmlapi.com, whose work includes an improved UI and more data endpoint.

Takeaways

1. 1

   A single Node process limited throughput, while using the Node cluster module to run one process per CPU core immediately doubled capacity on the Heroku dynos.

2. 2

   The service routinely handled 2k–20k requests per second and more than 30 billion requests per month, with average response times ranging from 1 to 20 milliseconds.

3. 3

   At a monthly cost of roughly $150–$200, ipify’s hosting cost was reported as $0.000000007 per request; the operator noted that serverless or functions-as-a-service deployment would cost thousands monthly.