How We Used Edge Computing to Reduce Latency- PAR-Technologies

 

How We Used Edge Computing to Reduce Latency

We first noticed the issue in a familiar way. Every evening, when traffic peaked, users started reporting that the app felt slow. It wasn’t crashing, but it wasn’t smooth either. And for users, even for me, if an app is slow, it’s a deal-breaker.

But before opting for the costly fix and adding more servers, we wanted to understand why the lag is occurring. We broke down the request path: DNS, TLS, trips to the origin, and the personalization endpoints. That’s where we found the problem; there were too many round-trip calls to the origin, doing the same work again and again.

Any solution? Yes.

The solution was to bring some of that work closer to the user. We shifted smaller, predictable tasks, such as authentication checks, cookie-based personalization, and pre-rendered snippets, closer to edge functions. This meant less travel time and quicker responses.

Caching also became our BFF, but we had to rethink how we implemented it. We kept dynamic content fresh using short TTLs, while ensuring users didn’t have to wait. Even small backend routines, like geolocation redirects, worked well at the edge.

What didn’t we touch?

We didn’t move everything. Real-time features, such as video sync, stayed in regional zones where they performed best. Not shifting certain features was as crucial as deciding what to shift.

And it showed loud and clear: the complaints got fewer over the week, peak hours got much smoother, and there was noticeably better response times. 

Learned some lessons!

Edge computing isn’t about big promises. But it is about carefully moving the right tasks closer to the user. If done well with a proper strategy, it quietly makes the experience faster.
Location: New Delhi, Delhi, India

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