Building for the Surge — What We Learned Architecting a System for 10,000+ Users at Once

Building for the Surge: Architecting for 10,000+ Users at Once When tickets for a big event go on sale, traffic doesn’t gradually increase. It spikes. All at once. Thousands of people hitting Buy Now in the same moment. That’s the scenario we had to design for when building EventStripe — a ticketing platform with one key constraint: The system had to stay responsive under 10,000+ concurrent users within the first minute. This wasn’t about long-term scalability or graceful degradation. It was about surviving the first 60 seconds. What we focused on We’ve worked on plenty of high-load platforms before, and we stick to a few architectural rules when the stakes are this high: Isolate traffic domains We split payments, seat reservations, and admin panels into separate services. No shared failures, independent scaling. Use queues and prioritize Payment spikes aren’t just traffic — they’re money. We used retry logic, backoff strategies, and metrics to keep the system graceful under pressure. Make monitoring a first-class citizen Grafana dashboards and ELK logs gave us zone-level visibility in real time. Saturation. Queue depth. Error rates. If it blinked — we saw it. Don’t fear launch-day deploys Jenkins pipelines with rollback and canary options gave us confidence. If something had to change mid-spike, we were ready. Simulate real chaos Load tests weren’t theoretical. We mimicked real user flows, used real API limits, and stress-tested until the system stopped blinking. Stack (if you’re curious) Java 20 + Spring (backend) Next.js (frontend) Docker + Kubernetes Jenkins, Grafana, ELK We ran tests simulating 9,000+ active users. The system held. No slowdowns. No unhandled spikes. Just tickets sold. It’s not a magic formula — just careful architecture and a lot of rehearsal. Have you built for traffic surges before? What helped your system survive? This project was designed and tested by our team at H‑Studio, where we focus on building resilient, high-load systems for SaaS and platforms.

Apr 23, 2025 - 12:18

Building for the Surge — What We Learned Architecting a System for 10,000+ Users at Once

Building for the Surge: Architecting for 10,000+ Users at Once

When tickets for a big event go on sale, traffic doesn’t gradually increase.

It spikes.

All at once. Thousands of people hitting Buy Now in the same moment.

That’s the scenario we had to design for when building EventStripe — a ticketing platform with one key constraint:

The system had to stay responsive under 10,000+ concurrent users within the first minute.

This wasn’t about long-term scalability or graceful degradation.

It was about surviving the first 60 seconds.

What we focused on

We’ve worked on plenty of high-load platforms before, and we stick to a few architectural rules when the stakes are this high:

Isolate traffic domains

We split payments, seat reservations, and admin panels into separate services. No shared failures, independent scaling.
Use queues and prioritize

Payment spikes aren’t just traffic — they’re money. We used retry logic, backoff strategies, and metrics to keep the system graceful under pressure.
Make monitoring a first-class citizen

Grafana dashboards and ELK logs gave us zone-level visibility in real time. Saturation. Queue depth. Error rates. If it blinked — we saw it.
Don’t fear launch-day deploys

Jenkins pipelines with rollback and canary options gave us confidence. If something had to change mid-spike, we were ready.
Simulate real chaos

Load tests weren’t theoretical. We mimicked real user flows, used real API limits, and stress-tested until the system stopped blinking.

Stack (if you’re curious)

Java 20 + Spring (backend)
Next.js (frontend)
Docker + Kubernetes
Jenkins, Grafana, ELK

We ran tests simulating 9,000+ active users.

The system held.

No slowdowns. No unhandled spikes. Just tickets sold.

It’s not a magic formula — just careful architecture and a lot of rehearsal.

Have you built for traffic surges before?

What helped your system survive?

This project was designed and tested by our team at H‑Studio, where we focus on building resilient, high-load systems for SaaS and platforms.