Virtual queues and waiting rooms
Admission control that meters arriving demand to a rate the platform can serve, instead of letting the entire crowd hit checkout simultaneously.
Available for contract, freelance and full-time engagements
High-Traffic & High-Concurrency Engineering
Traffic spikes break systems in two distinct ways, and fixing one does not fix the other. The infrastructure falls over, and concurrent users race each other for the same finite resource. I have built for both: The Ticket Central handles peak on-sale traffic with virtual queues, counters and waiting-room flows, deployed behind an ALB with Auto Scaling and stress-tested to 100,000 concurrent users.
What this covers
Race condition and contention handling
Concurrent claims on the same finite inventory resolved to exactly one holder — the difference between a sold-out event and an oversold one.
Caching and hot-path design
Redis for queue state, counters and rate limiting, keeping the coordination layer off the primary database.
Load testing and capacity
Stress testing the real path — to 100,000 concurrent users on The Ticket Central — so auto-scaling policy is set against measurements, not assumptions.
Tools and technologies
RedisAWS EC2ALBAuto ScalingBullMQPostgreSQLNest.jsNode.js
Proof of work
Projects where I have already done this, written up as case studies.
The Ticket Central
High-scale event ticketing platform stress-tested to 100,000 concurrent users.
Read case study: The Ticket CentralVistana
Browser-based screen recording and instant video sharing, built end to end.
Read case study: VistanaQuestions
How many concurrent users have you built for?
The Ticket Central was stress-tested to 100,000 concurrent users, running on EC2 behind an Application Load Balancer with Auto Scaling Groups.
Our booking system oversells under load. Can that be fixed?
Yes — that is a booking race condition, and it is solvable. It is one of the specific problems I solved on The Ticket Central, alongside queue fairness and peak-traffic overload.
What is a virtual queue and do we need one?
A virtual queue admits users to the live system at a controlled rate and holds the rest in a waiting room. You need one when demand arrives faster than you can serve it — event on-sales, launches, limited releases — because scaling infrastructure alone does not solve fairness or contention.
Can you work with an existing platform rather than rebuilding it?
Usually yes. Queueing, caching and admission control are layers you can add in front of a working system; a full rebuild is rarely the right first move.
Other services
LET'S TALK SPECIFICS
If high-traffic platform engineering is what you need, tell me about the system, the constraints and the timeline.