Scaling to 10,000+ Concurrent Users on AWS: Infrastructure Decisions

Travel traffic is spiky. A long weekend can 10× your load in hours. Here is the infrastructure that let BookTravel absorb those spikes without breaking a sweat.

Cache first, compute second

Redis sits in front of search and inventory. Most peak-season searches are for the same popular routes, so a short-TTL cache absorbs the majority of read traffic before it ever hits a provider.

Decouple with queues

• Celery workers handle notifications, emails, and post-booking tasks asynchronously.
• Auto-scaling groups add capacity based on queue depth and CPU.
• Read replicas take pressure off the primary database during spikes.

Takeaways

The right architecture is the one that lets your team move quickly today and still scales tomorrow. We optimize for clarity, measurable performance, and a codebase your team can own.

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