Get prepared for Black Friday with a load testing methodology that actually works

Gateway timeouts, fraud-service slowdown, connection exhaustion, duplicate orders after a retry. Retry after a timed-out call still produces exactly one order, every time.

Hot rows, lock contention, connection storms, replica lag under simultaneous reads and writes. Holds at production-like cardinality, not a 10% staging dataset.

Cold cache, mass TTL expiry, hot-SKU stampede, origin unable to survive a cache miss.
Origin stays under safe QPS when the cache goes cold mid-sale.

Scale-out reacts too slowly for the first wave; stateful tiers can't scale at all.
Warm-up before launch, not scale-out triggered by launch.

Load testing validates system behavior under expected peak traffic, stress testing pushes beyond expected limits to find breaking points, soak testing runs sustained load for hours to catch degradation over time, and spike testing simulates sudden traffic surges from campaigns or viral products.

No, Black Friday testing focuses on revenue-critical journeys like search, add to cart, checkout, and payment authorization rather than just homepage load, because these flows directly affect whether customers can complete purchases during high traffic.

Gatling executes scripts but cannot validate whether SKUs are published, stock levels are realistic, or pricing rules match production behavior—outdated or generic test data causes false failures that waste time during critical preparation periods.

Performance testing works best as part of regular development cycles rather than one week before the event, because late testing turns every finding into an urgent fix with no time to validate improvements or retest after changes.