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Frameworks & web · #gatling
Learn how Gatling feeders inject dynamic test data from CSV, JSON, JDBC, Redis or custom sources, with a concrete example, setup steps, and key limitations to watch.
Learn how to use Gatling CSV Feeders to parameterize HTTP requests, avoid server-side caching, and choose between random, circular, and queue distribution strategies.
Gatling's open and closed injection models measure different things. Learn how coordinated omission can flatter your latency numbers, and how to pick the right profile for checkout-style APIs versus capacity-bound internal services.
Consider a simple Gatling simulation that sends HTTP GET requests to a service endpoint, wrapped in a group named "api-call". Before making any changes to the backend, I want to know whether the latency observed for this group represents a bottleneck that warrants optimization. Which Gatling metric should I collect to isolate the bottleneck? How can I config