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Frameworks & web · #gatling
Goal Investigate how Gatling 3.7.0’s in‑memory HTTP cache responds to Cache‑Control directives when the responses traverse a reverse proxy that rewrites or drops headers. Constraints The cache is per‑host, limited by a configurable size, and invalidation is triggered only via the clearCache method. Proxies can modify Cache‑Control , ETag , or add Age , poten
Gatling 3.x is not source-compatible with the 2.x simulation DSL, which turns a move between the two major versions into a manual migration rather than a drop-in upgrade. HTTP protocol setup, request chaining, and injection profiles written for 2.x do not compile unchanged under 3.x. Since simulations are compiled Scala classes that the runner loads from the
Scenario I have a Gatling simulation (3.x line) that wraps a write request in tryMax(3) so transient failures don't fail the whole scenario. The wrapped chain is a POST /orders with a status.is(201) check. The API under test is not idempotent and has no deduplication on its side. Problem When the first attempt succeeds on the server but the response is lost
MaxConnectionsPerHost in Gatling The maxConnectionsPerHost setting controls the number of concurrent TCP connections Gatling will open to a single target host. The default value of 20 is adequate for low‑concurrency local tests but can become a bottleneck in high‑traffic production simulations. Uncertainty in Production Tuning Gatling’s documentation does no
Netty vs. Java HttpClient: Balancing Concurrency and SSL Reliability in Gatling Deployments When a Gatling simulation fails to deploy, the execution logs are the primary source for diagnosing the root cause. A core decision is whether to use the Netty HTTP client, which offers higher concurrency but requires explicit SSL configuration, or the Java HttpClient
The objective is to verify whether a session attribute created by an HTTP request remains accessible when a subsequent JMS request is executed within the same Gatling scenario. Constraints include using only built‑in session handling, testing on Gatling 3.7 and 3.8 to capture the documented change in session scope, and avoiding external feeders or databases.
Gatling's asynchronous engine allows a single injector to sustain high request rates, yet the standard HTML report aggregates response-time percentiles and request counts without providing a definitive signal that distinguishes client-side queuing or resource exhaustion from genuine server-side latency. When an injector approaches its own limits—CPU saturati
When executing high-concurrency simulations in Gatling, latency spikes often appear that do not correlate with the target application's response time. This behavior is observed when the HighRes scenario executor reaches its bounded thread pool limit, causing virtual users to be queued before execution. The interaction between usersPerSec and the feeder mecha
This question examines the interoperability between Gatling 3.x's feeder mechanism and its injection profile system when simulation duration exceeds the cardinality of the data source. The goal is to determine whether feeder data is automatically cycled, reused, or terminated, and what guarantees exist for record uniqueness across virtual users. Gatling feed
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