Defining Performance SLAs with k6 Thresholds
Learn how to use k6 Thresholds to define automated pass/fail criteria for your performance tests, ensuring your SLAs are met before code reaches production.
Loading…
ReadMeFeed / Community knowledge
#performance-testing
Real questions. Useful conversations. Find the people who know your stack.
k6Parameterizing Gatling Simulations with CSV Feeders
Learn how to use Gatling CSV Feeders to parameterize HTTP requests, avoid server-side caching, and choose between random, circular, and queue distribution strategies.
gatlingOpen vs. Closed Workload Models in Gatling: Picking the Injection Profile That Matches Reality
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.
How can I measure a specific bottleneck in Gatling before applying optimizations?
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
Global Timeout Configuration vs Per-Request Overrides for Latency Constraints
When designing performance tests in k6, managing request timeouts is essential to prevent hanging VU (Virtual User) iterations and to accurately measure service degradation. k6 provides two primary methods for controlling these durations: a global timeout property within the options object and granular overrides passed directly into individual http.request c
Gatling HTTP‑JMS Session Scope Interoperability: Can Shared Session Attributes Cross Protocol Boundaries?
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 HTML report limits in separating injector saturation from target latency
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
Gatling thread-pool saturation and latency spikes under concurrency
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
k6 Browser Module and HTTP Scenarios in One Run: Safe to Co-Locate VUs?
Goal I want a single k6 test run that exercises both layers of a web application: protocol-level HTTP scenarios driving backend load, and browser-module scenarios (Chromium via CDP) capturing frontend behavior, so one end-of-test summary contains both http_req_duration and the browser_web_vital_* metrics. Constraints and uncertainty The browser module runs e