We've taken the complexity out of load testing – even the novice tester can know the real performance limits of their software
Use Load Impact 3.0 if you need to run very large tests where there are more than 5000 Virtual Users (VUs). Run tests with up to 100,000 VUs. Expecting a major event-- Black Friday is approaching. Load Impact 3.0 ensures that your system will handle the extra load.
Load Impact 3.0 offers an easy-to-use Graphical User Interface (GUI) for creating, configuring and running load tests. Manage everything in the Load Impact 3.0 application.
$ pip install loadimpact-cli $ loadimpact test run
TEST_RUN_ID: 123456789 Initializing test ... TIMESTAMP: VUs : reqs/s : bandwidth : user load time : failure rate : 2018-04-20 17:32:23+00:00 1.0 1.65880228503 444675.79207 - - 2018-04-20 17:33:00+00:00 2.0 1.65655724996 444309.858371 - - 2018-04-20 17:33:03+00:00 2.0 1.65174480411 442789.175918 150.41 - 2018-04-20 17:33:36+00:00 2.0 3.31532339156 889063.643269 150.595 - 2018-04-20 17:34:03+00:00 2.0 1.65779745031 444464.780093 124.19 - 2018-04-20 17:34:06+00:00 3.0 1.65459748111 443768.339145 119.52 - ...
API load testing from simple API hammering to complex API user scenarios.
Enhanced performance leads to greater customer satisfaction, better conversion rates and more revenue. Determine the scalability of your website or app with just one click - no programming required.
A solution for the modern engineering team that wants to performance regression test as part of their test automation pipeline.
Collect all the essential performance metrics for your test runs: response times, throughput, availability and utilization metrics.
Maybe one of your important performance KPIs is not included out-of-the-box. Use custom metrics to track whatever you want. Track finer grained network metrics like latency/time-to-first-byte, TCP connection time and TLS handshake time.
Configure your tests with metric thresholds to get a pass or fail for every test run. This is an essential step for performance testing automation.
Plot individual metrics (general, URL, pages, custom or server metrics) or add them to the main chart for easier correlation.
Create a custom metric in your script to collect the result data you need.
local r = http.get("http://test.loadimpact.com/") result.custom_metric("latency", r.time_to_first_byte)
Set thresholds based on the custom metric (see last point) in your test config and plot the metric on the result page.
Add thresholds to you test configuration.
See the test pass/fail status on the test result page.
Record an HTTP session using our proxy recorder or our Chrome Extension and let the simulated users perform the same actions during the test.
Configure your load tests to run in the middle of the night or once per week - you don't have to be around at all! You can also include Load Impact as part of your Continuous delivery process with the use of our Jenkins, Circle CI and TeamCity plugins, as well as our open API.
Make your tests data-driven. Simulate real users by including several sources of parameterized data in your scenario scripts. Simply upload CSV files containing the data you wish to use - such as login credentials, product IDs, URLs, etc. - and associate it with the desired script.
Plot a single, high-level performance metric collected over multiple test runs to locate patterns of performance degradation or improvement, and more easily validate the performance impact of code and infrastructure changes over time. Make sure your service is delivering on time.