01 · CAPABILITY
Trigger tests from automation
Use API tokens so pipelines can start a known test definition without requiring an engineer to click through the UI.
CI/CD LOAD TESTING
Make performance a release check, not a post-release surprise.
Trigger repeatable load tests from your delivery pipeline, fail on agreed thresholds, compare releases, and keep larger performance runs on a schedule. Use automation where it gives fast signal without turning every build into a long benchmark.
FREE TO START · No credit card · HTTP performance testing · Managed execution
TEST DESIGN
A performance gate belongs in the same path as the code change
01Commit
Choose the scenario tied to the changed path.
02Run
Compare against a stable baseline with explicit thresholds.
03Gate
Fail only on a signal the team is prepared to act on.
WHY THIS PAGE EXISTS
Catch performance regressions close to the code change.
A CI/CD load test should be small enough to run often, deterministic enough to compare, and strict enough to stop a release when an important performance budget is broken. The pipeline does not need to reproduce peak production traffic on every commit. It needs to catch meaningful regressions early and escalate to deeper tests when risk is higher.
02 · CAPABILITY
Turn thresholds into gates
Set p95 latency and error-rate criteria so the pipeline has an objective pass/fail signal instead of relying on manual graph review.
03 · CAPABILITY
Keep scenarios repeatable
Use the same endpoints, payloads, traffic shape, and environment for regression checks so result changes are attributable to the release.
04 · CAPABILITY
Separate fast gates from deep tests
Run lightweight performance smoke tests in the main pipeline and schedule heavier capacity or soak-style validation outside the critical path.
05 · CAPABILITY
Compare against a baseline
A release can remain under an absolute threshold and still become meaningfully slower. Run comparison helps expose drift before it compounds.
06 · CAPABILITY
Send results where the team works
Use alerts, webhooks, exports, and result links so failures reach the release workflow instead of remaining isolated in a testing dashboard.
WORKFLOW
Put the smallest useful performance check at the right delivery stage.
Pipeline performance checks should sacrifice breadth for repeatability. Hold the environment, dataset, scenario, warm-up, and thresholds steady so a failed gate points back to the code change instead of the test harness.
01
Create one stable scenario
Start with a small, high-value API or HTTP flow. Remove unnecessary randomness and make its data setup predictable.
02
Choose a short traffic profile
Use enough traffic to reveal a regression without overwhelming a shared test environment. Keep duration appropriate for frequent execution.
03
Define the release budget
Set thresholds before integrating the test. Decide whether a breach blocks the build, creates a warning, or triggers a deeper test.
04
Call the test from CI/CD
Store the API token as a protected secret, trigger the run, and surface the resulting status in the pipeline.
05
Add deeper scheduled validation
Use scheduled runs or pre-release jobs for larger workloads. Keep these connected to the same baseline and review process.
PRODUCT FIT
Automation without maintaining load workers in your pipeline
The CI system should orchestrate the check, not become the load generator. LoadTester keeps distributed execution outside your build agents while the pipeline owns the trigger and pass/fail decision.
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IMPLEMENTATION GUIDE
Need the CI/CD implementation pattern?
Read the CI/CD load testing guide for pipeline scope, thresholds, environment choices, and rollout strategy.
Open the supporting guide →OTHER SOLUTIONS
Connect each release gate to the smallest useful performance scenario.
FAQ
CI/CD performance questions worth resolving before automation.
Should every CI build run a full load test?
Usually no. Frequent pipelines benefit from short, stable performance smoke tests. Larger capacity tests are better suited to scheduled runs, release candidates, or infrastructure changes.
What should fail a performance pipeline?
Use explicit thresholds such as p95 latency and error rate, and consider a regression limit versus a trusted baseline. Keep the rules stable enough that developers trust the signal.
Where should the load generator run?
A managed load service keeps traffic generation outside CI build agents. The pipeline can trigger the run and consume its status without provisioning and coordinating worker infrastructure.
How do I avoid flaky performance gates?
Control the environment, test data, scenario, and traffic model. Use a workload that is large enough to reveal regressions but not so large that unrelated environment noise dominates the result.
Put the performance signal close enough to the commit that someone can still fix it.
Begin with one high-signal scenario in the pipeline. Add heavier stages or scheduled runs only after the team trusts the fast gate.