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Load Testing Blog

Sharing variables between Virtual Users

Summary

Sharing dynamic values across Virtual Users is often required in realistic load-testing scenarios. AMQP provides a simple and reliable way to exchange data between scripts by pushing values into a queue and retrieving them later. The tutorial demonstrates how one Virtual User can publish generated IDs to RabbitMQ, while another consumes them on demand.

CloudAMQP is used as the example broker, but the method works with any AMQP-compatible system. OctoPerf integrates easily with these HTTP endpoints, allowing both insertion and retrieval of queued values. Combined with JSON extractors, this approach makes cross-VU coordination straightforward and scalable.

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OctoPerf Spira Integration tutorial

Summary

This guide shows** how to connect Spira and OctoPerf to streamline load-testing workflows**. The integration lets teams launch OctoPerf scenarios directly from Spira test cases and automatically receive results back in Spira. Setup involves enabling the OctoPerf app, configuring server credentials, and adding custom properties to Spira test cases.

Running a test from Spira triggers an OctoPerf execution using the referenced scenario ID. A webhook combined with OctoPerf notifications pushes the final test results into Spira for centralized reporting. The process improves collaboration by keeping performance test execution and results within the same toolset used for QA management.

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How to load test OpenID/OAUTH

Summary

Load-testing applications using OpenID Connect requires simulating real authentication flows and validating token handling under stress. The guide walks through the OIDC “code” flow, explaining tokens, JWT internals, and the roles of the application, user, and identity provider. A full JMeter scripting workflow is detailed—from recording traffic to extracting dynamic values like state, nonce, session codes and authorization codes.

The process includes generating tokens, decoding them, managing headers, and preparing for token refresh logic. Keycloak is used as a reference example, but the same approach applies to any OIDC-based system. Guidance is provided on load modeling, login frequency, token expiration, and designing realistic test policies.

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JMeter JMesPath Extractor

Summary

JMESPath offers a powerful and predictable way to extract and validate JSON data in JMeter, complementing JSONPath. It provides cleaner syntax, richer filtering options, and a fully specified grammar, making it reliable across platforms.

The article shows how JMESPath extractors and assertions work in JMeter, including variable handling, match modes, and real examples. Octoperf also integrates JMESPath with an expression builder that simplifies selector creation and testing.

Advanced features like projections, pipes, multiselect, and functions allow complex JSON transformations. Although it lacks recursive traversal and arithmetic operations, JMESPath covers most extraction needs for performance testing scripts.

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Playwright vs JMeter

Summary

Playwright brings real-browser load testing to OctoPerf SaaS & On-Premise versions, offering client-side realism that protocol testing alone cannot capture. Browser-based VUs execute actual user interactions and handle dynamic parameters automatically, reducing scripting effort. Protocol-based VUs remain far more efficient, generating heavy loads at minimal resource cost while providing deep server-side insights.

A side-by-side campaign shows Playwright offers richer realism but consumes dramatically more CPU and delivers slower journeys. The most effective approach is hybrid: protocol VUs for load, Playwright VUs for end-user experience under stress. This balance keeps costs and resource usage under control while still exposing client-side performance issues.

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