Parse Gatling simulation.log files to generate HTML reports with Plotly charts or CSV statistics.
Gatling Report is a Java-based tool that parses Gatling load testing simulation.log files and converts them into human-readable reports. It solves the problem of analyzing raw Gatling test data by providing both CSV statistical exports and interactive HTML reports with Plotly charts, making performance test results easier to interpret and share.
Performance engineers, QA automation specialists, and developers who use Gatling for load testing and need to analyze and visualize test results.
Developers choose Gatling Report because it provides specialized reporting capabilities beyond Gatling's built-in features, offering flexible output formats, visual charting with Plotly, and the ability to compare multiple test runs through differential and trend reports.
Parse Galting simulation.log files to output CSV stats or build HTML reports with Plotly charts.
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Exports detailed per-request metrics including percentiles (p50, p95, p99), success/error counts, Apdex scores, and request rates, as shown in the sample output table in the README.
Generates standalone HTML files with Plotly charts for easy visualization, enabling quick bottleneck identification and sharing, as demonstrated in the linked example reports.
Supports simulation, differential, and trend reports from single or multiple log files, allowing for analysis ranging from single tests to longitudinal comparisons.
Allows the use of custom Mustache templates to tailor report appearance and content, with default templates provided in src/main/resources for reference.
Officially tested only with Gatling versions up to 3.3.0, which may not support newer releases without updates, limiting compatibility with evolving Gatling ecosystems.
Requires a Java environment to execute the JAR file, adding overhead for teams not using Java in their stack or preferring lightweight, native tools.
Lacks built-in APIs or hooks for seamless automation in CI/CD pipelines, necessitating additional scripting for report generation and distribution.