performance-testing-workflow

Automating an end-to-end performance testing pipeline involves orchestrating BlazeMeter, Datadog, PerfAnalysis, PerfReport, and Confluence workflows sequentially. You supply a BlazeMeter run_id and environment to retrieve test results, collect metrics, analyze data, and generate reports automatically.

Yes, you can execute individual sub-workflows standalone. The pipeline supports running specific steps like retrieving BlazeMeter results or collecting Datadog metrics independently, rather than forcing the entire end-to-end performance testing sequence every time.

Publishing performance test results to Confluence is handled as an optional final step in the pipeline. After PerfReport generates the report from analyzed metrics, the workflow manages artifact publication directly to Confluence pages.

The performance analysis workflow explicitly handles cross-workflow data flow, step sequencing, and prerequisites validation. It includes defined inputs, outputs, and error handling policies to ensure data artifacts pass correctly between BlazeMeter, Datadog, and reporting steps.

You need an end-to-end performance testing workflow when you want to coordinate retrieving test results, collecting metrics, analyzing data, generating reports, and publishing results across Confluence without manually triggering each sub-workflow step.

To start the BlazeMeter performance testing workflow, you need to supply a BlazeMeter run_id and the target environment. These inputs allow the pipeline to retrieve the correct test results and initiate the sequential metric collection and analysis stages.