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Tracer integrates with WDL (Workflow Description Language) pipelines executed through engines like Cromwell or miniWDL. It automatically traces all WDL tasks as they run, giving per-task performance data and cross-node visibility without modifying workflow definitions.

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Why use Tracer in combination with WDL

While WDL focuses on portability and reproducibility, it lacks system-level telemetry. Tracer adds observability that helps teams debug and optimize large WDL workflows:
  • Step-level execution graphs for each WDL task
  • Real-time metrics for CPU, memory, I/O, and storage
  • Correlated logs and system traces even if task logs are minimal
  • Cost and resource attribution by sample, node, or step
  • Works locally, in HPC, or in cloud environments (AWS, GCP, Azure)

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Getting Started

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Prerequisites

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Just run your pipeline, Tracer will automatically attach

If Tracer is already installed on your operating system, you only need to enable the Tracer agent for pipelines that have not been run with Tracer before.
In that case, run the following command: 
sudo tracer init --token <your-token>
Go to our onboarding to get your own personal token
When running this command, you will be asked to name your pipeline for clear labeling in the dashboard.

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Examples

Launch the Tracer demo workflow: 
sudo tracer demo
Or run your WDL pipeline as usual. Once the pipeline starts, open the Tracer dashboard, and you’ll see each WDL task as a timeline step updating in real time.

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Watch your pipeline run in the Tracer dashboard
View real-time metrics, resource usage, and performance insights for your pipeline runs.