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  • Introduction
  • Contributing
  • Versions
  • v1.x.x
    • 🚀 Getting Started
      • 🛠️ Installation
      • 📂 Project Structure
    • Pipeless REST API
    • Stream Formats and Protocols
    • Inference Runtimes
    • Key Value Store
    • 🐋 Container images
    • Deploying your application
    • Ready to Use CV Models
      • Tensorflow
        • Multi-pose estimation Tensorflow Model
    • Export and monitor stream events
    • 🌟 Examples
      • Adding wattermarks
      • Passing data between hooks and stages
      • Detecting Cats on a Video
      • Pose detection with TensorFlow
      • Object detection - YOLOv8 Python lib
      • ONXX Runtime - Candy filter
      • ONNX Runtime - Object detection with YOLO
      • Play a piano with your eyes by looking to the notes
      • Object tracking - YOLO and Norfair
    • Benchmark
    • Version Notable Changes
    • Troubleshooting
    • Processing Restart Policy
  • v0.x.x
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v1.x.x
Export and monitor stream events

Exporting events and monitoring

In order to export events and monitor what is happening on your Pipeless streams you can configure a Redis publisher connection.

The following env vars are required:

  • PIPELESS_REDIS_URL: URL of the remote Redis instance where to push the events.
  • PIPELESS_REDIS_CHANNEL: Name of the Redis channel where Pipeless should send the events.

Then, start pipeless with the flag --export-events-redis:

pipeless start --project-dir /my-project --export-redis-events
Multi-pose estimation Tensorflow Model🌟 Examples

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