Integrate your favorite tools and critical workflows.

Foxglove webhooks provide real-time integration by delivering real time notifications with JSON payloads to your endpoint for subscribed events. 

Each webhook request includes a unique token for authentication and ensures at-least-once delivery, with automatic retries for failed attempts. For added security, notifications include a signed HMAC digest to verify integrity.

Designed with flexibility and scalability in mind, the Foxglove API allows you to programmatically interact with your data streams, manage devices, and customize layouts. Whether you’re building robotics systems, optimizing data analysis, or creating custom integrations, the Foxglove API offers in-depth support for seamless real-time data visualization and control.

An efficient way to visualize and debug your simulation environment. Automatically detect cameras, IMUs, and articulations. The Foxglove Isaac Sim extension dynamically updates to reflect scene changes and optimizes performance by querying sensors only when active.

Conduct interactive robotics data analysis using Jupyter Notebooks and Python libraries like python-mcap-ros1-support, ros2-support, and protobuf-support, you can effortlessly load and manipulate data from ROS 1, ROS 2, and Protobuf formats.

Paired with powerful tools like pandas, OpenCV, and Matplotlib, this integration enables advanced data transformations and exploratory analysis, delivering deeper insights.

Visualize Velodyne lidar data in real-time by directly connecting to the sensor. After establishing the connection, you can add a 3D panel to your layout, activate the /velodyne_points topic in the panel settings, and interactively explore the lidar scans in a 3D view. This streamlined setup simplifies calibration, troubleshooting, and data analysis, providing an efficient solution for working with lidar hardware.