The new Foxglove bridge connection dramatically improves streaming performance, provides custom message and publishing support, and offers reliable live connections to your ROS 1 and ROS 2 stacks. Install the foxglove\_bridge ROS package to start connecting live to your robots in Foxglove Studio.

The next generation of live ROS debugging

With foxglove\_bridge, Foxglove Studio users now have a stable, performant, and out-of-the-box solution for connecting live to their ROS 1 and ROS 2 systems. Foxglove bridge is a ROS node implemented in C++ for high performance and low overhead, and is designed to minimize impact when running on your robot or developer workbench.

With this new bridge, there’s no need to make tradeoffs. It maintains the low overhead and high performance of native connections, while supporting ROS 2 custom messages like Rosbridge connections. Connecting to your robot from outside the ROS stack also becomes easier than ever, as the Foxglove bridge reduces the networking complexity between Studio and your robot.

Since we've learned that Rosbridge can struggle with streaming high-frequency topics and large messages like images and point clouds – both from Foxglove Studio users and our own testing – we designed Foxglove bridge to tackle these performances issues and to provide a dramatically streamlined experience for Studio users debugging their robot.

Rosbridge vs. Foxglove Bridge performance
Streaming Intel RealSense images (1280x720 raw rgb8 images) from a NVIDIA Jetson TX2 robot. We found that Rosbridge was unable to keep up with reading, serializing, and sending all streamed data, dropping \~36% of messages.

Once you’ve installed and added the foxglove\_bridge node to your ROS stack, open Foxglove Studio to open a Foxglove WebSocket connection:

Foxglove Studio welcome dialog

You should now see your live robotics data loading in your Studio layout! Add new panels to start exploring your data.

Stay tuned

Robotics teams shouldn’t have to jump through hoops to view their live data. With the foxglove\_bridge, we hope Foxglove Studio users can more reliably connect to their systems – regardless of framework or data format – and spend more of their precious development time taking full advantage of our visualization and debugging features.

To learn more about our new foxglove\_bridge, check out the Foxglove Studio data connection docs and the package’s GitHub repo.

As always, join our Slack community to ask questions, or reach out to us directly with any feedback.


With self-managed sites, you can now host data in your own cloud infrastructure, while leveraging the full capabilities of Foxglove Data Platform.

When storing your robotics data, you often want to control the regions you use, where you deploy storage, and how people access your network. By using your own cloud account, you can exercise complete control over the security and isolation of your data.

Using Foxglove with your own cloud account

Foxglove Data Platform helps you explore data more efficiently by streamlining critical development workflows – you can retrieve your data at lightning speed, annotate it with events of interest, and stream it directly to Foxglove Studio for instant visualization.

With self-managed sites, you benefit from Foxglove’s rich data exploration and visualization capabilities while keeping data in your own cloud account. Whether you’re using Amazon Web Services, Azure, Google Cloud Platform, or your own private cloud on-premises, managing your own cloud infrastructure gives you more fine-grained control over how your data is secured and accessed.

Self-managed sites minimize network latency by colocating your robotics data with your company's other resources. By deploying in secure networks (e.g. behind a VPN), self-managed sites can help you restrict access to your sensitive robotics data and comply with company and regulatory data control requirements.

Deploy today

With self-managed sites, your organization has ultimate control over how you store data, while Foxglove does the heavy lifting. To learn more, check out our docs or ask questions in our Slack community.

If you're interested in adding a self-managed site to your Foxglove organization, sign up for a Foxglove Enterprise plan and contact our team to get started.


With Foxglove Studio v1.40, you can now customize your plots with the Plot panel’s new and improved settings interface. In addition to offering more configuration options, the new Plot interface consolidates all settings in the app sidebar for a streamlined interface and intuitive user experience.

What’s changed

The panel settings interface now contains all the controls you need to customize your Plot panel in one place:

As with the old Plot panel, you can use these settings to adjust your legend position, select your data
series paths, and customize plot colors:

Setting legend position and colors

We’ve also added the long-awaited feature of naming your plots, to better differentiate them from others in your layout:

Setting title

You can also give each data series a human-readable name, to better understand your data at-a-glance:

Naming data series

All these improvements have been made with one goal in mind – to empower Foxglove Studio users to better interpret and analyze their data.

Keep in touch

With this new and improved panel, we hope to make it easier than ever for Foxglove Studio users to build the tools they need to understand their robots. With these redesigned settings and streamlined plotting interface, we hope you can spend more of your development time leveraging our features and diving deeper into your data.

To learn more about our new Plot panel, check out the Foxglove Studio docs. As always, feel free to join our Slack community to ask questions or give us feedback.


Announcing Foxglove Studio’s Improved Plot Settings Interface

What’s changed

Keep in touch

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