Rosbag2

ROS 2 is an open-source robotics middleware (the successor to ROS/Robot Operating System) developed by Open Robotics and the ROS community that provides publish/subscribe topics, services, actions, parameters and lifecycle management for distributed robot software. It uses the DDS (Data Distribution Service) transport layer with implementations such as eProsima Fast DDS, Eclipse Cyclone DDS and RTI Connext, and includes client libraries (rclcpp, rclpy), tooling (colcon) and rosbag2 for logging and replay of topics. ROS 2 runs on Linux, Windows and macOS, integrates with simulators and robot stacks, and is distributed under the Apache 2.0 license.

Dalaran is an Apache-2.0 robotics-focused observability and visualization stack for recording, replaying, and inspecting multimodal time-series data such as ROS 2 topics, LiDAR sweeps, camera streams, IMU readings, and TF transforms on a synchronized timeline. It is a hard fork of Rerun, uses an Arrow-backed columnar chunk store, renders synchronized 2D and 3D views, and exposes recorded data as dataframes for computation. The project supports Python, Rust, and C++ SDKs, a viewer and CLI, ROS 2 data, Rosbag 2 and MCAP replay, existing Rerun .rrd recordings, and Dalaran .dlr recording files with saved .dbl blueprints; recordings can be written to files or streamed to a viewer or remote catalog.

Rerun is an open-source SDK and data layer for recording, querying, visualizing, transforming, and streaming multimodal physical-robotics data. It ingests multi-rate data such as images, point clouds, transforms, time series, joint states, tensors, and video from robot logs, human-data rigs, simulation, and web video, using formats including MCAP, RRD, and LeRobot. Its built-in viewer synchronizes and renders the data in real time for episode scrubbing, sensor comparison, and live computer-vision pipelines; the same data can be queried with dataframes or SQL and streamed directly into training. Rerun is built in Rust on column-chunk storage designed for multi-rate physical data, with Python, Rust, and C++ SDKs and a separate Viewer binary for network streaming and RRD files. The repository describes the project as being in active development, with an evolving API and possible breaking changes.

Project Rosetta Stone is a workshop and comparison repository for instrumenting the same AI agent with different agent frameworks and observability platforms. Its Wonder Toys application is a chat-to-purchase toy-store assistant with semantic vector search, product browsing, purchasing, order tracking, and cancellation; framework variants are provided without observability, with Arize Phoenix instrumentation, and with Arize AX instrumentation. Readers can compare the instrumentation footprint by diffing each framework's baseline and instrumented directories, then run the applications locally to send traces to Phoenix or AX. The repository also includes shared synthetic requests, evaluation harnesses, voice testing for the OpenAI voice tier, product data, and instructions for adding frameworks and running the end-to-end workflows; it is licensed under MIT.