ROS 2 connects the software components that sense, estimate, plan, decide, and command a robot. It also defines how those components discover one another, exchange data, handle incompatible timing assumptions, enter and leave service, and recover from faults. A graph can be functionally correct in a lab while still missing production requirements for startup order, bounded latency, resource contention, network isolation, observability, security, or field updates.

Recent peer-reviewed research reinforces the need to treat timing as a graph-level property. Teper et al. (2024) analyzed end-to-end timing across multi-executor ROS 2 systems, while Betz et al. (2025) showed that composition and deployment choices materially affect end-to-end latency in containerized ROS 2 software. The practical implication is direct: node-level benchmarks are useful, but the product must be profiled as a complete cause-and-effect chain on the target compute platform.

CTai LABS can establish that architecture before code is written or assess the graph a team already has. Starting early helps define message boundaries and acceptance criteria. Starting later can isolate queueing, copy, scheduling, driver, middleware, or resource-allocation problems without discarding working application logic.