## Deployment Considerations
When integrating ROS 2 into DACA, consider the following:
- **Real-Time Performance**: ROS 2’s DDS ensures low-latency communication, but Dapr and Kubernetes may introduce overhead. Use lightweight Kubernetes distributions (e.g., K3s) and optimize Dapr’s networking for edge deployments.
- **Networking**: Configure Kubernetes to support ROS 2’s DDS multicast (e.g., via host networking) and Dapr’s mDNS for service discovery.
- **Resource Constraints**: Robots often have limited CPU/memory. Optimize Docker images (e.g., use multi-stage builds) and leverage Dapr’s actor model for efficient resource usage.
- **Simulation-to-Production**: Use ROS 2’s Gazebo for local testing, then deploy the same containers to production with Kubernetes, ensuring consistency.
- **Observability**: Combine ROS 2’s debugging tools (e.g., rqt, rviz) with Dapr’s OpenTelemetry for end-to-end monitoring of agent performance.