How docker swarm helped us with a deployment of a precise and trusted localisation stack to the Network Rail New Measurement Train presented at the Edinburgh Docker Meetup 6th birthday bash.
8. Challenges
• very limited physical access
• semi-air gapped system
• multi architecture – x86_64 + aarch64
• R&D deployment where things will change often!
9. Docker & Swarm gives us …
• simple/vanilla local install of OS + docker-ce
• managed as a single resource
• converges to the defined / versioned configuration
• run local registry service for container images
• sneaker-net updates via my laptop’s image cache and a new
docker-compose.yaml
10. Rough Edges
• docker support in L4T kernel is fragile
• NVIDIA L4T seems to break overlay networks
• some ROS nodes will need to run CUDA code …
11. Geoff Ballinger / Head of Platform
Thanks for listening!
(We are hiring for CUDA developers now, software
engineers soon, and many other technical roles
over the next year!)
Editor's Notes
Joined at the start of the year
Precise and trusted location of vehicles
Long interested in IOT – this is the Internet Of very big Things
The big picture
Founder Anthony fell into the canal …
Trains, cars, and factory/warehouse robots …
This presentation focused on Network Rail New Measurement Train
This is real data ...
Lots more vanilla use of containers on the cloud side later
physical access every two weeks
train WIFI style access when powered up
intel in the train, arm in the sensor
complexity is in the containers
declarative deployment
powerup or other disruption
registry local and visible to all swarm members
L4T is derived from Ubuntu 16.04 (/ 18.04)
Carrier board specific mods have been known to break docker support
Access to CUDA/GPGPU driver from inside the container – or run it in a container?