ADVICE AI4EU Solution Experiment

ADVICE: AI-baseD predictiVe road maIntenanCE

Deployment Cheatsheet

Once the pipeline has been built on the AI4EU platform and exported to local:

0. Install docker and kubectl

1. Install minikube and start it:

      minikube start
   

2. Deactivate de Firewall to mount host's folder on the minikube virtual machine:

      ip r g $(minikube ip)|awk '{print $3}'|head -n1|xargs sudo ufw allow in on
      sudo ufw reload
   

3. Mount folder:

      minikube mount -v 5 <path-to>/advice-platform-pipeline/shared_folder:/tmp/hostpath-provisioner/test/pipeline
   

4. In other terminal, create namespace:

      kubectl create namespace test
   

5. Unzip solution.zip file

6. Run script (note IP address and port of the orchestrator):

      cd <path-to-unzipped-solution-folder>
      python3 kubernetes-client-script.py -n test
   

7. Wait until images are successfully pulled. For that purpose, run the following command:

      kubectl -n test get pod,svc -o wide
   

8. Run orchestrator script to start the pipeline, using the IP and port noted before:

     python3 orchestrator_client/orchestrator_client.py -e 192.168.49.2:30004 -b .
   

(Note: For deployment on local machine by source code please visit the "local" branch)

Acknowledgement

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Supported by AI4EU - A European AI On Demand Platform and Ecosystem.
More information: ai4europe.eu

This project has received funding from the European Union's Horizon 2020
research and innovation programme under grant agreement 825619.

Help

• Rafael Luque - [email protected]
• Adrian Rodriguez - [email protected]
• Other community or team contact