Seldon

Links

• Seldon https://www.seldon.io/

• GitHub SeldonIO/seldon-core

• Doc https://docs.seldon.io/projects/seldon-core/en/latest/

• Installation

  • Install Seldon Core: https://docs.seldon.io/projects/seldon-core/en/latest/workflow/github-readme.html#install-seldon-core

  • SeldonIO/seldon-core

  • Videos: https://docs.seldon.io/projects/seldon-core/en/latest/tutorials/videos.html

Install

• Use k8s 1.17.0: minikube start -p aged --kubernetes-version=v1.17.0

  • current version line 1.18.x does not work (at the moment)

  • when you want to start k8s again you have to provide this command again - with version number

  • maybe delete all k8s before: minikube delete --all - maybe with --purge

• follow this guide to install istio: SeldonIO/seldon-core

  • let’s use version 1.5 like the guide sais

  • %%curl -L https://istio.io/downloadIstio | ISTIO_VERSION=1.5.0 TARGET_ARCH=x86_64 sh - %%

  • add export PATH="$PATH:/home/mike/bin/istio-1.5.0/bin" to .bashrc

  • istioctl manifest apply --set profile=demo

• install the rest

  • checkout seldon-core from git: SeldonIO/seldon-core

  • change to directory examples/auth

  • follow the rest of the guide: SeldonIO/seldon-core

  • Uninstall: helm uninstall seldon-core --namespace seldon-system

Using and Testing with Python

• Usage with Python: https://docs.seldon.io/projects/seldon-core/en/v1.1.0/python/index.html

  • Seldon Core Python Package: https://docs.seldon.io/projects/seldon-core/en/v1.1.0/python/python_module.html

  • Seldon Python Component: https://docs.seldon.io/projects/seldon-core/en/v1.1.0/python/python_component.html

  • Seldon Python Client: https://docs.seldon.io/projects/seldon-core/en/v1.1.0/python/seldon_client.html

  • Python API: https://docs.seldon.io/projects/seldon-core/en/v1.1.0/python/api/modules.html

  • Class name and script name have to be exactly the same!

• Testing - without Kubernetis - just localy

  • start API to test

    • export PREDICTIVE_UNIT_PARAMETERS='[{"name":"model_uri","value":"<uri>","type":"STRING"}]'

    • example: export PREDICTIVE_UNIT_PARAMETERS='[{"name":"model_uri","value":"file:///home/myuser/models/german_sentiment_electra","type":"STRING"}]'

  • get model from cloud storage: model_file = os.path.join(seldon_core.Storage.download(self.model_uri))

  • seldon-core-microservice <script_name_without_.py> REST

  • curl -X POST -H 'Content-Type: application/json' -d '{"data": { "ndarray": ["data1", "data2"]}}' http://127.0.0.1:5000/api/v1.0/predictions

• see here: https://docs.seldon.io/projects/seldon-core/en/v0.3.0/workflow/api-testing.html

  • Alternatively, if your component is a Python module you can run it directly from python using the core tool seldon-core-microservice” […]

• Testing Your Model Endpoints: https://docs.seldon.io/projects/seldon-core/en/v1.1.0/workflow/serving.html