Difficulty: Easy
Estimated Time: 20 minutes

Introduction 👩‍💻

In this scenario, you will deploy Seldon Core to a Kubernetes environment.

You will then use Seldon Core to deploy and test a machine learning classifier- pre-trained on the Scikit-Learn Iris dataset.

Pre-requisites ☁

An understanding of Kubernetes terminology and concepts will be helpful!

What is Seldon Core? 🤖

Seldon Core is an open source platform to deploy your machine learning models at scale on Kubernetes.

Seldon Core makes it simple to convert machine learning models into production-grade microservices following three steps:

  1. Containerise: Model binaries from popular frameworks (Scikit-Learn, Tensorflow, XGBoost) are readily containerised thanks to pre-built model servers. Custom models are supported using language wrappers (Python, Java) allowing you to take any model in these languages and containerise them.
  2. Deploy: Seldon Core extends Kubernetes by adding the custom SeldonDeployment resource. Seldon deployments support a range of complex inference patterns, such as canary rollouts and multi-armed bandits. Seldon deployments are built out of a number of core components e.g. Transformers, Predictors, Explainers, Routers, etc.
  3. Monitor: Logging can easily be configured to support tracing of network traffic to deployments, monitoring of request/response payloads, visualisation of real time model health. Alerting for outlier detection and concept drift can be setup.

✍️ Tutorial authored by Tom Farrand. Source here.

Congratulations on making it this far!

You can now bask in your achievements after all that hardwork. 😌

Hopefully this has given you a taste of the potential of Seldon. You can learn so much more here.

If you have any feedback then please submit an issue here!

Deploying Seldon Core

Step 1 of 5

Installing Helm ⛴

It's time to get your hands dirty! 🧑‍🔧

Prior to installing Seldon you will install Helm. Helm is a Kubernetes package manager which makes it dead easy to install other Kubernetes software with- including Seldon. 📦

Helm is straightforward to install. You will first grab the install script: curl -fsSL -o get_helm.sh https://raw.githubusercontent.com/helm/helm/master/scripts/get-helm-3

Changing the permissions, to allow the script to be executed: chmod 700 get_helm.sh

Running the installer: ./get_helm.sh

If you are successful, you will see the following message: helm installed into /usr/local/bin/helm