Operationalizing Models: ModelOp Runtime as REST

This article describes how to prepare the ModelOp Runtime and the MLC Process to deploy a model.

Table of Contents

 

 

Operationalize a Model in a ModelOp Runtime - ONLINE Deployment

The following are the steps to deploy a model as REST via ModelOp Center:

Pre-Requisites:

Prior to any model deployment, the following steps should be conducted by the Enterprise AI Architect and ModelOps team.

  1. Runtime Environments/Stages. Define the Runtime Environments/Stages required for operationalizing models for a given team and/or class of models. For example, if this team requires a model to be deployed and tested in Development, then SIT, then UAT, before being promoted to Production.

  2. Operationalization MLC. The Enterprise AI Architect and/or ModelOps Engineer will create the model life cycles (MLC’s) required for operationalization models for that team and/or class of models. This operationalization MLC will take into account the technical and governance requirements as a model is operationalized, which may include running tests, obtaining approvals, promoting the model to the next higher Runtime Environment (e.g. from Dev to QA).

Note, each Business Unit / Team may have different requirements and therefore these steps may be updated or repeated as the overall program progresses.

 

Steps:

Prepare Runtimes.

  1. Identify the target Runtimes across the requisite Environments. For each target Runtime, complete the following:

    1. Add Runtime Endpoints. If any runtimes will be used to provide an online model, add the required Endpoints.

      1. To add an endpoint, follow these instructions: Adding Endpoints to a ModelOp Runtime

      2. For runtimes that will be used for Batch runs of the model, do not put endpoints on the model.

    2. Add “Environment/Stage Tags”. Based on the environments/stages required (see pre-requisites), add the necessary “environment/stage tag” to the runtime.

      1. Example: add a “DEV” tag to the Runtime in their development environment, an “SIT” tag to the Runtime in their SIT environment, a “UAT” tag to the Runtime in their UAT environment, and ultimately a “PROD” tag to the Runtime in their Prod environment

    3. Add “Model Service Tags”. The Model “Service” tag will be used to identify that this specific runtime is designed to be a target runtime for that particular model. Add the appropriate “Model Service Tag” to the runtime.

      1. Example: add a “cc-fraud” Model Service Tag to the runtime for a 3rd party credit card model to the “Dev”, “SIT”, “UAT”, and “Prod” runtimes.

 

Create a Snapshot of the model.

 

Related Articles

Next Article: Operationalize a Model - Batch >