Deployment view

The Peltarion deployment solution provides the means to quickly test out model prototypes all the way directly in your services.
It also provides the stability and scalability you need for a system that will be deployed for longer periods of time with a reliable model for server-to-server integration.

Create deployment

Click New deployment to create a new deployment.

New deployment button

Select if you want to create a Standard or Similarity search deployment.

Standard deployment

Standard deployments are used when you’re working with classification and regression models.

Select the Experiment and Checkpoint you want to deploy.

Similarity search deployment

Select Similarity search if you’re working with an image or text similarity search model. Select:

  • Experiment

  • Checkpoint

  • Output feature

  • Output block

Enable deployment for requests

Click Enable to enable a deployed model.

Enable button

A deployed model will be accessible through the Peltarion Deployment API for forward pass queries. You can request one or several predictions at a time, within the API limitations.

The Deployment view allows you to quickly see which models are deployed and when they were deployed. A green checkmark Check mark indicates that the experiment is deployed and the date is shown in the Deployment info section.

In turn, click Disable to disable a deployed model. The deployed model will not respond with predictions while the deployment is disabled.

A deployment can be enabled and disabled several times, and can be deleted when it’s not relevant anymore. Note that you have to disable the deployment before you can delete it.


The parameter section gives a list of all the input and output features used by the deployed model.

When you submit a request to the deployed model, you have to send all the input features. The response will contain the predicted output feature for each submitted example.

The Name field refers to the name you want to use for a feature when exchanging data via the API. You can update it to something convenient to you before enabling the deployment for the first time. To change it after the deployment has been enabled once, you will need to duplicate the deployment to change it.

API information

The API is called by sending an HTTP POST to the endpoint indicated by the URL in the interface. The request body needs to be multipart-form encoded or json.

  • The URL is the API endpoint where you submit samples.

  • The Token is required to allow the deployment to respond with predictions.
    Since the token is considered a secret, the deployment system is not meant to be shipped in the client-code (like javascript widgets, Android apps and so on).

Using your deployment

Peltarion test app

As soon as your deployment is enabled, you can start requesting predictions. You can try a deployment easily by using one of our web apps for submitting

Deployment API

You can also use the deployment API to integrate your deployment in your program. If you are unfamiliar with REST APIs, checkout our Python package Sidekick, which makes it easy work with deployed models.

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