Configure your experiment

  • Updated

This article will help you:

  • Create a deployment to house your experiment
  • Install the SDK you wish to use for your experiment

The first step in creating an experiment is to configure it. Configuring is a brief, two-step process: first you’ll create a deployment, then you’ll install the SDK you want to use.

Create a deployment

In Amplitude Experiment, a deployment is where you can serve a group of flags or experiments for code execution. Once you create a deployment, Experiment will generate an access key, which you can then use to properly route your flags and experiments.

Deployments live under Amplitude Analytics projects. A project can have multiple deployments, but each deployment can only be attached to a single project.

To create a deployment follow these steps:

  1. From inside Experiment, click Deployments in the left-hand rail. Then click + Add Deployment. 
  2. Choose the Amplitude Analytics project you’d like the deployment to be associated with. If you want to create deployments in multiple projects at once, just select all the relevant projects from the drop-down list.
  3. Next, choose a name for your deployment and specify its type:
          • Client-side: These deployments run on a client device, such as a web browser or mobile app. The deployment key associated with client deployments can be viewed publicly and should be used in client-side SDKs.
          • Server-side: These deployments run on a server you control, such as a web server or batch processing system. The deployment key associated with server deployments should be kept secret and are for use in server-side SDKs. Server-side keys can access the REST API for flag evaluation. If, instead of running a full-blown experiment, you only need to evaluate flags using the REST API, you should create a server-side deployment.
  1. Click Add Deployment. Amplitude Experiment will create your deployments and automatically generate keys to copy and use.

Install the SDK

If you’re not planning to use the REST API, the next step is to install the SDK. Each SDK has different installation instructions, which you can find in the Amplitude Developer Center's SDK Catalog.

All SDKs send a request to Amplitude Experiment to determine what flag configurations should be served to a particular user. That said, there are some important differences between client-side and server-side SDKs you should be aware of.

Client-side SDKs are meant to be run in the end-user application deployment. When choosing between client-side and server-side, keep in mind that client-side SDKs:

  • Assume a single user deployment
  • Use client-side deployment keys, which are public and visible to end users
  • Fetch variants up front for a given user
  • Store variants locally on the client for offline mode

Server-side SDKs, on the other hand, are meant to be run in a server deployment. Server-side SDKs:

  • Assume a multi user deployment
  • Use Server-side deployment keys, which should be kept private
  • Fetch variants on each request

The User context

When assigning variants, the evaluation engine applies the targeting rules to a user context object. This object represents the identity of an individual user. In client-side SDKs, this object-user relationship is set on initialization and passed to the server on every request for variants. In server-side SDKs, the user may change, and should be set on every request.

When targeting individual users to allocate variants, Experiment will match on any of the listed user IDs ( user_id ) or device IDs ( device_id ). Using rule-based user segments, users will match on any of the predefined properties (country, platform, etc.), or on custom properties specified in the user_properties object. Read more about defining experiment users in the Amplitude Developer Center.

NOTE: You should use the same user identifiers ( user_id and device_id ) for Amplitude Experiment that you use for sending data to Amplitude Analytics. This way, identities will be resolved correctly, and data generated will be correctly associated with the same user in Analytics.