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Experiments & testing overview

As a DecisionOps platform, Nextmv provides first-class support for different types of testing that can be done on decision models. Generally speaking, these can be categorized into two types:

  • offline: experiments that run on stored data, which does not involve the production system.
  • online: experiments that run on live data, which involves the production system.

Please find a brief overview of the different types of experiments below. For more information, go to each of the individual sections.

Name Type Description
Batch experiments offline Analyze the output from one or more decision models on a fixed input set.
Scenario tests offline Compare the output from one or more scenarios.
Acceptance tests offline Verify that a decision model meets the acceptance criteria.
Shadow tests online Run a decision model in parallel with the production model to compare results.
Switchback tests online Evaluate the impact of changes by switching between different versions of a decision model.

Data for experiments can generally be provided by two mechanisms:

  • Input sets: a collection of input data. Consists of one or more inputs, where an input can be obtained from a run or a managed input.
  • Managed inputs: data that can be uploaded directly to Nextmv.