Update an experiment. Updating an experiment uses the semantic patch format.
To make a semantic patch request, you must append domain-model=launchdarkly.semanticpatch to your Content-Type header. To learn more, read Updates using semantic patch.
Semantic patch requests support the following kind instructions for updating experiments.
Deprecated:
updateNamewill be removed in a future version. UseupdateExperimentFieldsinstead.
Updates the experiment name.
value: The new name.Here’s an example:
Deprecated:
updateDescriptionwill be removed in a future version. UseupdateExperimentFieldsinstead.
Updates the experiment description.
value: The new description.Here’s an example:
Updates one or more fields on an experiment or its current iteration. Each field update specifies an operation (add, update, or remove) and an optional value.
Which fields are mutable depends on the current iteration status. To discover which fields and operations are allowed, expand mutableFieldsByStatus on the Get experiment response.
value: An object mapping field names to field updates. Each field update has the following properties:
operation: The operation to perform. One of add, update, or remove.value: The new value for the field. Required for add and update operations.To find which fields are supported and which operations are allowed for each iteration status, expand mutableFieldsByStatus on the Get experiment response.
Here’s an example:
Stops the current running iteration, creates a new iteration from it, optionally applies field updates, and starts the new iteration. This is a convenience instruction that combines stopping, updating, and starting in a single operation.
changeJustification: (Optional) The reason for stopping and starting a new iteration.value: (Optional) An object mapping field names to field updates, using the same format as updateExperimentFields. These updates are applied to the new iteration before it is started.Here’s an example:
Starts a new iteration for this experiment. You must create a new iteration before calling this instruction.
An iteration may not be started until it meets the following criteria:
randomizationUnit is settreatments has a non-zero allocationPercentchangeJustification: The reason for starting a new iteration. Required when you call startIteration on an already running experiment, otherwise optional.Here’s an example:
Stops the current iteration for this experiment.
winningTreatmentId: The ID of the winning treatment. Treatment IDs are returned as part of the Get experiment response. They are the _id of each element in the treatments array.winningReason: The reason for the winnerHere’s an example:
Archives this experiment. Archived experiments are hidden by default in the LaunchDarkly user interface. You cannot start new iterations for archived experiments.
Here’s an example:
Restores an archived experiment. After restoring an experiment, you can start new iterations for it again.
Here’s an example:
The instructions to perform when updating. This should be an array with objects that look like <code>{“kind”: “update_action”}</code>. Some instructions also require a <code>value</code> field in the array element.