Evaluation Rules

Get an evaluation rule

GET /evaluationrules/{id}

Retrieves the specified evaluation rule and its configuration.

Query parameters

api-version string required

The API version to use for this operation.

Path parameters

id string required

Unique identifier for the evaluation rule.

Responses

The request has succeeded.

Body

Content-Type: application/json

id string required

Unique identifier for the evaluation rule.

displayName string

Display Name for the evaluation rule.

description string

Description for the evaluation rule.

action continuousEvaluation | traceEvaluation | datasetEvaluation | humanEvaluationPreview required

Evaluation action model.

One of the following:

continuousEvaluation ContinuousEvaluationRuleAction

Evaluation rule action for continuous evaluation.

type enum required

continuousEvaluation

evalId string required

Eval Id to add continuous evaluation runs to.

maxHourlyRuns integer

Maximum number of evaluation runs allowed per hour.

samplingRate number

Percentage (0-100] chance that a matching event triggers an evaluation. When omitted, the service-default is to evaluate every event, which is equivalent to setting a sampling rate of 100.

traceEvaluation TraceEvaluationRuleAction

Configures a scheduled evaluation of observed agent traces.

type enum required

traceEvaluation

evalId string required

Identifier of the evaluation used to score the selected traces.

source TracesEvalRunDataSource | TraceSourceEvalRunDataSource | TracesPreviewEvalRunDataSource | TraceSourcePreviewEvalRunDataSource required

Existing trace-evaluation inputs supported by scheduled rules.

Any of the following:

type enum required

The type of data source, always azure_ai_traces.

azure_ai_traces

trace_ids string[]

Collection of Agent trace identifiers that should be evaluated.

conversation_ids string[]

Collection of conversation identifiers to filter traces by conversation.

agent_id string

The agent ID used to filter traces for evaluation.

agent_name string

The agent name used to filter traces for evaluation.

lookback_hours integer

Lookback window (in hours) applied when retrieving traces from Application Insights. For scheduled evaluations this is inferred from the recurrence interval.

end_time integer

max_traces integer

Sampling limit applied to traces retrieved for evaluation.

ingestion_delay_seconds integer

The delay to apply for ingestion when querying traces.

type enum required

The type of data source, always azure_ai_trace_data_source.

azure_ai_trace_data_source

trace_source trace_id_source | conversation_id_source | agent_filter

Base class for polymorphic trace sources nested within a TraceSourceEvalRunDataSource.

One of the following:

trace_id_source TraceIdTraceSource

A trace source that selects traces by explicit trace IDs.

type enum required

The type of trace source, always trace_id_source.

trace_id_source

trace_ids string[] required

Collection of trace identifiers to evaluate.

conversation_id_source ConversationIdTraceSource

A trace source that selects traces by conversation IDs.

type enum required

The type of trace source, always conversation_id_source.

conversation_id_source

conversation_ids string[] required

Collection of conversation identifiers to filter traces by.

agent_filter AgentFilterTraceSource

A trace source that selects traces by agent reference with time-based filtering.

type enum required

The type of trace source, always agent_filter.

agent_filter

agent_id string

The identifier of the agent to filter traces by.

agent_name string

The name of the agent to filter traces by.

agent_version string

The version of the agent to filter traces by.

start_time integer

end_time integer

max_traces integer

Maximum number of traces to sample. Must be greater than 0.

filter_strategy string | enum

Specifies the type of filter strategy used to select traces for evaluation.

Any of the following:

string

enum

random_samplingsmart_filtering

type enum required

The type of data source, always azure_ai_traces_preview.

azure_ai_traces_preview

trace_ids string[]

Collection of Agent trace identifiers that should be evaluated.

conversation_ids string[]

Collection of conversation identifiers to filter traces by conversation.

agent_id string

The agent ID used to filter traces for evaluation.

agent_name string

The agent name used to filter traces for evaluation.

lookback_hours integer

Lookback window (in hours) applied when retrieving traces from Application Insights. For scheduled evaluations this is inferred from the recurrence interval.

end_time integer

max_traces integer

Sampling limit applied to traces retrieved for evaluation.

ingestion_delay_seconds integer

The delay to apply for ingestion when querying traces.

type enum required

The type of data source, always azure_ai_trace_data_source_preview.

azure_ai_trace_data_source_preview

trace_source trace_id_source | conversation_id_source | agent_filter

Base class for polymorphic trace sources nested within a TraceSourceEvalRunDataSource.

One of the following:

trace_id_source TraceIdTraceSource

A trace source that selects traces by explicit trace IDs.

type enum required

The type of trace source, always trace_id_source.

trace_id_source

trace_ids string[] required

Collection of trace identifiers to evaluate.

conversation_id_source ConversationIdTraceSource

A trace source that selects traces by conversation IDs.

type enum required

The type of trace source, always conversation_id_source.

conversation_id_source

conversation_ids string[] required

Collection of conversation identifiers to filter traces by.

agent_filter AgentFilterTraceSource

A trace source that selects traces by agent reference with time-based filtering.

type enum required

The type of trace source, always agent_filter.

agent_filter

agent_id string

The identifier of the agent to filter traces by.

agent_name string

The name of the agent to filter traces by.

agent_version string

The version of the agent to filter traces by.

start_time integer

end_time integer

max_traces integer

Maximum number of traces to sample. Must be greater than 0.

filter_strategy string | enum

Specifies the type of filter strategy used to select traces for evaluation.

Any of the following:

string

enum

random_samplingsmart_filtering

evaluation_level enum | string

The level at which evaluation is performed.

Any of the following:

enum

turnconversation

string

datasetEvaluation DatasetEvaluationRuleAction

Configures a scheduled evaluation of dataset inputs.

type enum required

datasetEvaluation

evalId string required

Identifier of the evaluation used to score the dataset.

Dataset inputs supported by scheduled rules. Targets are configured within the selected source.

Any of the following:

type enum required

The type of data source. Always jsonl.

jsonl

source OpenAI.EvalJsonlFileContentSource | OpenAI.EvalJsonlFileIdSource required

Determines what populates the item namespace in the data source.

One of the following:

type enum required

The type of jsonl source. Always file_content.

file_content

content OpenAI.EvalJsonlFileContentSourceContent[] required

The content of the jsonl file.

type enum required

The type of jsonl source. Always file_id.

file_id

id string required

The identifier of the file.

type enum required

The type of data source, always csv.

csv

source EvalCsvFileIdSource required

Represents a reference to an uploaded CSV file used as a source for evaluation data.

type enum required

The type of source, always file_id.

file_id

id string required

The identifier of the uploaded CSV file.

type enum required

The type of run data source. Always completions.

completions

input_messages OpenAI.CreateEvalCompletionsRunDataSourceInputMessagesTemplate | OpenAI.CreateEvalCompletionsRunDataSourceInputMessagesItemReference

Used when sampling from a model. Dictates the structure of the messages passed into the model. Can either be a reference to a prebuilt trajectory (ie, item.input_trajectory), or a template with variable references to the item namespace.

One of the following:

type enum required

template

template (OpenAI.EasyInputMessage | OpenAI.EvalItem)[] required

type enum required

item_reference

item_reference string required

sampling_params OpenAI.CreateEvalCompletionsRunDataSourceSamplingParams

reasoning_effort string | enum | null

Constrains effort on reasoning for reasoning models. Currently supported values are none, minimal, low, medium, high, xhigh, and max. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response. Not all reasoning models support every value. See the reasoning guide for model-specific support.

Any of the following:

string

enum

noneminimallowmediumhighxhighmax

temperature number

max_completion_tokens integer

top_p number

seed integer

response_format OpenAI.ResponseFormatText | OpenAI.ResponseFormatJsonSchema | OpenAI.ResponseFormatJsonObject

One of the following:

type enum required

The type of response format being defined. Always text.

text

type enum required

The type of response format being defined. Always json_schema.

json_schema

json_schema OpenAI.ResponseFormatJsonSchemaJsonSchema required

description string

name string required

schema OpenAI.ResponseFormatJsonSchemaSchema

The schema for the response format, described as a JSON Schema object. Learn how to build JSON schemas here.

strict boolean | null

type enum required

The type of response format being defined. Always json_object.

json_object

tools OpenAI.ChatCompletionTool[]

model string

The name of the model to use for generating completions (e.g. "o3-mini").

source OpenAI.EvalJsonlFileContentSource | OpenAI.EvalJsonlFileIdSource | OpenAI.EvalStoredCompletionsSource required

Determines what populates the item namespace in this run's data source.

One of the following:

type enum required

The type of jsonl source. Always file_content.

file_content

content OpenAI.EvalJsonlFileContentSourceContent[] required

The content of the jsonl file.

type enum required

The type of jsonl source. Always file_id.

file_id

id string required

The identifier of the file.

type enum required

The type of source. Always stored_completions.

stored_completions

metadata OpenAI.Metadata | null

Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard. Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

[key: string] string

model string | null

created_after integer | null

created_before integer | null

limit integer | null

type enum required

The type of data source, always azure_ai_target_completions.

azure_ai_target_completions

input_messages OpenAI.CreateEvalCompletionsRunDataSourceInputMessagesItemReference

type enum required

item_reference

item_reference string required

source OpenAI.EvalJsonlFileContentSource | OpenAI.EvalJsonlFileIdSource required

The source configuration for inline or file data.

Any of the following:

type enum required

The type of jsonl source. Always file_content.

file_content

content OpenAI.EvalJsonlFileContentSourceContent[] required

The content of the jsonl file.

type enum required

The type of jsonl source. Always file_id.

file_id

id string required

The identifier of the file.

target azure_ai_model | azure_ai_agent required

Base class for targets with discriminator support.

One of the following:

azure_ai_model AzureAIModelTarget

A target that identifies an Azure AI model. See evaluate administrator-connected models.

type enum required

The type of target, always azure_ai_model.

azure_ai_model

model string

The name of the model deployment to invoke as the evaluation target.

sampling_params ModelSamplingParams

Represents a set of parameters used to control the sampling behavior of a language model during text generation.

temperature number

The temperature parameter for sampling. Defaults to 1.0.

top_p number

The top-p parameter for nucleus sampling. Defaults to 1.0.

seed integer

The random seed for reproducibility. Defaults to 42.

max_completion_tokens integer

The maximum number of tokens allowed in the completion.

azure_ai_agent AzureAIAgentTarget

A target that identifies an Azure AI agent. See evaluate model or agent targets.

type enum required

The type of target, always azure_ai_agent.

azure_ai_agent

name string required

The name of the Azure AI agent to invoke as the evaluation target.

version string

The version of the Azure AI agent. When omitted, the latest version is used.

tool_descriptions ToolDescription[]

Optional descriptions of tools available to the agent.

tools OpenAI.Tool[]

Tool definitions made available when invoking the agent.

Configures how the service prepares input items for an evaluation run before applying testing criteria. Depending on type, preparation can generate new inputs, retrieve existing responses, transform source data, or simulate conversations. Each type selects a workflow-specific model with the parameters required by that preparation workflow. These parameters do not define the evaluated target or the testing criteria.

One of the following:

red_team RedTeamItemGenerationParams

Represents the parameters for red team item generation.

type enum required

The type of item generation parameters.

red_team

attack_strategies AttackStrategy[] required

The collection of attack strategies to be used.

num_turns integer required

The number of turns allowed in the game.

red_team_seed_prompts RedTeamSeedPromptsItemGenerationParams

Represents the parameters for red team seed prompts item generation.

type enum required

The type of item generation parameters, always red_team_seed_prompts.

red_team_seed_prompts

attack_strategies AttackStrategy[] required

The collection of attack strategies to be used.

num_turns integer required

The number of turns allowed in the game.

source OpenAI.EvalJsonlFileContentSource required

type enum required

The type of jsonl source. Always file_content.

file_content

content OpenAI.EvalJsonlFileContentSourceContent[] required

The content of the jsonl file.

red_team_taxonomy RedTeamTaxonomyItemGenerationParams

Represents the parameters for red team taxonomy item generation.

type enum required

The type of item generation parameters, always red_team_taxonomy.

red_team_taxonomy

attack_strategies AttackStrategy[] required

The collection of attack strategies to be used.

num_turns integer required

The number of turns allowed in the game.

source OpenAI.EvalJsonlFileContentSource required

type enum required

The type of jsonl source. Always file_content.

file_content

content OpenAI.EvalJsonlFileContentSourceContent[] required

The content of the jsonl file.

response_retrieval ResponseRetrievalItemGenerationParams

Parameters for retrieving deployed conversations for evaluation. See evaluate deployed conversations.

type enum required

The type of item generation parameters, always response_retrieval.

response_retrieval

max_num_turns integer required

The maximum number of turns of chat history to evaluate.

data_mapping object required

Maps response_id to the source field that contains a stored Responses API response identifier. For example, {"response_id": "{{item.resp_id}}"}. Field names are case-sensitive.

[key: string] string

source OpenAI.EvalJsonlFileContentSource | OpenAI.EvalJsonlFileIdSource required

The inline JSONL content containing the response identifiers to retrieve. The azure_ai_responses data source supports file_content only; providing a file_id results in a 400 Bad Request response.

Any of the following:

type enum required

The type of jsonl source. Always file_content.

file_content

content OpenAI.EvalJsonlFileContentSourceContent[] required

The content of the jsonl file.

type enum required

The type of jsonl source. Always file_id.

file_id

id string required

The identifier of the file.

target_completion TargetCompletionItemGenerationParams

Parameters for generating target completions for simulated conversations. See simulate conversations.

type enum required

The type of item generation parameters, always target_completion.

target_completion

max_concurrency integer

The maximum number of target completions to execute concurrently. The services defaults to 1 if a value is not specified by the caller, which invokes the target sequentially.

synthetic_data_gen SyntheticDataGenerationItemGenerationParams

Represents the parameters for synthetic data generation item generation.

type enum required

The type of item generation parameters.

synthetic_data_gen

samples_count integer required

The maximum number of data samples to generate.

prompt string

The prompt used to generate synthetic data. This property is optional when the target is an agent that already has instructions.

model_deployment_name string required

The name of the model deployment to use for generating synthetic data.

output_dataset_name string

The name of the output dataset where generated synthetic data will be stored. If not provided, service generates dataset name automatically.

output_dataset_id string

The identifier of the output dataset where generated synthetic data is stored. The generated data is a jsonl file with columns id, query and test_description.

sources OpenAI.EvalJsonlFileIdSource[] required

The optional seed data content source files for data generation.

type enum required

The type of data source, always azure_ai_user_conversation_simulation.

azure_ai_user_conversation_simulation

source OpenAI.EvalJsonlFileContentSource | OpenAI.EvalJsonlFileIdSource | UserConversationSimulationInlineTestCasesSource required

Sources supported by user conversation simulation.

Any of the following:

type enum required

The type of jsonl source. Always file_content.

file_content

content OpenAI.EvalJsonlFileContentSourceContent[] required

The content of the jsonl file.

type enum required

The type of jsonl source. Always file_id.

file_id

id string required

The identifier of the file.

type enum required

The source type. Always inline_user_conversation_simulation.

inline_user_conversation_simulation

test_cases UserConversationSimulationTestCase[] required

Test scenarios from which user conversations are simulated. At least one test case is required.

target azure_ai_model | azure_ai_agent required

Base class for targets with discriminator support.

One of the following:

azure_ai_model AzureAIModelTarget

A target that identifies an Azure AI model. See evaluate administrator-connected models.

type enum required

The type of target, always azure_ai_model.

azure_ai_model

model string

The name of the model deployment to invoke as the evaluation target.

sampling_params ModelSamplingParams

Represents a set of parameters used to control the sampling behavior of a language model during text generation.

temperature number

The temperature parameter for sampling. Defaults to 1.0.

top_p number

The top-p parameter for nucleus sampling. Defaults to 1.0.

seed integer

The random seed for reproducibility. Defaults to 42.

max_completion_tokens integer

The maximum number of tokens allowed in the completion.

azure_ai_agent AzureAIAgentTarget

A target that identifies an Azure AI agent. See evaluate model or agent targets.

type enum required

The type of target, always azure_ai_agent.

azure_ai_agent

name string required

The name of the Azure AI agent to invoke as the evaluation target.

version string

The version of the Azure AI agent. When omitted, the latest version is used.

tool_descriptions ToolDescription[]

Optional descriptions of tools available to the agent.

tools OpenAI.Tool[]

Tool definitions made available when invoking the agent.

model_configuration EvaluationModelConfiguration required

Configures the model that plays the simulated user. This model is separate from the evaluated target.

model string required

Model deployment that generates simulated user turns, in the format {connectionName}/modelDeploymentName.

sampling_params ModelSamplingParams

Represents a set of parameters used to control the sampling behavior of a language model during text generation.

temperature number

The temperature parameter for sampling. Defaults to 1.0.

top_p number

The top-p parameter for nucleus sampling. Defaults to 1.0.

seed integer

The random seed for reproducibility. Defaults to 42.

max_completion_tokens integer

The maximum number of tokens allowed in the completion.

voice_model azure-standard

Voice configuration used to convert text to speech for evaluation through the Voice Live endpoint.

One of the following:

azure-standard EvaluationAzureStandardVoiceModelConfiguration

Configures an Azure standard neural voice used to convert text to speech for evaluation through the Voice Live endpoint.

type enum required

The voice kind. Always azure-standard.

azure-standard

name string required

The Azure neural voice name.

temperature number

The synthesis temperature, from 0 to 1. When omitted, the service defaults to the underlying voice model's default temperature.

default_simulation_configuration UserConversationSimulationDefaultConfiguration

Configures default conversation behavior and optional run-wide persistence of generated conversations.

max_num_turns integer

Hard limit on turns in each conversation. When omitted, the service defaults to 20.

conversation_repetitions integer

Number of independent conversation repetitions for each test case. Defaults to 1 when not specified at either the data-source or test-case level.

desired_num_turns integer

Target number of turns in each conversation. The effective value cannot exceed the effective max_num_turns. When omitted, no target is set and the simulation model determines the conversation length dynamically from the scenario.

audio_effects UserConversationSimulationAudioEffectsConfiguration

Configures effects applied to simulated conversation audio.

effects UserConversationSimulationAudioEffect[]

Effects to apply to simulated audio.

volume_percentage integer

Volume of the configured audio effects, as a percentage from 1 through 100. When omitted, the service defaults to 15.

user_behavior UserConversationSimulationUserBehaviorConfiguration

Configures conversation behavior for the simulated user.

interruption default

Configuration for simulated user interruption behavior.

One of the following:

default UserConversationSimulationDefaultInterruptionConfiguration

Configures the default interruption behavior for the simulated user.

type enum required

The interruption type, always default.

default

enable_conversation_dataset_generation boolean

Whether to write all generated conversations to a versioned Foundry dataset. When enabled, the completed run includes a simulated_user_conversations entry in output_datasets. When omitted, the service defaults to false.

output_conversation_dataset_name string

Name of the dataset to which generated conversations are written. This property is used only when enable_conversation_dataset_generation is true. When omitted, the service generates a dataset name.

data_mapping object

Maps JSONL dataset attributes to user conversation simulation inputs when their names differ from the defaults. The default attribute names are test_case_id, test_case_category, test_case_description, and simulation_configuration, matching UserConversationSimulationTestCase. Omit when the dataset uses these names or when using inline_user_conversation_simulation.

[key: string] string

type enum required

The type of data source, always azure_ai_user_conversation_simulation_preview.

azure_ai_user_conversation_simulation_preview

source OpenAI.EvalJsonlFileContentSource | OpenAI.EvalJsonlFileIdSource | UserConversationSimulationInlineTestCasesSource required

Sources supported by user conversation simulation.

Any of the following:

type enum required

The type of jsonl source. Always file_content.

file_content

content OpenAI.EvalJsonlFileContentSourceContent[] required

The content of the jsonl file.

type enum required

The type of jsonl source. Always file_id.

file_id

id string required

The identifier of the file.

type enum required

The source type. Always inline_user_conversation_simulation.

inline_user_conversation_simulation

test_cases UserConversationSimulationTestCase[] required

Test scenarios from which user conversations are simulated. At least one test case is required.

target azure_ai_model | azure_ai_agent required

Base class for targets with discriminator support.

One of the following:

azure_ai_model AzureAIModelTarget

A target that identifies an Azure AI model. See evaluate administrator-connected models.

type enum required

The type of target, always azure_ai_model.

azure_ai_model

model string

The name of the model deployment to invoke as the evaluation target.

sampling_params ModelSamplingParams

Represents a set of parameters used to control the sampling behavior of a language model during text generation.

temperature number

The temperature parameter for sampling. Defaults to 1.0.

top_p number

The top-p parameter for nucleus sampling. Defaults to 1.0.

seed integer

The random seed for reproducibility. Defaults to 42.

max_completion_tokens integer

The maximum number of tokens allowed in the completion.

azure_ai_agent AzureAIAgentTarget

A target that identifies an Azure AI agent. See evaluate model or agent targets.

type enum required

The type of target, always azure_ai_agent.

azure_ai_agent

name string required

The name of the Azure AI agent to invoke as the evaluation target.

version string

The version of the Azure AI agent. When omitted, the latest version is used.

tool_descriptions ToolDescription[]

Optional descriptions of tools available to the agent.

tools OpenAI.Tool[]

Tool definitions made available when invoking the agent.

model_configuration EvaluationModelConfiguration required

Configures the model that plays the simulated user. This model is separate from the evaluated target.

model string required

Model deployment that generates simulated user turns, in the format {connectionName}/modelDeploymentName.

sampling_params ModelSamplingParams

Represents a set of parameters used to control the sampling behavior of a language model during text generation.

temperature number

The temperature parameter for sampling. Defaults to 1.0.

top_p number

The top-p parameter for nucleus sampling. Defaults to 1.0.

seed integer

The random seed for reproducibility. Defaults to 42.

max_completion_tokens integer

The maximum number of tokens allowed in the completion.

voice_model azure-standard

Voice configuration used to convert text to speech for evaluation through the Voice Live endpoint.

One of the following:

azure-standard EvaluationAzureStandardVoiceModelConfiguration

Configures an Azure standard neural voice used to convert text to speech for evaluation through the Voice Live endpoint.

type enum required

The voice kind. Always azure-standard.

azure-standard

name string required

The Azure neural voice name.

temperature number

The synthesis temperature, from 0 to 1. When omitted, the service defaults to the underlying voice model's default temperature.

default_simulation_configuration UserConversationSimulationDefaultConfiguration

Configures default conversation behavior and optional run-wide persistence of generated conversations.

max_num_turns integer

Hard limit on turns in each conversation. When omitted, the service defaults to 20.

conversation_repetitions integer

Number of independent conversation repetitions for each test case. Defaults to 1 when not specified at either the data-source or test-case level.

desired_num_turns integer

audio_effects UserConversationSimulationAudioEffectsConfiguration

Configures effects applied to simulated conversation audio.

effects UserConversationSimulationAudioEffect[]

Effects to apply to simulated audio.

volume_percentage integer

Volume of the configured audio effects, as a percentage from 1 through 100. When omitted, the service defaults to 15.

user_behavior UserConversationSimulationUserBehaviorConfiguration

Configures conversation behavior for the simulated user.

interruption default

Configuration for simulated user interruption behavior.

One of the following:

default UserConversationSimulationDefaultInterruptionConfiguration

Configures the default interruption behavior for the simulated user.

type enum required

The interruption type, always default.

default

enable_conversation_dataset_generation boolean

output_conversation_dataset_name string

data_mapping object

[key: string] string

evaluation_level enum | string

The level at which evaluation is performed.

Any of the following:

enum

turnconversation

string

humanEvaluationPreview HumanEvaluationPreviewRuleAction

Evaluation rule action for human evaluation.

type enum required

humanEvaluationPreview

templateId string required

Identifier of a saved asset.

filter EvaluationRuleFilter

Evaluation filter model.

agentName string required

Filter by agent name.

eventType string | enum required

Type of the evaluation rule event.

Any of the following:

string

enum

responseCompletedmanualtimerTrigger

schedule Cron | Recurrence | OneTime

Base model for Trigger of the schedule.

One of the following:

Cron CronTrigger

Cron based trigger.

type enum required

Cron

expression string required

Five-field cron expression that defines the schedule frequency: minute hour day-of-month month day-of-week.

timeZone string

Time zone for the cron schedule. Defaults to UTC.

startTime string

Start time for the cron schedule in ISO 8601 format.

endTime string

End time for the cron schedule in ISO 8601 format.

Recurrence RecurrenceTrigger

Recurrence based trigger.

type enum required

Type of the trigger.

Recurrence

startTime string

Start time for the recurrence schedule in ISO 8601 format.

endTime string

End time for the recurrence schedule in ISO 8601 format.

timeZone string

Time zone for the recurrence schedule. Defaults to UTC.

interval integer required

Interval for the recurrence schedule.

schedule Hourly | Daily | Weekly | Monthly required

Recurrence schedule model.

One of the following:

Hourly HourlyRecurrenceSchedule

Hourly recurrence schedule.

type enum required

Hourly

Daily DailyRecurrenceSchedule

Daily recurrence schedule.

type enum required

Daily recurrence type.

Daily

hours integer[]

Hours for the recurrence schedule. If omitted, the service uses the current UTC hour when the schedule is created.

Weekly WeeklyRecurrenceSchedule

Weekly recurrence schedule.

type enum required

Weekly recurrence type.

Weekly

daysOfWeek DayOfWeek[] required

Days of the week for the recurrence schedule.

Monthly MonthlyRecurrenceSchedule

Monthly recurrence schedule.

type enum required

Monthly recurrence type.

Monthly

daysOfMonth integer[] required

Days of the month for the recurrence schedule.

OneTime OneTimeTrigger

One-time trigger.

type enum required

OneTime

triggerAt string required

Date and time for the one-time trigger in ISO 8601 format.

timeZone string

Time zone for the one-time trigger. Defaults to UTC.

provisioningStatus string | enum

Schedule provisioning status.

Any of the following:

string

enum

CreatingUpdatingDeletingSucceededFailed

error Azure.Core.Foundations.Error

The error object.

code string required

One of a server-defined set of error codes.

message string required

A human-readable representation of the error.

target string

The target of the error.

details Azure.Core.Foundations.Error[]

An array of details about specific errors that led to this reported error.

innererror Azure.Core.Foundations.InnerError

An object containing more specific information about the error. As per Azure REST API guidelines - https://aka.ms/AzureRestApiGuidelines#handling-errors.

code string

One of a server-defined set of error codes.

innererror Azure.Core.Foundations.InnerError

enabled boolean required

Indicates whether the evaluation rule is enabled. Default is true.

systemData object required

System metadata for the evaluation rule.

[key: string] string

Get an evaluation rule

Query parameters

Path parameters

Responses

Body

Headers

Body

Headers

Body

Request

Response