⭐API Overview
NOTE: Metrics Advisor for Equipment (Project Adel) is currently in private preview. Some features may not be supported or have limited capabilities. The current API version is 2022-07-10-preview.
| REST API | Python SDK |
Metrics Advisor for Equipment offers a full list of APIs, covering functionalities in:
You should also refer to Quotas and limits for a quick reference and a detailed description the quotas and limits for Metrics Advisor for Equipment.
Here are the 32 APIs in Metrics Advisor for Equipment:
Datasets (4 APIs)
A dataset in Metrics Advisor for Equipment contains the metadata describing where the data is and what the data actually looks like. Specifically, it contains the location of the data source, the data schema, and other information. The dataset you created can be used for model training, evaluation, and/or real-time streaming inference.
| HTTP Method | API Path | Description |
|---|---|---|
| PUT | /datasets/{datasetName} | Create/add a dataset for training, evaluation, or real-time inference. |
| GET | /datasets/{datasetName} | Get dataset info including data source type, data schema, data granularity, etc. |
| GET | /datasets[?skip][&maxpagesize][&sortBy][&orderBy] | List models in a Metrics Advisor resource. |
| DELETE | /datasets/{datasetName} | Delete a dataset in a Metrics Advisor resource. This action doesn't delete the data in the source system. |
Models (4 APIs)
A Metrics Advisor for Equipment model is a machine learning model that learns the patterns of normal behavior (i.e., training dataset) and detects abnormal behavior that could be potential equipment failure (or maintenance events). On the backend, we will divide your training dataset into train & test sets and return the training and validaiton loss scores for your reference.
| HTTP Method | API Path | Description |
|---|---|---|
| PUT | /multivariate/models/{modelName} | Create and train a model. |
| GET | /multivariate/models/{modelName} | Get model info including training dataset, training time range(s), variables being used, training job status, etc. |
| GET | /multivariate/models[?skip][&maxpagesize][&sortBy][&orderBy][&status][&datasetNames][&topPerDataset] | List models in a Metrics Advisor resource. |
| DELETE | /multivariate/models/{modelName} | Delete a model in a Metrics Advisor resource. |
Evaluations (4 APIs)
An evaluation is the process of using different dataset(s) to test the performance a trained model. You are highly recommended to review and tune the evaluation results with subject matter expertises (SMEs) at your company.
| HTTP Method | API Path | Description |
|---|---|---|
| PUT | /multivariate/evaluations/{evaluationName} | Create a model evaluation. |
| GET | /multivariate/evaluations/{evaluationName} | Get model evaluation info including model evaluated, evaluation dataset, evaluation time range, evaluation job status, etc. |
| GET | /multivariate/evaluations[?skip][&maxpagesize][&sortBy][&orderBy][&status][&modelNames][&topPerModel] | List model evaluations in a Metrics Advisor resource. |
| DELETE | /multivariate/evaluations/{evaluationName} | Delete an evaluation in a Metrics Advisor resource. |
Hooks and Alert Configurations (10 APIs)
A hook is a channel to receive alert notifications.
| HTTP Method | API Path | Description |
|---|---|---|
| PUT | /hooks/{hookName} | Create a hook. |
| GET | /hooks/{hookName} | Get hook info including hook type and associated set up details. |
| GET | /hooks[?skip][&maxapgesize][&sortBy][&orderBy] | List hooks in a Metrics Advisor resource. |
| DELETE | /hooks/{hookName} | Delete a hook in a Metrics Advisor resource. |
| PATCH | /hooks/{hookName} | Update a hook. Updatable properties differ by hook type. |
An alert configuration allows users to set up criteria that determine which anomalies should trigger an alert and via which hook(s). This setting can later be applied to a streaming inference schedule. You are highly recommended to evaluate the model first and consult subject matter expertises (SMEs) at your company when setting up alert configurations.
| HTTP Method | API Path | Description |
|---|---|---|
| PUT | /alertConfigs/{alertConfigName} | Create an alert configuration. |
| GET | /alertConfigs/{alertConfigName} | Get alert configuration info including alert configuration type and associated settings. |
| GET | /alertConfigs[?skip][&maxapgesize][&sortBy][&orderBy] | List alert configurations in a Metrics Advisor resource. |
| DELETE | /alertConfigs/{alertConfigName} | Delete an alert configuration in a Metrics Advisor resource. |
| PATCH | /alertConfigs/{alertConfigName} | Update an alert configuration. Updatable properties differ by alert configuraiton type. |
Inference Schedule (10 APIs)
An inference schedule sets up a streaming inference pipeline to analyze incoming data in real-time.
| HTTP Method | API Path | Description |
|---|---|---|
| PUT | /inference/schedules/{scheduleName} | Create an inference schedule. |
| GET | /inference/schedules/{scheduleName} | Get inference schedule info including model used, dataset used, data delay offset (if applicable), schedule start time , alert configurations, etc. |
| GET | /inference/schedules[?skip][&maxpagesize][&sortBy][&orderBy][&status][&modelNames][&topPerModel] | List inference schedules in a Metrics Advisor resource. |
| DELETE | /inference/schedules/{scheduleName} | Delete an inference schedule in a Metrics Advisor resource. |
| PATCH | /inference/schedules/{scheduleName} | Pause/resume or update selected properties of an inference schedule. Updatable properties: inference status, model to be inferenced with, data delay offset, alert configurations. |
| GET | /inference/schedules/{scheduleName}/getHistory | Retrieve detected anomalies over a historical time period. |
A replay allows you to inference a historical time range with settings from an exiting inference schedule. The new anomaly detection results will overwrite the historical results in the replay time range but no alerts will be sent out.
| HTTP Method | API Path | Description |
|---|---|---|
| PUT | /inference/replays/{replayName} | Create a replay on an inference schedule. |
| GET | /inference/replays/{replayName} | Get replay info including associated inference schedule, replay time range, replay job status, etc. |
| GET | /inference/replays[?skip][&maxpagesize][&sortBy][&orderBy][&status][&scheduleName][&topPerSchedule] | List replay jobs in a Metrics Advisor resource. |
| DELETE | /inference/replays/{replayName} | Delete a replay job in a Metrics Advisor resource. This action doesn't revert the inference results in the replay time range. |