DataRobot

Supported OS Linux Windows Mac OS

marketplace
Integration version1.0.0
CDS DataRobot - Overview
CDS DataRobot - Deployments
CDS DataRobot - Models
CDS DataRobot - Prediction
CDS DataRobot - LLM
CDS DataRobot - Use Cases

Overview

DataRobot is an AI platform that uses machine learning to automate the process of building, deploying, and managing models. It’s designed to help organizations of all sizes use AI to improve their business outcomes. With DataRobot, users can create and deploy models on their datasets to generate predictions while also designing custom blueprints for their machine learning workflows.

This integration enables seamless collection and visualization of DataRobot’s data as metrics and logs in Datadog. You can configure the following components:

Inventory Data:

  • Deployments
    • Dependent Components: BatchServiceStats, Accuracy, ServiceStatsOverTime, ServiceStats [Metric Ingestion], PredictionsVsActualsOverTime, HumilityStatsOverTime, FeatureDrift, TargetDrift
  • LLM
    • Related Components: LLMApiCalls [Metric Ingestion]
  • Projects
    • Dependent Components: Models
    • Project - Model Dependent Components: ModelDetails, NumIterationsTrained, MissingReport, Features, CrossValidationScores
  • ModelPackages
  • ExternalDataSources
  • ExternalDataDrivers
  • ExternalDataStores
  • BatchPredictions

Non Inventory Data:

  • UseCases
    • Dependent Components: Data, Projects
  • LLMBlueprints
  • Playground

This integration includes six out-of-the-box dashboards:

  1. Use Cases: Monitor and visualize UseCases statistics, including associated datasets and projects.

  2. Deployments: Displays an overview of deployments collected at the user-defined interval_for_inventory.

  3. Models: Monitors model statistics collected at the user-defined interval_for_inventory.

  4. LLM: Shows an overview of LLM-related information collected at the user-defined interval_for_inventory.

  5. Predictions: Presents an overview of prediction-related information collected at the user-defined interval_for_inventory.

  6. Overview: Summarizes data from Playgrounds, ExternalDataSources, ExternalDataStores and ExternalDataDrivers collected at the user-defined interval_for_inventory.

Data Collected

Metrics

cds.datarobot.deployments.totalPredictions
(gauge)		Total number of predictions made by deployments.
cds.datarobot.deployments.totalRequests
(gauge)		Total number of API requests received by deployments.
cds.datarobot.deployments.slowRequests
(gauge)		Number of requests that took longer than expected to process.
cds.datarobot.deployments.executionTime
(gauge)		Total execution time for prediction requests.
Shown as second
cds.datarobot.deployments.responseTime
(gauge)		Time taken to respond to client requests.
Shown as second
cds.datarobot.deployments.userErrorRate
(gauge)		Percentage of errors caused by user-related issues.
Shown as percent
cds.datarobot.deployments.serverErrorRate
(gauge)		Percentage of errors caused by server-side issues.
Shown as percent
cds.datarobot.deployments.numConsumers
(gauge)		Number of active consumers using the deployment.
cds.datarobot.deployments.cacheHitRatio
(gauge)		Percentage of requests served from cache.
Shown as percent
cds.datarobot.deployments.medianLoad
(gauge)		Median number of concurrent requests handled.
cds.datarobot.deployments.peakLoad
(gauge)		Highest number of concurrent requests handled.
cds.datarobot.llmApiCalls.counter
(gauge)		Total number of LLM API calls made.

Service Checks

crest_data_systems_datarobot.status

Returns CRITICAL if the user configurations are invalid or authentication fails. Returns OK otherwise.

Statuses: ok, critical

Support

For support or feature requests, contact Crest Data through the following channels:

This application is made available through the Marketplace and is supported by a Datadog Technology Partner. Click Here to purchase this application.