Aporia Documentation
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  • ๐Ÿ“–Aporia Docs
  • ๐Ÿค—Introduction
    • Quickstart
    • Support
  • ๐Ÿ’กCore Concepts
    • Why Monitor ML Models?
    • Understanding Data Drift
    • Analyzing Performance
    • Tracking Data Segments
    • Models & Versions
  • ๐Ÿš€Deployment
    • AWS
    • Google Cloud
    • Azure
    • Databricks
    • Offline / On-Prem
    • Platform Architecture
  • ๐Ÿ Storing your Predictions
    • Overview
    • Real-time Models (Postgres)
    • Real-time Models (Kafka)
    • Batch Models
    • Kubeflow / KServe
  • ๐Ÿง Model Types
    • Regression
    • Binary Classification
    • Multiclass Classification
    • Multi-Label Classification
    • Ranking
  • ๐ŸŒˆExplainability
    • SHAP values
  • ๐Ÿ“œNLP
    • Intro to NLP Monitoring
    • Example: Text Classification
    • Example: Token Classification
    • Example: Question Answering
  • ๐ŸชData Sources
    • Overview
    • Amazon S3
    • Athena
    • BigQuery
    • Databricks
    • Glue Data Catalog
    • Google Cloud Storage
    • PostgreSQL
    • Redshift
    • Snowflake
    • Microsoft SQL Server
    • Oracle
  • โšกMonitors & Alerts
    • Overview
    • Data Drift
    • Metric Change
    • Missing Values
    • Model Activity
    • Model Staleness
    • Performance Degradation
    • Prediction Drift
    • Value Range
    • Custom Metric
    • New Values
    • Alerts Consolidation
  • ๐ŸŽจDashboards
    • Overview
  • ๐Ÿค–ML Monitoring as Code
    • Getting started
    • Adding new models
    • Data Segments
    • Custom metrics
    • Querying metrics
    • Monitors
    • Dashboards
  • ๐Ÿ“กIntegrations
    • Slack
    • Webhook
    • Teams
    • Single Sign On (SAML)
    • Cisco
  • ๐Ÿ”Administration
    • Role Based Access Control (RBAC)
  • ๐Ÿ”‘API Reference
    • REST API
    • API Extended Reference
    • Custom Segment Syntax
    • Custom Metric Syntax
    • Code-Based Metrics
    • Metrics Glossary
  • โฉRelease Notes
    • Release Notes 2024
    • Release Notes 2023
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On this page
  • Add a Webhook integration
  • Alert's format
  1. Integrations

Webhook

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Last updated 2 years ago

Aporia allows you to send alerts generated from Aporiaโ€™s monitors to any system using webhooks.

Add a Webhook integration

  1. Log into Aporiaโ€™s console. On the navbar on the left, click on Integrations, switch to the Applications tab and choose Webhook.

  2. Enter your Integration Name, Webhook URL and Custom Headers(optional). The url should include the schema (http/ https).

  3. Click Save. On success the save button will become disabled, and you'll be able to Test or Remove the integration.

Congratulations: Youโ€™ve now successfully added your webhook integration to Aporia!

After Integrating your webhook you'll be able to select sending alerts to your webhook in the Custom mode of the monitor builder.

Alert's format

The alert will be sent by POST action to the URL defined in the integration, as a JSON in the following format:

Key
Description

alert_id

The ID of the alert.

monitor_type

The type of the monitor that rose the alert.

monitor_id

The ID of the monitor that rose the alert.

monitor_name

The name of the monitor that rose the alert.

model_id

The ID of the model that the monitor created on.

model_name

The name of the model that the monitor created on.

severity

The severity of the alert as defined when building the monitor.

monitor_notes

Additional monitor notes added by the user.

pretty_description

A short pretty summery about the specific alert.

dashboard_link

A link for the alert in the Aporia's dashboard for farther investigation.

You'll be able to see an example alert by clicking on Test in the Webhook Integration page mentioned in the previous section.

Happy Monitoring!

๐Ÿ“ก
Webhook integration
Webhook configuration
Monitor with webhook action