Paradime Help Docs
Get Started
  • 🚀Introduction
  • 📃Guides
    • Paradime 101
      • Getting Started with your Paradime Workspace
        • Creating a Workspace
        • Setting Up Data Warehouse Connections
        • Managing workspace configurations
        • Managing Users in the Workspace
      • Getting Started with the Paradime IDE
        • Setting Up a dbt™ Project
        • Creating a dbt™ Model
        • Data Exploration in the Code IDE
        • DinoAI: Accelerating Your Analytics Engineering Workflow
          • DinoAI Agent
            • Creating dbt Sources from Data Warehouse
            • Generating Base Models
            • Building Intermediate/Marts Models
            • Documentation Generation
            • Data Pipeline Configuration
            • Using .dinorules to Tailor Your AI Experience
          • Accelerating GitOps
          • Accelerating Data Governance
          • Accelerating dbt™ Development
        • Utilizing Advanced Developer Features
          • Visualize Data Lineage
          • Auto-generated Data Documentation
          • Enforce SQL and YAML Best Practices
          • Working with CSV Files
      • Managing dbt™ Schedules with Bolt
        • Creating Bolt Schedules
        • Understanding schedule types and triggers
        • Viewing Run History and Analytics
        • Setting Up Notifications
        • Debugging Failed Runs
    • Migrating from dbt™ cloud to Paradime
  • 🔍Concepts
    • Working with Git
      • Git Lite
      • Git Advanced
      • Read Only Branches
      • Delete Branches
      • Merge Conflicts
      • Configuring Signed Commits on Paradime with SSH Keys
      • GitHub Branch Protection Guide: Preventing Direct Commits to Main
    • dbt™ fundamentals
      • Getting started with dbt™
        • Introduction
        • Project Strucuture
        • Working with Sources
        • Testing Data Quality
        • Models and Transformations
      • Configuring your dbt™ Project
        • Setting up your dbt_project.yml
        • Defining Your Sources in sources.yml
        • Testing Source Freshness
        • Unit Testing
        • Working with Tags
        • Managing Seeds
        • Environment Management
        • Variables and Parameters
        • Macros
        • Custom Tests
        • Hooks & Operational Tasks
        • Packages
      • Model Materializations
        • Table Materialization
        • View​ Materialization
        • Incremental Materialization
          • Using Merge for Incremental Models
          • Using Delete+Insert for Incremental Models
          • Using Append for Incremental Models
          • Using Microbatch for Incremental Models
        • Ephemeral Materialization
        • Snapshots
      • Running dbt™
        • Mastering the dbt™ CLI
          • Commands
          • Methods
          • Selector Methods
          • Graph Operators
    • Paradime fundamentals
      • Global Search
        • Paradime Apps Navigation
        • Invite users to your workspace
        • Search and preview Bolt schedules status
      • Using --defer in Paradime
      • Workspaces and data mesh
    • Data Warehouse essentials
      • BigQuery Multi-Project Service Account
  • 📖Documentation
    • DinoAI
      • Agent Mode
        • Use Cases
          • Creating Sources from your Warehouse
          • Generating dbt™ models
          • Fixing Errors with Jira
          • Researching with Perplexity
          • Providing Additional Context Using PDFs
      • Context
        • File Context
        • Directory Context
      • Tools and Features
        • Warehouse Tool
        • File System Tool
        • PDF Tool
        • Jira Tool
        • Perplexity Tool
        • Terminal Tool
        • Coming Soon Tools...
      • .dinorules
      • Ask Mode
      • Version Control
      • Production Pipelines
      • Data Documentation
    • Code IDE
      • User interface
        • Autocompletion
        • Context Menu
        • Flexible layout
        • "Peek" and "Go To" Definition
        • IDE preferences
        • Shortcuts
      • Left Panel
        • DinoAI Coplot
        • Search, Find, and Replace
        • Git Lite
        • Bookmarks
      • Command Panel
        • Data Explorer
        • Lineage
        • Catalog
        • Lint
      • Terminal
        • Running dbt™
        • Paradime CLI
      • Additional Features
        • Scratchpad
    • Bolt
      • Creating Schedules
        • 1. Schedule Settings
        • 2. Command Settings
          • dbt™ Commands
          • Python Scripts
          • Elementary Commands
          • Lightdash Commands
          • Tableau Workbook Refresh
          • Power BI Dataset Refresh
          • Paradime Bolt Schedule Toggle Commands
          • Monte Carlo Commands
        • 3. Trigger Types
        • 4. Notification Settings
        • Templates
          • Run and Test all your dbt™ Models
          • Snapshot Source Data Freshness
          • Build and Test Models with New Source Data
          • Test Code Changes On Pull Requests
          • Re-executes the last dbt™ command from the point of failure
          • Deploy Code Changes On Merge
          • Create Jira Tickets
          • Trigger Census Syncs
          • Trigger Hex Projects
          • Create Linear Issues
          • Create New Relic Incidents
          • Create Azure DevOps Items
        • Schedules as Code
      • Managing Schedules
        • Schedule Configurations
        • Viewing Run Log History
        • Analyzing Individual Run Details
          • Configuring Source Freshness
      • Bolt API
      • Special Environment Variables
        • Audit environment variables
        • Runtime environment variables
      • Integrations
        • Reverse ETL
          • Hightouch
        • Orchestration
          • Airflow
          • Azure Data Factory (ADF)
      • CI/CD
        • Turbo CI
          • Azure DevOps
          • BitBucket
          • GitHub
          • GitLab
          • Paradime Turbo CI Schema Cleanup
        • Continuous Deployment with Bolt
          • GitHub Native Continuous Deployment
          • Using Azure Pipelines
          • Using BitBucket Pipelines
          • Using GitLab Pipelines
        • Column-Level Lineage Diff
          • dbt™ mesh
          • Looker
          • Tableau
          • Thoughtspot
    • Radar
      • Get Started
      • Cost Management
        • Snowflake Cost Optimization
        • Snowflake Cost Monitoring
        • BigQuery Cost Monitoring
      • dbt™ Monitoring
        • Schedules Dashboard
        • Models Dashboard
        • Sources Dashboard
        • Tests Dashboard
      • Team Efficiency Tracking
      • Real-time Alerting
      • Looker Monitoring
    • Data Catalog
      • Data Assets
        • Looker assets
        • Tableau assets
        • Power BI assets
        • Sigma assets
        • ThoughtSpot assets
        • Fivetran assets
        • dbt™️ assets
      • Lineage
        • Search and Discovery
        • Filters and Nodes interaction
        • Nodes navigation
        • Canvas interactions
        • Compare Lineage version
    • Integrations
      • Dashboards
        • Sigma
        • ThoughtSpot (Beta)
        • Lightdash
        • Tableau
        • Looker
        • Power BI
        • Streamlit
      • Code IDE
        • Cube CLI
        • dbt™️ generator
        • Prettier
        • Harlequin
        • SQLFluff
        • Rainbow CSV
        • Mermaid
          • Architecture Diagrams
          • Block Diagrams Documentation
          • Class Diagrams
          • Entity Relationship Diagrams
          • Gantt Diagrams
          • GitGraph Diagrams
          • Mindmaps
          • Pie Chart Diagrams
          • Quadrant Charts
          • Requirement Diagrams
          • Sankey Diagrams
          • Sequence Diagrams
          • State Diagrams
          • Timeline Diagrams
          • User Journey Diagrams
          • XY Chart
          • ZenUML
        • pre-commit
          • Paradime Setup and Configuration
          • dbt™️-checkpoint hooks
            • dbt™️ Model checks
            • dbt™️ Script checks
            • dbt™️ Source checks
            • dbt™️ Macro checks
            • dbt™️ Modifiers
            • dbt™️ commands
            • dbt™️ checks
          • SQLFluff hooks
          • Prettier hooks
      • Observability
        • Elementary Data
          • Anomaly Detection Tests
            • Anomaly tests parameters
            • Volume anomalies
            • Freshness anomalies
            • Event freshness anomalies
            • Dimension anomalies
            • All columns anomalies
            • Column anomalies
          • Schema Tests
            • Schema changes
            • Schema changes from baseline
          • Sending alerts
            • Slack alerts
            • Microsoft Teams alerts
            • Alerts Configuration and Customization
          • Generate observability report
          • CLI commands and usage
        • Monte Carlo
      • Storage
        • Amazon S3
        • Snowflake Storage
      • Reverse ETL
        • Hightouch
      • CI/CD
        • GitHub
        • Spectacles
      • Notifications
        • Microsoft Teams
        • Slack
      • ETL
        • Fivetran
    • Security
      • Single Sign On (SSO)
        • Okta SSO
        • Azure AD SSO
        • Google SAML SSO
        • Google Workspace SSO
        • JumpCloud SSO
      • Audit Logs
      • Security model
      • Privacy model
      • FAQs
      • Trust Center
      • Security
    • Settings
      • Workspaces
      • Git Repositories
        • Importing a repository
          • Azure DevOps
          • BitBucket
          • GitHub
          • GitLab
        • Update connected git repository
      • Connections
        • Code IDE environment
          • Amazon Athena
          • BigQuery
          • Clickhouse
          • Databricks
          • Dremio
          • DuckDB
          • Firebolt
          • Microsoft Fabric
          • Microsoft SQL Server
          • MotherDuck
          • PostgreSQL
          • Redshift
          • Snowflake
          • Starburst/Trino
        • Scheduler environment
          • Amazon Athena
          • BigQuery
          • Clickhouse
          • Databricks
          • Dremio
          • DuckDB
          • Firebolt
          • Microsoft Fabric
          • Microsoft SQL Server
          • MotherDuck
          • PostgreSQL
          • Redshift
          • Snowflake
          • Starburst/Trino
        • Manage connections
          • Set alternative default connection
          • Delete connections
        • Cost connection
          • BigQuery cost connection
          • Snowflake cost connection
        • Connection Security
          • AWS PrivateLink
            • Snowflake PrivateLink
            • Redshift PrivateLink
          • BigQuery OAuth
          • Snowflake OAuth
        • Optional connection attributes
      • Notifications
      • dbt™
        • Upgrade dbt Core™ version
      • Users
        • Invite users
        • Manage Users
        • Enable Auto-join
        • Users and licences
        • Default Roles and Permissions
        • Role-based access control
      • Environment Variables
        • Bolt Schedules Environment Variables
        • Code IDE Environment Variables
  • 💻Developers
    • GraphQL API
      • Authentication
      • Examples
        • Audit Logs API
        • Bolt API
        • User Management API
        • Workspace Management API
    • Python SDK
      • Getting Started
      • Modules
        • Audit Log
        • Bolt
        • Lineage Diff
        • Custom Integration
        • User Management
        • Workspace Management
    • Paradime CLI
      • Getting Started
      • Bolt CLI
    • Webhooks
      • Getting Started
      • Custom Webhook Guides
        • Create an Azure DevOps Work item when a Bolt run complete with errors
        • Create a Linear Issue when a Bolt run complete with errors
        • Create a Jira Issue when a Bolt run complete with errors
        • Trigger a Slack notification when a Bolt run is overrunning
    • Virtual Environments
      • Using Poetry
      • Troubleshooting
    • API Keys
    • IP Restrictions in Paradime
    • Company & Workspace token
  • 🙌Best Practices
    • Data Mesh Setup
      • Configure Project dependencies
      • Model access
      • Model groups
  • ‼️Troubleshooting
    • Errors
    • Error List
    • Restart Code IDE
  • 🔗Other Links
    • Terms of Service
    • Privacy Policy
    • Paradime Blog
Powered by GitBook
On this page
  • Key Features
  • Available Alerts
  • 1. How to Configure Alerts
  • 2. Receiving and Acting on Alerts

Was this helpful?

  1. Documentation
  2. Radar

Real-time Alerting

PreviousTeam Efficiency TrackingNextLooker Monitoring

Last updated 6 months ago

Was this helpful?

Radar's real-time Alerting feature provides instant notifications for critical events in your data pipeline, allowing you to act promptly on issues related to job performance, cost spikes, and data quality. This proactive approach helps maintain SLA targets and control costs effectively.

Prerequisites

  • Completed the in Radar's .

Key Features

  • Comprehensive Coverage: Built-in alerts for various scenarios for your pipelines: Snowflake, BigQuery, Bolt Schedules.

  • Multi-channel Notifications: Receive on-time alerts via Slack, MS Teams, and email.


Available Alerts

Alert Name
Description
Recommended Threshold

Project Cost Anomaly Alert

Alerts when a project's cost exceeds a set percentage (e.g., 20%) above the daily average over the past 7 days.

0.2

User Cost Anomaly Alert

Alerts when a user's cost exceeds a set percentage (e.g., 20%) above the daily average over the past 7 days. Focuses on the top 10 costly users.

0.2

dbt Cost Anomaly Alert

Alerts when a dbt model's cost exceeds a set percentage (e.g., 20%) above the daily average over the past 7 days. Focuses on the top 10 costly dbt models.

0.2

Query Cost Anomaly Alert

Alerts when a specific query's cost exceeds a set percentage (e.g., 20%) above the daily average over the past 7 days. Focuses on the top 10 costly queries.

0.2

Warehouse Compute Cost Anomaly Alert

Alerts when a warehouse's compute cost exceeds a set percentage (e.g., 20%) of the daily average costs over the past 7 days.

0.2

Query Remote Spillage Ratio Anomaly Alert

Alerts when the ratio of bytes spilled to remote storage exceeds 5 times the total bytes scanned. Focuses on the top 10 queries with the highest costs.

5

Alert Name
Description
Recommended Threshold

Project Cost Anomaly Alert

Alerts when a project's cost exceeds a set percentage (e.g., 20%) above the daily average over the past 7 days.

0.2

User Cost Anomaly Alert

Alerts when a user's cost exceeds a set percentage (e.g., 20%) above the daily average over the past 7 days. Focuses on the top 10 costly users.

0.2

dbt Cost Anomaly Alert

Alerts when a dbt model's cost exceeds a set percentage (e.g., 20%) above the daily average over the past 7 days. Focuses on the top 10 costly dbt models.

0.2

Query Cost Anomaly Alert

Alerts when a specific query's cost exceeds a set percentage (e.g., 20%) above the daily average over the past 7 days. Focuses on the top 10 costly queries.

0.2

Small Query Waste Anomaly Alert

Alerts when the difference between billed bytes and processed bytes exceeds a set percentage (e.g., 5%) of total billed bytes for a project in a day.

0.05

High Shuffle Spill Anomaly Alert

Alerts when shuffled bytes spilled to disk exceed a set percentage (e.g., 20%) of total bytes processed. Focuses on the top 10 queries with the highest processed bytes.

0.2

Query Runtime Anomaly Alert

Alerts when query runtime increases by more than a set percentage (e.g., 50%) compared to the average over the past week.

0.5

Query Slot Usage Anomaly Alert

Alerts when average slot usage increases by more than a set percentage (e.g., 50%) compared to the average over the past week. Focuses on the top 10 costly queries.

1

Alert Name
Description
Recommended Threshold

Schedules Time Guard Alert

Alerts when a schedule run takes longer than expected. The alert triggers when a schedule takes more than a set percentage (e.g., 20%) longer than the average over the last 7 days.

0.2

Threshold Range: All thresholds must be set between 0-1 for valid configurations.


1. How to Configure Alerts

  1. Navigate to the Data Alerts section in Radar.

  2. Select the alert you want to configure.

  3. Set the threshold for the alert. For example:

    • For cost anomaly alerts, a threshold of 0.2 means the alert will trigger when costs exceed 20% above the average of the past 7 days.

    • For time-based alerts like the Schedules Time Guard, a threshold of 0.2 means the alert will trigger when a run takes 20% longer than the average of the past 7 days.

  4. Click the toggle switch to enable/disable the alert.


2. Receiving and Acting on Alerts

When an alert is triggered, you'll receive a notification through your configured channels (Slack, MS Teams, or email). The alert will provide:

  • A description of the issue

  • Relevant metrics and comparisons

  • Suggested actions to address the problem

How to Act on Alerts:

  • Use this information to quickly diagnose and resolve issues, helping to maintain the efficiency and cost-effectiveness of your data operations.


Best Practices

  1. Start with key metrics: Begin by setting up alerts for your most critical operations and costs.

  2. Refine thresholds: Adjust alert thresholds over time based on your specific needs and patterns.

  3. Regular review: Periodically review your alert configurations to ensure they remain relevant and effective.

  4. Team alignment: Ensure that the right team members are receiving the appropriate alerts for quick action.

📖
Get Started guide
Real-time Alerting setup