Custom Scheduling For Monitors
Configure flexible monitoring schedules to match your data pipeline and business requirements.
Take control of your monitoring frequency with flexible scheduling options that align with your data update patterns and business requirements.
Scheduling Strategy Guide
Choose the right frequency based on your data characteristics and monitoring needs:
Quick Selection Guide
Frequency
Best For
Use Cases
Resource Impact
Every 1 Hour
Real-time systems
Live dashboards, streaming data
High
Every 3 Hours
Active pipelines
ETL processes, API feeds
Medium-High
Every 6 Hours
Regular updates
Business reporting, batch jobs
Medium
Every 12 Hours
Daily processes
Nightly ETL, twice-daily updates
Low-Medium
Daily
Standard reporting
Business reports, compliance checks
Low
Weekly
Periodic data
Reference data, slow-changing dimensions
Very Low
Monthly
Historical data
Archive validation, trend analysis
Minimal
Frequency Options
High-Frequency Monitoring (1-6 Hours)
Every 1 Hour ⚡
Ideal for: Real-time dashboards, streaming data, critical business metrics
Consider: High resource usage, potential for alert fatigue
Best practices: Use for truly time-sensitive data only
Every 3 Hours 🔄
Ideal for: Active ETL pipelines, frequent API updates
Consider: Good balance of coverage and resource efficiency
Best practices: Monitor business hours vs. off-hours patterns
Every 6 Hours ⏰
Ideal for: Regular batch processes, scheduled data loads
Consider: Covers most business scenarios without overwhelming
Best practices: Align with your ETL schedule timing
Standard Monitoring (12 Hours)
Every 12 Hours 📊
Ideal for: Daily business processes, twice-daily updates
Consider: Catches issues within business day cycles
Best practices: Schedule to align with business operations

Advanced Scheduling Options
Daily Scheduling 📅
For precise control over daily monitoring:
Configuration Options:
Timezone Selection: Align with your business timezone
Specific Time: Set exact execution time (24-hour format)
Business Day Alignment: Consider peak vs. off-hours monitoring
Best Practices:
Schedule after ETL completion times
Avoid peak business hours for large table scans
Consider data team working hours for incident response

Weekly Scheduling 📋
Configuration Options:
Day Selection: Choose specific day of the week
Timezone: Business timezone alignment
Time: Specific execution time
Ideal Use Cases:
Reference data validation
Weekly report quality checks
Slow-changing dimension monitoring
Compliance reporting

Monthly Scheduling 📆
Configuration Options:
Day Selection:
Every "N"th day of the month (up to 28th)
Every last day of the month (for 30th/31st requirements)
Timezone: Business alignment
Time: Specific execution time
Ideal Use Cases:
Month-end financial data
Periodic compliance checks
Historical data validation
Archive integrity monitoring

Setup Process
Accessing Custom Scheduling
Navigate to Config > Create
Select your monitor type (Freshness, Volume, Field Health, Custom SQL)
Choose "Scheduled" monitor mode
Configure frequency in the setup form
Configuration Steps
Select Base Frequency from the available options
Configure Details (for Daily/Weekly/Monthly):
Set timezone
Choose specific day (Weekly/Monthly)
Set execution time
Validate Settings against your data patterns
Save Configuration and monitor performance
Best Practices & Optimization
🎯 Frequency Selection Strategy
Start Conservative:
Begin with lower frequencies (Daily/Weekly)
Monitor alert patterns and false positives
Increase frequency only if needed for timely detection
Match Data Patterns:
Hourly data updates → Every 1-3 hours monitoring
Daily ETL jobs → Daily monitoring (post-job completion)
Weekly batch loads → Weekly monitoring
Monthly reporting → Monthly monitoring
⚡ Performance Considerations
Resource Management:
High-frequency monitoring increases compute costs
Balance monitoring coverage with resource efficiency
Use grouped-by monitoring for dimension-specific needs
Alert Management:
Higher frequency = more potential alerts
Ensure alert channels can handle volume
Consider incident severity levels appropriately
Related Topics
Available Monitor ModesIncident model feedbackNeed Help? Contact [email protected] for guidance on optimal scheduling strategies for your specific data architecture.
Last updated