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Database Rule Trigger Configuration Guide

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Rule Setup Flow

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1. DB Instances (Required First Step)

• Select All: Choose all available instances at once
• Individual Selection: Pick specific instances
• Impact: Your selection here determines what databases and users appear in trigger dropdowns later

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2. Triggers (Up to 3 Maximum)

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Trigger Type (Required)

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Connection idle time

• Greater Than: Trigger when idle time exceeds value
• Less Than: Trigger when idle time is below value

• Free up memory from abandoned connections
• Prevent connection pool exhaustion
• Clean up development/test connections

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Connection utilization

• Greater Than: Trigger when usage exceeds percentage
• Less Than: Trigger when usage falls below percentage

• Prevent “too many connections” errors
• Proactive connection pool management
• Emergency connection cleanup during high load

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Query duration

• Greater Than: Trigger when runtime exceeds duration
• Less Than: Trigger when runtime is below duration

• Stop running queries that slow the database
• Enforce query timeout policies
• Performance protection

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Query pattern

• The system is case-insensitive and automatically removes semicolons before matching
• Use % wildcard to represent any content: select % from table_name
• Patterns must match query structure exactly (except case and semicolons)
• ⚠️ Critical: Rule will NOT work with different spacing/formatting such as extra spaces or different line breaks

• Like: Trigger when queries match any pattern
• Not Like: Trigger when queries don’t match any pattern

• Security: Like: %DROP TABLE% - Block destructive operations
• Performance: Not Like: %limit% - Block inefficient queries
• Compliance: Like: %SELECT * FROM salary% - Monitor sensitive data access

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Complex Pattern Examples

SELECT e.lastName, e.firstName, p.amount,pg_sleep(%)  FROM employees e JOIN customers c ON e.employeeNumber = c.salesRepEmployeeNumber JOIN payments p ON c.customerNumber = p.customerNumber WHERE p.amount < 1000 limit 1;

select e.lastname, e.firstname, p.amount,pg_sleep(10)  from employees e join customers c on e.employeenumber = c.salesrepemployeenumber join payments p on c.customernumber = p.customernumber where p.amount < 1000 limit 1;

SELECT e.lastName,    e.firstName  , p.amount,   pg_sleep(10)  FROM employees e JOIN customers c ON e.employeeNumber = c.salesRepEmployeeNumber JOIN payments p ON c.customerNumber = p.customerNumber WHERE p.amount < 1000 limit 1;

select e.lastname, e.firstname, p.amount,pg_sleep(10)
from employees e join customers c on e.employeenumber = c.salesrepemployeenumber
join payments p on c.customernumber = p.customernumber
where p.amount < 1000 limit 1;

-- ORIGINAL QUERY
SELECT 
    c.[customer_id],
    c.[first_name] + ' ' + c.[last_name] AS [full_name],
    cat.[category_name],
    p.[product_name],
    p.[price],
    oi.[quantity],
    (oi.[quantity] * p.[price]) AS [line_total],
    o.[order_date],
    r.[rating],
    r.[review_text],
    CASE 
        WHEN r.[rating] >= 4 THEN 'Positive'
        WHEN r.[rating] = 3 THEN 'Neutral'
        ELSE 'Negative'
    END AS [review_sentiment]
FROM [customers] c
INNER JOIN [orders] o ON c.[customer_id] = o.[customer_id]
INNER JOIN [order_items] oi ON o.[order_id] = oi.[order_id]
INNER JOIN [products] p ON oi.[product_id] = p.[product_id]
LEFT JOIN [categories] cat ON p.[category_id] = cat.[category_id]
LEFT JOIN [reviews] r ON p.[product_id] = r.[product_id] 
    AND c.[customer_id] = r.[customer_id]
WHERE o.[order_date] >= '2023-01-01'
    AND p.[price] > 50.00
    AND c.[country] IN ('USA', 'Canada', 'UK')

SELECT 
    c.[customer_id],
    c.[first_name] + ' ' + c.[last_name] AS [full_name],
    cat.[category_name],
    p.[product_name],
    p.[price],
    oi.[quantity],
    (oi.[quantity] * p.[price]) AS [line_total],
    o.[order_date],
    r.[rating],
    r.[review_text],
    CASE 
        WHEN r.[rating] >= 4 THEN 'Positive'
        WHEN r.[rating] = 3 THEN 'Neutral'
        ELSE 'Negative'
    END AS [review_sentiment]
FROM [customers] c
INNER JOIN [orders] o ON c.[customer_id] = o.[customer_id]
INNER JOIN [order_items] oi ON o.[order_id] = oi.[order_id]
INNER JOIN [products] p ON oi.[product_id] = p.[product_id]
LEFT JOIN [categories] cat ON p.[category_id] = cat.[category_id]
LEFT JOIN [reviews] r ON p.[product_id] = r.[product_id] 
    AND c.[customer_id] = r.[customer_id]
WHERE o.[order_date] >= %
    AND p.[price] > %
    AND c.[country] IN (%)

• Exact line break formatting preserved between original and pattern
• Multiple wildcards (%) used for flexible matching on dates, prices, and countries
• Comments preserved to maintain exact structure
• All spacing and indentation must match exactly

• Original query (with line breaks): Won’t match a single-line pattern
• Rule pattern (single line): Won’t catch queries that have line breaks
• Solution: Pattern formatting must match the actual query formatting exactly

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Best Practices for Copy-Paste Query Patterns

• Copy query from Rapydo Application (Query workspace | Dashboard slowest reports)
• Copy from Query Logs/Monitoring:
  • Database query logs
  • Application logs
  • Query monitoring tools (Rapydo)
  • Database audit trails

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DB name

• Search Function: Find specific databases quickly
• Select All: Choose all databases that are in the dropdown

• In: Trigger for activity on specified databases
• Not In: Trigger for activity NOT on specified databases

• Production protection: In “production_db” - Apply strict rules to production
• Development monitoring: Not In “dev_db,test_db” - Monitor non-dev access

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User

• Search Function: Find specific users quickly
• Select All: Choose all users that are in the dropdown
• Shared Indicators: Shows users shared across instances

• In: Trigger for processes from specified users
• Not In: Trigger for processes NOT from specified users

• Admin monitoring: In “admin,dba,root” - Enhanced monitoring for privileged users
• Service account limits: In “app_user,backup_user” - Control service account activity

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Ip

• In: Trigger for processes from specified IPs
• Not In: Trigger for processes NOT from specified IPs

• Security monitoring: In “192.168.1.100” - Watch specific suspicious IP
• External access: Not In “10.0.0.0/8” - Monitor external connections
• Office restriction: In “203.0.113.0/24” - Limit to office network

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Custom script

• Complex business rules requiring multiple conditions
• Integration with external monitoring systems
• Custom performance metrics
• Time-based rules (business hours, maintenance windows)

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3. Actions

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Connection Management

• Kill connection: Terminate the specific connections matching the trigger criteria. Uses pg_terminate_backend for PostgreSQL and CALL mysql.rds_kill for MySQL.
• Kill idle connections: Terminate idle connections when connection utilization exceeds threshold. Includes rate limit per cycle.
• Kill query: Difference from Kill Connection: Terminates only the running query, keeps the connection alive. Uses pg_cancel_backend for PostgreSQL and CALL mysql.rds_kill_query for MySQL.

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Traffic Control

• Rate limit: Limit the amount of concurrent operations for matching the trigger criteria
• No action: Monitor only (log events & email - without taking action)

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Analysis

• RCA: Analyzes slow queries and provides root cause analysis by email.
• Custom script: SQL statement(s) executed when rule triggers

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4. Notifications

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Multiple Trigger Logic (Important)

• Trigger 1: Connection idle time > 300 seconds
• Trigger 2: User In “test_user,dev_user”
• Trigger 3: IP In “192.168.1.100”