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- Collection Overview
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- Collecting Syslog
- Collection by LogListener
- Collecting Text Log
- Uploading Log over Kafka
- Uploading Logs via Anonymous Write
- Uploading Logs via Logback Appender
- Uploading Logs via Log4j Appender
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- Log Storage
- Metric Storage
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- Quick Analysis
- SQL Syntax
- SQL Functions
- String Function
- Date and Time Functions
- IP Geographic Function
- URL Function
- Mathematical Calculation Functions
- Mathematical Statistical Function
- General Aggregate Function
- Geospatial Function
- Binary String Function
- Estimation Function
- Type Conversion Function
- Logical Function
- Operators
- Bitwise Operation
- Regular Expression Function
- Lambda Function
- Conditional Expressions
- Array Functions
- Interval-Valued Comparison and Periodicity-Valued Comparison Functions
- JSON Functions
- Window Functions
- Sampling Analysis
- Configuring Indexes
- Reindexing
- Multi-Topic Search
- Context Search and Analysis
- Custom Redirect
- Downloading Log
- Search and Analysis (Metric Topic)
- Dashboard
- Data Processing documents
- Data Processing
- Data Processing Overview
- Creating Processing Task
- Viewing Data Processing Details
- Data Processing Functions
- Function Overview
- Key-Value Extraction Functions
- Enrichment Functions
- Flow Control
- Row Processing Functions
- Field Processing Functions
- Value Structuring Functions
- Regular Expression Processing Functions
- Time Value Processing Functions
- String Processing Functions
- Type Conversion Functions
- Logical and Mathematical Functions
- Encoding and Decoding Functions
- IP Parsing Functions
- Processing Cases
- Scheduled SQL Analysis
- SCF
- Data Processing
- Shipping and Consumption
- Monitoring Alarm
- Historical Documentation
- Practical Tutorial
- Developer Guide
- API Documentation
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- Making API Requests
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- Log Set Management APIs
- Index APIs
- Topic Partition APIs
- Machine Group APIs
- Collection Configuration APIs
- Log APIs
- Metric APIs
- Alarm Policy APIs
- Data Processing APIs
- Kafka Protocol Consumption APIs
- CKafka Shipping Task APIs
- Kafka Data Subscription APIs
- COS Shipping Task APIs
- SCF Delivery Task APIs
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- COS Data Import Task APIs
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Setting Alarm Trigger Conditions by Time Period
Last updated: 2024-01-20 17:28:40
Overview
For business nature reasons, different alarm trigger conditions need to be set for different time periods. For example, an alarm should be triggered when the number of logs containing errors exceeds 100 during work hours (9:00 AM to 6:00 PM) or when this number exceeds 10 during off hours (7:00 PM to 8:00 AM).
Configuration method
Query statement 1:
error | select count(*) as error_count
Count logs containing errors
Query statement 2:
* | select hour(now()) as hour limit 1
Trigger conditions:
($1.error_count>100 && $2.hour>=9 && $2.hour<=18 ) || ($1.error_count>10 && ($2.hour<9 || $2.hour>18))
Use the trigger condition expression to specify a trigger condition and threshold. Here,
$1.error_count>100 && $2.hour>=9 && $2.hour<=18 indicates to trigger an alarm when error_count exceeds 100 between 9:00 AM and 6:00 PM, while $1.error_count>10 && ($2.hour<9 || $2.hour>18) indicates to trigger an alarm when error_count exceeds 10 between 7:00 PM and 8:00 AM.
Yes
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