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- Collection Overview
- Collecting Logs in Self-Built Kubernetes Cluster
- 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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- Uploading Log via API
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- Metric Collection
- Log Storage
- Metric Storage
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- 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
- Context Search and Analysis
- Downloading Log
- Search and Analysis (Metric Topic)
- Dashboard
- Data Processing documents
- Data Processing
- 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
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- Practical Tutorial
- Developer Guide
- API Documentation
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- Topic Management APIs
- 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
- Scheduled SQL Analysis APIs
- COS Data Import Task APIs
- Data Types
- Error Codes
- FAQs
- CLS Service Level Agreement
- CLS Policy
- Contact Us
- Glossary
Setting Alarm Trigger Conditions by Time Period
Terakhir diperbarui: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.
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