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- Operation Guide
- Resource Management
- Permission Management
- Log Collection
- 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
- Uploading Log via SDK
- Uploading Log via API
- Importing Data
- Tencent Cloud Service Log Access
- Metric Collection
- Log Storage
- Metric Storage
- Search and Analysis (Log Topic)
- Syntax and Rules
- Statistical Analysis (SQL)
- 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
- 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
- Historical Documentation
- Practical Tutorial
- Developer Guide
- API Documentation
- History
- Introduction
- API Category
- Making API Requests
- 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
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- 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
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- Glossary
A trigger condition expression is used to determine whether to trigger an alarm. The query analysis result of the monitoring object is input as a variable for the trigger expression. If the expression is true, an alarm will be triggered.
Syntax Description
Operator | Description | Example |
$N.keyname | Imports the query analysis result. N is the monitoring object number, keyname is the field name in the query analysis result (which must start with a letter and can contain letters, digits, and underscores. We recommend you use the AS syntax to set an alias for the result.) | $1.ErrCount |
+ | Addition operator | $1.ErrCount+$1.FatCount>10 |
- | Subtraction operator | $1.Count-$1.InfoCount>100 |
* | Multiplication operator | $1.RequestMilSec*1000>10 |
/ | Division operator | $1.RequestSec/1000>0.01 |
% | Modulo operator | $1.keyA%10==0 |
== | Comparison operator: equal to | $1.ErrCount==100 $1.level=="Error" |
> | Comparison operator: greater than | $1.ErrCount>100 |
< | Comparison operator: less than | $1.pv<100 |
>= | Comparison operator: greater than or equal to | $1.ErrCount>=100 |
<= | Comparison operator: less than or equal to | $1.pv<=100 |
!= | Comparison operator: not equal to | $1.level!="Info" |
() | Parentheses for controlling the operation priority | ($1.a+$1.b)/$1.c>100 |
&& | Logical operator: AND | $1.ErrCount>100 && $1.level=="Error" |
|| | Logical operator: OR | $1.ErrCount>100 || $1.level=="Error" |
An alarm will be triggered only if the expression is true. For example, if the calculation result of
$1.a+$1.b is 100, no alarms will be triggered; if the result is greater than or equal to 100, an alarm will be triggered.keyname in $N.keyname is the field name of the query analysis result. It must start with a letter and can contain letters, digits, and underscores, such as level:error | select count(*) AS errCount. errCount can be directly used as keyname in the trigger condition expression. If the field name contains special symbols, you need to enclose the imported variable with [], such as [$1.count(*)]. We recommend you use an AS analysis statement to set an alias for the result field name.Up to three monitoring objects can be set in an alarm policy. Each one is identified by a number starting from 1. For example,
$1.key1 imports the key1 field name in the query whose number is 1, and $2.key2 imports the key2 field name in the query whose number is 2.If multiple values are returned in the query analysis result, the expression will be calculated according to the values for up to 1,000 times or until the calculation result is
true. For example, if the expression is $1.a+$2.b>100, analysis 1 returns m results, and analysis 2 returns n results, then the expression will be calculated for m * n times, and calculation will stop when $1.a+$2.b>100 is true or after 1,000 times of calculation.
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