It is recommended to enable Guance integration - extension - hosted Func: all prerequisites are automatically installed, please continue with the script installation
Note: Please prepare the required Tencent Cloud AK in advance (for simplicity, you can directly grant global read-only permission ReadOnlyAccess)
To synchronize MariaDB monitoring data, we install the corresponding collection script: "Guance integration (Tencent Cloud-MariaDB collection)" (ID: guance_tencentcloud_mariadb)
After clicking 【Install】, enter the corresponding parameters: Tencent Cloud AK, Tencent Cloud account name.
Click 【Deploy startup script】, the system will automatically create a Startup script set and automatically configure the corresponding startup script.
After enabling, you can see the corresponding automatic trigger configuration in "Manage / Automatic trigger configuration". Click 【Execute】 to execute immediately without waiting for the scheduled time. Wait for a moment, and you can view the execution task records and corresponding logs.
If you need to collect the corresponding logs, you also need to enable the corresponding log collection script. If you need to collect billing information, enable the cloud billing collection script.
In "Manage / Automatic trigger configuration", confirm whether the corresponding tasks have the corresponding automatic trigger configuration, and at the same time, check the corresponding task records and logs for any anomalies.
On the Guance platform, under "Infrastructure / Custom", check if there is asset information.
On the Guance platform, under "Metrics", check if there is corresponding monitoring data.
Instance-level monitoring metric, calculated by summing up active thread counts of all shard master-slave nodes
Count
InstanceId
BinlogDiskAvailable
Remaining Binlog Log Disk Space
Instance-level monitoring metric, calculated by summing up the BinlogDiskAvailableShard monitoring values of each shard
GB
InstanceId
BinlogUsedDisk
Used Binlog Log Disk Space
Instance-level monitoring metric, calculated by summing up used Binlog log disk space of the master node of each shard
GB
InstanceId
ConnUsageRate
DB Connection Usage Rate
Instance-level monitoring metric, value taken as the maximum DB connection usage rate of all shard master-slave nodes
%
InstanceId
CpuUsageRate
CPU Usage Rate
Instance-level monitoring metric, value taken as the maximum CPU usage rate of all shard master nodes
%
InstanceId
DataDiskAvailable
Available Data Disk Space
Instance-level monitoring metric, calculated by summing up available data disk space of the master node of each shard
GB
InstanceId
DataDiskUsedRate
Data Disk Space Usage Rate
Instance-level monitoring metric, value taken as the maximum data disk space usage rate of each shard master node
%
InstanceId
DeleteTotal
DELETE Request Count
Instance-level monitoring metric, calculated by summing up DELETE request counts of all shard master nodes
Times/Second
InstanceId
InnodbBufferPoolReads
innodb Disk Read Page Count
Instance-level monitoring metric, calculated by summing up innodb disk read page counts of all shard master-slave nodes
Times
InstanceId
InnodbBufferPoolReadAhead
innodb Buffer Pool Pre-read Page Count
Instance-level monitoring metric, calculated by summing up innodb buffer pool pre-read page counts of all shard master-slave nodes
Times
InstanceId
InnodbBufferPoolReadRequests
innodb Buffer Pool Read Page Count
Instance-level monitoring metric, calculated by summing up innodb buffer pool read page counts of all shard master-slave nodes
Times
InstanceId
InnodbRowsDeleted
innodb Executed DELETE Row Count
Instance-level monitoring metric, calculated by summing up innodb executed DELETE row counts of all shard master nodes
Rows
InstanceId
InnodbRowsInserted
innodb Executed INSERT Row Count
Instance-level monitoring metric, calculated by summing up innodb executed INSERT row counts of all shard master nodes
Rows
InstanceId
InnodbRowsRead
innodb Executed READ Row Count
Instance-level monitoring metric, calculated by summing up innodb executed READ row counts of all shard master-slave nodes
Rows
InstanceId
InnodbRowsUpdated
innodb Executed UPDATE Row Count
Instance-level monitoring metric, calculated by summing up innodb executed UPDATE row counts of all shard master nodes
Rows
InstanceId
InsertTotal
INSERT Request Count
Instance-level monitoring metric, calculated by summing up INSERT request counts of all shard master nodes
Times/Second
InstanceId
LongQueryCount
Slow Query Count
Instance-level monitoring metric, calculated by summing up slow query counts of all shard master nodes
Times
InstanceId
MemAvailable
Available Cache Space
Instance-level monitoring metric, calculated by summing up available cache space of all shard master nodes
GB
InstanceId
MemHitRate
Cache Hit Rate
Instance-level monitoring metric, value taken as the minimum cache hit rate of each shard master node
%
InstanceId
ReplaceSelectTotal
REPLACE_SELECT Request Count
Instance-level monitoring metric, calculated by summing up REPLACE-SELECT request counts of all shard master nodes
Times/Second
InstanceId
ReplaceTotal
REPLACE Request Count
Instance-level monitoring metric, calculated by summing up REPLACE request counts of all shard master nodes
Times/Second
InstanceId
RequestTotal
Total Request Count
Instance-level monitoring metric, calculated by summing up total request counts of all master nodes and SELECT request counts of all slave nodes
Times/Second
InstanceId
SelectTotal
SELECT Request Count
Instance-level monitoring metric, calculated by summing up SELECT request counts of all shard master-slave nodes
Times/Second
InstanceId
SlaveDelay
Slave Delay
Instance-level monitoring metric, first calculate the standby delay of each shard, then take the maximum value as the standby delay of this instance. The standby delay of a shard is the minimum delay of all standby nodes of this shard
Seconds
InstanceId
UpdateTotal
UPDATE Request Count
Instance-level monitoring metric, calculated by summing up UPDATE request counts of all shard master nodes
Times/Second
InstanceId
ThreadsConnected
Current Open Connections
Instance-level monitoring metric, calculated by summing up current open connections of all shard master-slave nodes
Times
InstanceId
ConnMax
Maximum Connections
Instance-level monitoring metric, calculated by summing up maximum connections of all shard master-slave nodes
Count
InstanceId
ClientConnTotal
Total Client Connections
Instance-level monitoring metric, calculated by summing up all connections on the instance Proxy. This metric truly shows how many clients are connected to the database instance
Count
InstanceId
SQLTotal
Total SQL Count
Instance-level monitoring metric, indicates how many SQL statements are sent to the database instance
Statements
InstanceId
ErrorSQLTotal
SQL Error Count
Instance-level monitoring metric, indicates how many SQL statements execute errors
Statements
InstanceId
SuccessSQLTotal
SQL Success Count
Instance-level monitoring metric, indicates the number of successfully executed SQL statements
Count
InstanceId
TimeRange0
Latency (<5ms) Request Count
Instance-level monitoring metric, indicates the number of requests executing less than 5ms
Times/Second
InstanceId
TimeRange1
Latency (5~20ms) Request Count
Instance-level monitoring metric, indicates the number of requests executing between 5-20ms
Times/Second
InstanceId
TimeRange2
Latency (20~30ms) Request Count
Instance-level monitoring metric, indicates the number of requests executing between 20~30ms
Times/Second
InstanceId
TimeRange3
Latency (>30ms) Request Count
Instance-level monitoring metric, indicates the number of requests executing greater than 30ms
Times/Second
InstanceId
MasterSwitchedTotal
Master-Slave Switch Count
Instance-level monitoring metric, indicates the number of times the master-slave switch occurs
Times
InstanceId
IOUsageRate
IO Usage Rate
Instance-level monitoring metric, value taken as the maximum IO usage rate of each shard master node
%
InstanceId
MaxSlaveCpuUsageRate
Maximum Slave Node CPU Usage Rate
Instance-level monitoring metric, value taken as the maximum CPU usage rate of all slave nodes
%
InstanceId
ThreadsRunningCount
Aggregated Running Threads Count
Instance-level monitoring metric, value taken as the sum of Threads_running values of all nodes in the instance. Threads_running is the result obtained by executing show status like 'Threads_running'
The collected Tencent Cloud MariaDB object data structure can be seen in "Infrastructure - Custom"
{"measurement":"tencentcloud_mariadb","tags":{"AppId":"1311xxx185","AutoRenewFlag":"0","DbEngine":"MariaDB","DbVersion":"10.1","DbVersionId":"10.1","InstanceId":"tdsql-ewqokixxxxxhu","InstanceName":"tdsql-ewqoxxxxxxihu","InstanceType":"2","Paymode":"postpaid","ProjectId":"0","RegionId":"ap-shanghai","Status":"0","StatusDesc":"Creating","TdsqlVersion":"Based on MariaDB 10.1 design (compatible with Mysql 5.6)","Uin":"100xxxx113474","Vip":"","Vport":"3306","WanDomain":"","WanPort":"0","WanVip":"","Zone":"ap-shanghai-5","name":"tdsql-ewqokihu","WanVIP":""},"fields":{"Cpu":1,"CreateTime":"2023-08-17 17:55:03","Memory":2,"NodeCount":2,"PeriodEndTime":"0001-01-01 00:00:00","Qps":2100,"Storage":10,"UpdateTime":"2023-08-17 17:55:03","message":"{Instance JSON data}"}}
Note: Fields in tags, fields may change with subsequent updates
Tip 1: tags.name value serves as unique identification
Tip 2: fields.message, fields.InstanceNode are serialized JSON strings