Tencent Cloud CVM¶
Use the "Cloud Sync" series of script packages in the script market to sync cloud monitoring and cloud asset data to Guance
Configuration¶
Install Func¶
It is recommended to activate Guance Integration - Extensions - DataFlux Func (Automata): All prerequisites are automatically installed, please proceed with the script installation.
If deploying Func manually, refer to Manual Func Deployment
Activate Script¶
Note: Please prepare the required Tencent Cloud AK in advance (for simplicity, you can directly grant the global read-only permission
ReadOnlyAccess)
Activate Script in Automata¶
- Log in to the Guance console.
- Click the [Integration] menu and select [Cloud Account Management].
- Click [Add Cloud Account], select [Tencent Cloud], and fill in the required information on the interface. If you have already configured the cloud account information before, you can skip this step.
- Click [Test], and if the test is successful, click [Save]. If the test fails, please check if the relevant configuration information is correct and test again.
- Click [Cloud Account Management] to see the added cloud account in the list, click the corresponding cloud account to enter the details page.
- Click the [Integration] button on the cloud account details page, find
Tencent Cloud CVMunder theNot Installedlist, and click the [Install] button to pop up the installation interface for installation.
Manually Activate Script¶
-
Log in to the Func console, click [Script Market], enter the Guance script market, and search for
integration_tencentcloud_cvm. -
Click [Install], then enter the corresponding parameters: Tencent Cloud AK, SK, and account name.
-
Click [Deploy Startup Script], the system will automatically create the
Startupscript set and automatically configure the corresponding startup script. -
After enabling, you can see the corresponding automatic trigger configuration in "Management / Automatic Trigger Configuration". Click [Execute] to execute it immediately without waiting for the scheduled time. Wait a moment, you can view the execution task records and corresponding logs.
Verification¶
- In "Management / Automatic Trigger Configuration", confirm whether the corresponding task has the corresponding automatic trigger configuration, and you can also check the corresponding task records and logs to check for any abnormalities.
- In Guance, check if there is asset information in "Infrastructure / Custom".
- In Guance, check if there is corresponding monitoring data in "Metrics".
Metrics¶
After configuring Tencent Cloud Cloud Monitoring, the default measurement is as follows. You can collect more metrics by configuring Tencent Cloud Cloud Monitoring Metrics Details
CPU Monitoring¶
| Metric Name | Metric Chinese Name | Description | Unit | Dimension | Statistics Granularity |
|---|---|---|---|---|---|
CpuUsage |
CPU Utilization | Real-time CPU percentage occupied during machine operation | % | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
CpuLoadavg |
CPU One-minute Average Load | Average number of tasks using and waiting to use CPU in 1 minute (This metric is not available for Windows machines) | - | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
Cpuloadavg5m |
CPU Five-minute Average Load | Average number of tasks using and waiting to use CPU in 5 minutes (This metric is not available for Windows machines) | - | InstanceId |
60s, 300s, 3600s |
Cpuloadavg15m |
CPU Fifteen-minute Average Load | Average number of tasks using and waiting to use CPU in 15 minutes (This metric is not available for Windows machines) | - | InstanceId |
60s, 300s, 3600s |
BaseCpuUsage |
Base CPU Utilization | Base CPU utilization is collected and reported by the host machine, allowing data to be viewed without installing monitoring components, and data can still be collected and reported when the virtual machine is under high load | % | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
GPU Monitoring¶
| Metric Name | Metric Chinese Name | Description | Unit | Dimension | Statistics Granularity |
|---|---|---|---|---|---|
GpuMemTotal |
GPU Memory Total | GPU Memory Total | MB | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
GpuMemUsage |
GPU Memory Utilization | GPU Memory Utilization | % | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
GpuMemUsed |
GPU Memory Usage | Evaluate the load on GPU memory | MB | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
GpuPowDraw |
GPU Power Usage | GPU Power Usage | W | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
GpuPowLimit |
GPU Power Total | GPU Power Total | W | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
GpuPowUsage |
GPU Power Utilization | GPU Power Utilization | % | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
GpuTemp |
GPU Temperature | Evaluate GPU cooling status | °C | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
GpuUtil |
GPU Utilization | Evaluate the computing power consumed by the load, the percentage of non-idle state | % | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
Network Monitoring¶
| Metric Name | Metric Chinese Name | Description | Unit | Dimension | Statistics Granularity |
|---|---|---|---|---|---|
LanOuttraffic |
Internal Network Outbound Bandwidth | Average outbound traffic per second of the internal network card | Mbps | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
LanIntraffic |
Internal Network Inbound Bandwidth | Average inbound traffic per second of the internal network card | Mbps | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
LanOutpkg |
Internal Network Outbound Packet Count | Average outbound packet count per second of the internal network card | packets/sec | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
LanInpkg |
Internal Network Inbound Packet Count | Average inbound packet count per second of the internal network card | packets/sec | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
WanOuttraffic |
External Network Outbound Bandwidth | Average outbound traffic rate per second of the external network, the minimum granularity data is calculated as the total outbound traffic in 10 seconds divided by 10 seconds, this data is the sum of the outbound/inbound bandwidth of EIP+CLB+CVM | Mbps | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
WanIntraffic |
External Network Inbound Bandwidth | Average inbound traffic rate per second of the external network, the minimum granularity data is calculated as the total inbound traffic in 10 seconds divided by 10 seconds, this data is the sum of the outbound/inbound bandwidth of EIP+CLB+CVM | Mbps | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
WanOutpkg |
External Network Outbound Packet Count | Average outbound packet count per second of the external network card | packets/sec | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
WanInpkg |
External Network Inbound Packet Count | Average inbound packet count per second of the external network card | packets/sec | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
AccOuttraffic |
External Network Outbound Traffic | Average outbound traffic per second of the external network card | MB | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
TcpCurrEstab |
TCP Connection Count | Number of TCP connections in ESTABLISHED state | count | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
TimeOffset |
UTC Time and NTP Time Difference of the Virtual Machine | UTC time and NTP time difference of the virtual machine | seconds | InstanceId |
60s, 300s, 3600s, 86400s |
Memory Monitoring¶
| Metric Name | Metric Chinese Name | Description | Unit | Dimension | Statistics Granularity |
|---|---|---|---|---|---|
MemUsed |
Memory Usage | Actual memory used by the user, excluding memory occupied by buffers and system cache, total memory - available memory (including buffers and cached) to get the memory usage value, excluding buffers and cached | MB | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
MemUsage |
Memory Utilization | Actual memory utilization by the user, excluding memory occupied by buffers and system cache, excluding cache, buffer and remaining, the ratio of actual memory used by the user to total memory | % | InstanceId |
10s, 60s, 300s, 3600s, 86400s |
Disk Monitoring¶
| Metric Name | Metric Chinese Name | Description | Unit | Dimension | Statistics Granularity |
|---|---|---|---|---|---|
CvmDiskUsage |
Disk Utilization | Percentage of disk used capacity to total capacity (all disks) | % | InstanceId |
60s, 300s |
RDMA Monitoring¶
| Metric Name | Metric Chinese Name | Description (Optional) | Unit | Dimension | Statistics Granularity |
|---|---|---|---|---|---|
RdmaIntraffic |
RDMA Network Card Receive Bandwidth | RDMA Network Card Receive Bandwidth | Mbps | InstanceId |
60s, 300s, 3600s, 86400s |
RdmaOuttraffic |
RDMA Network Card Send Bandwidth | RDMA Network Card Send Bandwidth | Mbps | InstanceId |
60s, 300s, 3600s, 86400s |
RdmaInpkt |
RDMA Network Card Inbound Packet Count | RDMA Network Card Inbound Packet Count | packets/sec | InstanceId |
60s, 300s, 3600s, 86400s |
RdmaOutpkt |
RDMA Network Card Outbound Packet Count | RDMA Network Card Outbound Packet Count | packets/sec | InstanceId |
60s, 300s, 3600s, 86400s |
CnpCount |
CNP Statistics | Congestion Notification Packet Statistics | packets/sec | InstanceId |
60s, 300s, 3600s, 86400s |
EcnCount |
ECN Statistics | Explicit Congestion Notification Statistics | packets/sec | InstanceId |
60s, 300s, 3600s, 86400s |
RdmaPktDiscard |
End-to-end Packet Loss | End-to-end Packet Loss | packets/sec | InstanceId |
60s, 300s, 3600s, 86400s |
RdmaOutOfSequence |
Receiver Out-of-order Error Count | Receiver Out-of-order Error Count | packets/sec | InstanceId |
60s, 300s, 3600s, 86400s |
RdmaTimeoutCount |
Sender Timeout Error Count | Sender Timeout Error Count | packets/sec | InstanceId |
60s, 300s, 3600s, 86400s |
TxPfcCount |
TX PFC Statistics | TX PFC Statistics | packets/sec | InstanceId |
60s, 300s, 3600s, 86400s |
RxPfcCount |
RX PFC Statistics | RX PFC Statistics | packets/sec | InstanceId |
60s, 300s, 3600s, 86400s |
Object¶
The collected Tencent Cloud CVM object data structure can be seen in "Infrastructure - Custom".
{
"measurement": "tencentcloud_cvm",
"tags": {
"name" : "ins-bahxxxx",
"RegionId" : "ap-shanghai",
"Zone" : "ap-shanghai-1",
"InstanceId" : "ins-bahxxxx",
"InstanceChargeType": "POSTPAID_BY_HOUR",
"InstanceType" : "SA2.MEDIUM2",
"OsName" : "TencentOS Server 3.1 (TK4)"
},
"fields": {
"CPU" : 2,
"Memory" : 2,
"InstanceState" : "RUNNING",
"PublicIpAddresses" : "{Public IP Data}",
"PrivateIpAddresses": "{Private IP Data}",
"SystemDisk" : "{System Disk JSON Data}",
"DataDisks" : "{Data Disk JSON Data}",
"Placement" : "{Region JSON Data}",
"ExpiredTime" : "2022-05-07T01:51:38Z",
"message" : "{Instance JSON Data}"
}
}