Tencent Cloud MongoDB¶

Use the script packages in the Script Market of the "Guance Cloud Sync" series to synchronize cloud monitoring and cloud asset data to Guance.

Configuration¶

Install Func¶

We recommend enabling the Guance integration - extension - DataFlux Func (Automata): all prerequisites are automatically installed, please proceed with the script installation.

If you deploy Func yourself, refer to Self-deployed Func

Install Script¶

Note: Please prepare a qualified Tencent Cloud AK in advance (for simplicity, you can directly grant global read-only permission ReadOnlyAccess)

To synchronize the monitoring data of MongoDB cloud resources, we install the corresponding collection script: "Guance Integration (Tencent Cloud-MongoDB Collection)" (ID: guance_tencentcloud_mongodb)

After clicking 【Install】, enter the corresponding parameters: Tencent Cloud AK, Tencent Cloud account name.

Click 【Deploy Start Script】, the system will automatically create a Startup script set and automatically configure the corresponding start script.

After enabling, you can see the corresponding automatic trigger configuration in "Manage / Automatic Trigger Configuration". Click 【Execute】to immediately execute it once without waiting for the scheduled time. After a short while, you can view the execution task records and corresponding logs.

By default, we collect some configurations, see the metrics section Customize Cloud Object Metrics

Verification¶

In "Manage / Automatic Trigger Configuration", confirm whether the corresponding task has an automatic trigger configuration, and at the same time, you can 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.

Metrics¶

After configuring Tencent Cloud - Cloud Monitoring, the default metric sets are as follows. You can collect more metrics through configuration Tencent Cloud Cloud Monitoring Metric Details

Request Class¶

Metric English Name	Metric Chinese Name	Meaning	Unit	Dimensions
`Inserts_sum`	Write request count	Number of writes within a unit of time	Times	target (Instance ID)
`Reads_sum`	Read request count	Number of reads within a unit of time	Times	target (Instance ID)
`Updates_sum`	Update request count	Number of updates within a unit of time	Times	target (Instance ID)
`Deletes_sum`	Delete request count	Number of deletes within a unit of time	Times	target (Instance ID)
`Counts_sum`	Count request count	Number of counts within a unit of time	Times	target (Instance ID)
`Success_sum`	Successful request count	Number of successful requests within a unit of time	Times	target (Instance ID)
`Commands_sum`	Command request count	Number of command requests within a unit of time	Times	target (Instance ID)
`Qps_sum`	Requests per second	Operations per second, including CRUD operations	Times/sec	target (Instance ID)
`CountPerSecond_sum`	Counts per second request count	Count requests per second	Times/sec	target (Instance ID)
`DeletePerSecond_sum`	Deletes per second request count	Delete requests per second	Times/sec	target (Instance ID)
`InsertPerSecond_sum`	Inserts per second request count	Insert requests per second	Times/sec	target (Instance ID)
`ReadPerSecond_sum`	Reads per second request count	Read requests per second	Times/sec	target (Instance ID)
`UpdatePerSecond_sum`	Updates per second request count	Update requests per second	Times/sec	target (Instance ID)

Latency Request Class¶

Metric English Name	Metric Chinese Name	Meaning	Unit	Dimensions
`Delay10_sum`	Request count with latency between 10 - 50 milliseconds	Number of successful requests with delay between 10ms - 50ms within a unit of time	Times	target (Instance ID)
`Delay50_sum`	Request count with latency between 50 - 100 milliseconds	Number of successful requests with delay between 50ms - 100ms within a unit of time	Times	target (Instance ID)
`Delay100_sum`	Request count with latency over 100 milliseconds	Number of successful requests with delay over 100ms within a unit of time	Times	target (Instance ID)
`AvgAllRequestDelay_sum`	Average delay of all requests	Average delay of all requests	ms	target (Instance ID)

Connection Class¶

Metric English Name	Metric Chinese Name	Meaning	Unit	Dimensions
`ClusterConn_max`	Cluster connection count	Total cluster connections, referring to the number of connections received by the current cluster proxy	Times	target (Instance ID)
`Connper_max`	Connection usage rate	Proportion of the current cluster's connections to the total cluster connection configuration	%	target (Instance ID)

System Class¶

Metric English Name	Metric Chinese Name	Meaning	Unit	Dimensions
`ClusterDiskusage`	Disk usage rate	Proportion of actual storage space occupied by the cluster to the total capacity configuration	%	target (Instance ID)

Inbound and Outbound Traffic Class¶

Metric English Name	Metric Chinese Name	Meaning	Unit	Dimensions
`ClusterNetin`	Inbound traffic	Cluster network inbound traffic	Bytes	target (Instance ID)
`ClusterNetout`	Outbound traffic	Cluster network outbound traffic	Bytes	target (Instance ID)

MongoDB Replica Set¶

1. System Class¶

Metric English Name	Metric Chinese Name	Meaning	Unit	Dimensions
`ReplicaDiskusage`	Disk usage rate	Replica set capacity usage rate	%	target (Replica Set ID)

2. Master-Slave Class¶

Metric English Name	Metric Chinese Name	Meaning	Unit	Dimensions
`SlaveDelay`	Master-slave delay	Average master-slave delay within a unit of time	Seconds	target (Replica Set ID)
`Oplogreservedtime`	oplog retention time	Difference in time between the last operation and the first operation in the oplog records	Hours	target (Replica Set ID)

3. Cache Class¶

Metric English Name	Metric Chinese Name	Meaning	Unit	Dimensions
`CacheDirty`	Cache dirty data percentage	Percentage of dirty data in the current memory Cache	%	target (Replica Set ID)
`CacheUsed`	Cache usage percentage	Current Cache usage percentage	%	target (Replica Set ID)
`HitRatio`	Cache hit rate	Current Cache hit rate	%	target (Replica Set ID)

Mongo Node¶

1. System Class¶

Metric English Name	Metric Chinese Name	Meaning	Unit	Dimensions
`CpuUsage`	CPU usage	CPU usage	%	target (Node ID)
`MemUsage`	Memory usage	Memory usage	%	target (Node ID)
`NetIn`	Network inbound traffic	Network inbound traffic	MB/s	target (Node ID)
`NetOut`	Network outbound traffic	Network outbound traffic	MB/s	target (Node ID)
`Disk`	Node disk usage	Node disk usage	MB	target (Node ID)
`Conn`	Connection count	Connection count	Times	target (Node ID)
`ActiveSession`	Active session count	Active session count	Times	target (Node ID)
`NodeOplogReservedTime`	Oplog retention duration	Node oplog retention duration	-	target (Node ID)
`NodeHitRatio`	Cache hit rate	Cache hit rate	%	target (Node ID)
`NodeCacheUsed`	Cache usage percentage	Cache usage percentage in total memory	%	target (Node ID)
`NodeSlavedelay`	Master-slave delay	Slave node delay	s	target (Node ID)
`Diskusage`	Node disk usage rate	Node disk usage rate	%	target (Node ID)
`Ioread`	Disk read count	Disk read IOPS	Times/sec	target (Node ID)
`Iowrite`	Disk write count	Disk write IOPS	Times/sec	target (Node ID)
`NodeCacheDirty`	Cache dirty data percentage	Cache dirty data ratio	%	target (Node ID)

2. Read/Write Class¶

Metric English Name	Metric Chinese Name	Meaning	Unit	Dimensions
`Qr`	Read request queue count	Read request queue count	Count	target (Node ID)
`Qw`	Write request queue count	Write request queue count	Count	target (Node ID)
`Ar`	WT engine ActiveRead	Active Read request count	Count	target (Node ID)
`Aw`	WT engine ActiveWrite	Active Write request count	Count	target (Node ID)

3. Latency & Request Class¶

Metric English Name	Metric Chinese Name	Meaning	Unit	Dimensions
`NodeAvgAllRequestDelay`	Average delay of all requests	Node average delay of all requests	ms	target (Node ID)
`NodeDelay100`	Node request count with delay over 100 milliseconds	Node request count with delay over 100 milliseconds	Times	target (Node ID)
`NodeDelay10`	Node request count with delay between 10-50 milliseconds	Node request count with delay between 10-50 milliseconds	Times	target (Node ID)
`NodeDelay50`	Node request count with delay between 50-100 milliseconds	Node request count with delay between 50-100 milliseconds	Times	target (Node ID)
`NodeSuccessPerSecond`	Node request success count per second	Node request success count per second	Times/sec	target (Node ID)
`NodeCountPerSecond`	Node count request count per second	Node count request count per second	Times/sec	target (Node ID)
`NodeDeletePerSecond`	Node delete request count per second	Node delete request count per second	Times/sec	target (Node ID)
`NodeInsertPerSecond`	Node insert request count per second	Node insert request count per second	Times/sec	target (Node ID)
`NodeReadPerSecond`	Node read request count per second	Node read request count per second	Times/sec	target (Node ID)
`NodeUpdatePerSecond`	Node update request count per second	Node update request count per second	Times/sec	target (Node ID)
`SuccessPerSecond`	Total requests	Node request success count per second	Times/sec	target (Node ID)

4. TTL Index Class¶

Metric English Name	Metric Chinese Name	Meaning	Unit	Dimensions
`TtlDeleted`	TTL deleted data count	TTL deleted data count	Count	target (Node ID)
`TtlPass`	TTL operation cycles	TTL operation cycles	Count	target (Node ID)

Objects¶

The structure of Tencent Cloud MongoDB objects collected can be seen from "Infrastructure - Custom".

{
  "measurement": "tencentcloud_mongodb",
  "tags": {
    "ClusterType" : "0",
    "InstanceId"  : "cmxxxx",
    "InstanceName": "test_01",
    "InstanceType": "1",
    "MongoVersion": "MONxxxx",
    "NetType"     : "1",
    "PayMode"     : "0",
    "ProjectId"   : "0",
    "RegionId"    : "ap-nanjing",
    "Status"      : "2",
    "VpcId"       : "vpc-nf6xxxxx",
    "Zone"        : "ap-nanjing-1",
    "name"        : "cmxxxx"
  },
  "fields": {
    "CloneInstances"   : "[]",
    "CreateTime"       : "2022-08-24 13:54:00",
    "DeadLine"         : "2072-08-24 13:54:00",
    "ReadonlyInstances": "[]",
    "RelatedInstance"  : "{Instance JSON data}",
    "ReplicaSets"      : "{Instance JSON data}",
    "StandbyInstances" : "[]",
    "message"          : "{Instance JSON data}",
  }
}

Logs¶

Slow Query Statistics¶

Prerequisites¶

Note 1: The code execution of this script depends on MongoDB instance object collection. If MongoDB custom object collection is not configured, the slow log script cannot collect slow log data.

Install Script¶

On top of the previous setup, you need to install another script corresponding to MongoDB Slow Query Log Collection

In "Manage / Script Market", click and install the corresponding script package:

"Guance Integration (Tencent Cloud-MongoDB Slow Query Log Collection)" (ID: guance_tencentcloud_mongodb_slowlog)

After the data is synchronized normally, you can view the data in the "Logs" section of Guance.

An example of the reported data is as follows:

{
  "measurement": "tencentcloud_mongodb_slow_log",
  "tags": {

  },
  "fields": {
      "Slowlog": "Slow log details",
      "message": "{Instance JSON data}"
  }
}

Note: Fields in tags, fields may change with subsequent updates.

Note 1: tags values are supplemented by custom objects.

Note 2: fields.message is a string serialized in JSON format.

Note 3: fields.Slowlog represents each record of all slow query details.

Tencent Cloud MongoDB¶

Configuration¶

Install Func¶

Install Script¶

Verification¶

Metrics¶

Request Class¶

Latency Request Class¶

Connection Class¶

System Class¶

Inbound and Outbound Traffic Class¶

MongoDB Replica Set¶

1. System Class¶

2. Master-Slave Class¶

3. Cache Class¶

Mongo Node¶

1. System Class¶

2. Read/Write Class¶

3. Latency & Request Class¶

4. TTL Index Class¶

Objects¶

Logs¶

Slow Query Statistics¶

Prerequisites¶

Install Script¶

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