Monitoring Clusters Using Cloud Eye¶
Function¶
This section describes how to check cluster metrics on Cloud Eye. By monitoring cluster running metrics, you can identify the time when the database cluster is abnormal and analyze potential activity problems based on the database logs, improving database performance. This section describes the metrics that can be monitored by Cloud Eye as well as their namespaces and dimensions. You can use the management console or APIs provided by Cloud Eye to query the monitoring metrics and alarms generated by GaussDB(DWS). For details, see the User Guide and API Reference of Cloud Eye.
Namespace¶
SYS.DWS
Cluster Monitoring Metrics¶
With the GaussDB(DWS) monitoring metrics provided by Cloud Eye, you can obtain information about the cluster running status and performance. This information will provide a better understanding of the node-level information.
Table 1 describes GaussDB(DWS) monitoring metrics.
Metric ID | Name | Description | Value Range | Monitored Object | Monitoring Period (Raw Data) |
|---|---|---|---|---|---|
dws001_shared_buffer_hit_ratio | Cache Hit Ratio | Ratio of requested data that already exists in the cache. It the ratio of the amount of data that already exists in the cache to the total amount of requested data. A higher cache hit ratio means higher cache usage of the system, fewer times that data needs to be read from the disk or network, and faster system response speed. Unit: Percent | 0% to 100% | Data warehouse cluster | 4 minutes |
dws002_in_memory_sort_ratio | In-memory Sort Ratio | Ratio of the extra memory space used by the sorting algorithm to the memory space occupied by the sorted data. In a merge sort, for example, the size of the merge buffer is often proportional to the size of the sorted data, so the in-memory ratio is usually between 10% and 50%. Unit: Percent | 0% to 100% | Data warehouse cluster | 4 minutes |
dws003_physical_reads | File Reads | Total number of database file reads | > 0 | Data warehouse cluster | 4 minutes |
dws004_physical_writes | File Writes | Total number of database file writes | > 0 | Data warehouse cluster | 4 minutes |
dws005_physical_reads_per_second | File Reads per Second | Number of database file reads per second | >= 0 | Data warehouse cluster | 4 minutes |
dws006_physical_writes_per_second | File Writes per Second | Number of database file writes per second | >= 0 | Data warehouse cluster | 4 minutes |
dws007_db_size | Data Volume | Total size of data in the database, in MB | >= 0 MB | Data warehouse cluster | 4 minutes |
dws008_active_sql_count | Active SQL Count | Number of active SQLs in the database | >= 0 | Data warehouse cluster | 4 minutes |
dws009_session_count | Session Count | Number of sessions that access the database | >= 0 | Data warehouse cluster | 4 minutes |
dws010_cpu_usage | CPU Usage | CPU usage of each node in a cluster, in percentage | 0% to 100% | Data warehouse node | 1 minute |
dws011_mem_usage | Memory Usage | Memory usage of each node in a cluster, in percentage Note After the console is upgraded to 8.3.0.202, the memory usage includes the memory occupied by the cache. Therefore, the value of this metric increases compared with that before the upgrade. | 0% to 100% | Data warehouse node | 1 minute |
dws012_iops | IOPS | Number of I/O requests processed by each node in the cluster per second | >= 0 | Data warehouse node | 1 minute |
dws013_bytes_in | Network Input Throughput | Data input to each node in the cluster per second over the network Unit: byte/s | >= 0 bytes/s | Data warehouse node | 1 minute |
dws014_bytes_out | Network Output Throughput | Data sent to the network per second from each node in the cluster Unit: byte/s | >= 0 bytes/s | Data warehouse node | 1 minute |
dws015_disk_usage | Disk Usage | Disk usage of each node in a cluster, in percentage | 0% to 100% | Data warehouse node | 1 minute |
dws016_disk_total_size | Total Disk Size | Total disk space of each node in the cluster Unit: GB | 100 to 2000 GB | Data warehouse node | 1 minute |
dws017_disk_used_size | Used Disk Space | Used disk space of each node in the cluster Unit: GB | 0 to 3600 GB | Data warehouse node | 1 minute |
dws018_disk_read_throughput | Disk Read Throughput | Data volume read from each disk in the cluster per second Unit: byte/s | >= 0 bytes/s | Data warehouse node | 1 minute |
dws019_disk_write_throughput | Disk Write Throughput | Data volume written to each disk in the cluster per second Unit: byte/s | >= 0 bytes/s | Data warehouse node | 1 minute |
dws020_avg_disk_sec_per_read | Average Time per Disk Read | Average time used each time when a disk reads data Unit: second | > 0s | Data warehouse node | 1 minute |
dws021_avg_disk_sec_per_write | Average Time per Disk Write | Average time used each time when data is written to a disk Unit: second | > 0s | Data warehouse node | 1 minute |
dws022_avg_disk_queue_length | Average Disk Queue Length | Average I/O queue length of a disk | >= 0 | Data warehouse node | 1 minute |
dws_024_dn_diskio_util | DN I/O usage | Average disk I/O usage of DNs in a cluster | 0% to 100% | Data warehouse instance | 1 minute |
Dimensions¶
Key | Value |
|---|---|
datastore_id | Data warehouse cluster ID |
dws_instance_id | Data warehouse node ID |
Cluster and Node Monitoring Information¶
Log in to the GaussDB(DWS) console and choose Clusters > Dedicated Clusters.
View the cluster information. In the cluster list, click View Metric in the Operation column where a specific cluster resides. The Cloud Eye management console is displayed. By default, the cluster monitoring information on the Cloud Eye management console is displayed.
Additionally, you can specify a specific monitoring metric and the time range to view the performance curve.
Comparing the Monitoring Metrics of Multiple Nodes¶
In the navigation pane of the Cloud Eye management console, choose Dashboards > My Dashboards. Click the name of the dashboard for which you want to add a graph. On the My Dashboards page that is displayed, click Add Graph.
On the Add Graph page, you can select Line Chart or Bar Chart to display the graph. After confirming that the information is correct, click OK.
For example, select Line Chart and One View for Multiple Metrics to compare the CPU usage of three GaussDB(DWS) nodes. The following table describes the parameters.
Table 2 Configuration example¶ Parameter
Example Value
Resource Type
DWS
Dimension
Data Warehouse Node
Monitored Object
dws-demo-dws-cn-cn-2-1
dws-demo-dws-cn-cn-1-1
dws-demo-dws-dn-1-1
Metric
CPU Usage
Click OK.
On the selected My Dashboards page, you can view the metric trend on the newly added monitoring graph. You can click the zoom in button to zoom in and view detailed metric comparison data.
Creating Alarm Rules¶
GaussDB(DWS) enables you to customize alarm rules for monitoring specific objects and notification policies, ensuring you stay informed about its running status in a timely manner.
A GaussDB(DWS) alarm rule includes the alarm rule name, monitored object, metric, threshold, monitoring interval, and whether to send a notification. This section describes how to set GaussDB(DWS) alarm rules.
Log in to the GaussDB(DWS) console.
In the navigation pane, choose Clusters > Dedicated Clusters.
Locate the row containing the target cluster, click View Metric in the Operation column to enter the Cloud Eye management console and view the GaussDB(DWS) monitoring information.
The status of the target cluster must be Available. Otherwise, you cannot create alarm rules.
In the left navigation pane of the Cloud Eye management console, choose Alarm Management > Alarm Rules.
On the Alarm Rules page, click Create Alarm Rule in the upper right corner.
On the Create Alarm Rule page, set parameters as prompted.
Configure the rule name and description.
Configure the alarm parameters as prompted.
Table 3 Configuring alarm parameters¶ Parameter
Description
Example Value
Resource Type
Name of the cloud service resource for which the alarm rule is configured.
Data Warehouse Service
Dimension
Metric dimension of the alarm rule. You can select Data Warehouse Nodes or Data Warehouses.
Data Warehouse Node
Monitoring Scope
Resource scope to which an alarm rule applies. Select Specific resources and select one or more monitoring objects. For GaussDB(DWS), select the cluster ID or node ID in the dialog box that is displayed.
Specific resources
Trigger Rule
You can select an associated template, use an existing template or create a custom template as required.
Create manually
Template
This parameter is valid only when Use template is selected.
Select the template to be imported. If no alarm template is available, click Create Custom Template to create one that meets your requirements.
-Alarm Policy
This parameter is valid only when Create manually is selected.
Set the policy that triggers an alarm. For example, trigger an alarm if the CPU usage equals to or is greater than 80% for 3 consecutive periods.
Table 1 lists the GaussDB(DWS) monitoring metrics.
-Alarm Severity
Severity of an alarm. Valid values are Critical, Major, Minor, and Informational.
Major
Configure the alarm notification parameters as prompted.
Table 4 Configuring alarm notifications¶ Parameter
Description
Example Value
Alarm Notification
Whether to notify users when alarms are triggered. Notifications can be sent as emails or text messages, or HTTP/HTTPS requests sent to the servers.
You can enable (recommended) or disable Alarm Notification.
Enable
Notification Object
Name of the topic to which the alarm notification is sent.
If you enable Alarm Notification, you need to select a topic. If no desired topics are available, create one first, whereupon the SMN service is invoked. For details about how to create a topic, see the Simple Message Notification User Guide.
For details about how to create a topic, see the Simple Message Notification User Guide.
-Trigger Condition
Condition for triggering the alarm. You can select Generated alarm, Cleared alarm, or both.
-After the configuration is complete, click Next.
After the alarm rule is created, if the metric data reaches the specified threshold, Cloud Eye will immediately inform you that an exception has occurred.