Studio Connect Monitoring Guide
Introduction
As of SingleStore Studio 3.1.0 and SingleStore DB 7.3, your SingleStore Studio instance can be connected to your cluster’s monitoring data from SingleStore DB’s monitoring solution. Throughout this guide, the “Source” cluster is the cluster that you are monitoring, and the “Metrics” cluster (or database) is the cluster or database that monitoring data is stored for a given Source cluster.
This functionality allows you to surface your time-series monitoring data directly in Studio. This guide will walk you through creating the connection between a Studio instance and your SingleStore DB metrics
database.
When you connect to a cluster with Studio, you are providing information about where your cluster is located. We’ve introduced additional configuration to make Studio aware of the metrics
database that holds monitoring data associated with your cluster.
Without this new configuration, Studio surfaces the UI that allows users to record and collect their query resource usage over a given period. You can now use this new feature to configure Studio to connect to a data source that holds your monitoring data. Instead of seeing the recording option, you will see the last hour of your query resource usage data by default. Also, you will have the opportunity to change the period of data that the interface surfaces.
If you don’t have a metrics
database, you may continue to use the default recording interface. However, historical information is valuable for understanding your cluster’s state, and we recommend that you follow this guide to set up SingleStore DB’s monitoring solution.
Requirements
Studio 3.1.0 or later
SingleStore DB 7.3 or later for the Source cluster
Local or remote database that’s monitoring a Source (
metrics
by default)
Studio Dashboards and Historical Data
The following Studio dashboards support displaying data from a metrics
database.
Resource Usage Monitoring
The Activity Resource Usage
dashboard, when configured, allows you to view and investigate the query history on your cluster and the respective resource usage of each query. This dashboard is useful for analyzing workload performance, as well as troubleshooting query issues.