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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.