[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["難以理解","hardToUnderstand","thumb-down"],["資訊或程式碼範例有誤","incorrectInformationOrSampleCode","thumb-down"],["缺少我需要的資訊/範例","missingTheInformationSamplesINeed","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間：2025-08-28 (世界標準時間)。"],[],[],null,["# Dashboards overview\n\nThis document helps you choose when to use predefined dashboards and when\nto create dashboards. This document also lists techniques that you can use\nto avoid dashboard designs that can result in performance issues.\n\nChoose Google Cloud, third-party, or custom dashboards\n------------------------------------------------------\n\nCloud Monitoring automatically installs a dashboard when you create a resource\nin a Google Cloud project. These dashboards display metrics and general information\nabout a single Google Cloud service. For example,\nif you add Compute Engine instances to your Google Cloud project, then\nMonitoring installs a dashboard named **VM Instances** in your\nGoogle Cloud project. You can't modify or copy these service-specific\ndashboards. However, you can copy charts from these dashboards to\nyour custom dashboards.\nFor more information, see\n[View and customize Google Cloud dashboards](/monitoring/charts/predefined-dashboards).\n\nCloud Monitoring automatically installs a dashboard when you configure\na supported third-party application and that application sends metric data to\nyour Google Cloud project. These dashboards display metrics and general information\nabout a single third-party application. You can find the list of supported\nthird-party applications on the **Integrations** page.\nYou can copy these dashboards and then edit the copy, and you\ncan copy charts on these dashboards to custom dashboards.\nFor more information, see [Manage integrations](/monitoring/agent/integrations).\n\nCustom dashboards are dashboards that you [create](/monitoring/charts/dashboards),\n[copy from one project to another](/monitoring/charts/dashboards#copy-dashboard),\n[install from a shared location](/monitoring/dashboards/dashboard-templates), or\n[import Grafana dashboards into Cloud Monitoring](/monitoring/dashboards/import-grafana-dashboards).\nUnlike dashboards for Google Cloud services and\nthose for your supported integrations,\ncustom dashboards let you view and analyze data from different sources in the\nsame context.\nFor example, you can create a dashboard that displays metric data, alerting\npolicies, and log data.\n\nWhen troubleshooting, you might want to use\n[permanent filters](/monitoring/dashboards/filter-permanent) that apply to some\nor all items on a custom dashboard. Or, you might want to\n[share a dashboard](/monitoring/charts/share-dashboards) with other people\nor groups in your organization.\n\nTo create custom dashboards, you\ncan use the Google Cloud console, the Google Cloud CLI, or the Cloud Monitoring API.\nFor more information, see\n[Create and manage dashboards](/monitoring/charts/dashboards) and\n[Create and manage dashboards by API](/monitoring/dashboards/api-dashboard).\n\nChoose the right widgets for your dashboard\n-------------------------------------------\n\nWhen creating a custom dashboard, consider what kind\nof information that you want to view and how best to display that data.\nIn addition to [displaying metric data](/monitoring/charts), dashboards can\n[display incidents and charts for alerting policies](/monitoring/dashboards/alerts-and-incidents),\n[show log entries](/monitoring/charts/view-logs), and\n[include descriptive text](/monitoring/dashboards/text-and-grouping).\nWhen displaying metric data, you can\nview that data over a time interval or show only the most recent values.\n\nTo facilitate debugging, pair charts with tables. Charts display data\nover a time interval, so you can view historical behavior and identify\nanomalies. When you spot an anomaly on a chart, you can switch to the table\nview and then sort and filter the table to find values for specific time series.\nFor example, you might modify the table to show values only for a particular\ndisk or for instances located in a specific zone.\n\nTo simplify management of your dashboard content, place related charts and\ntables in a collapsible group. Groups have collapsed and expanded\nmodes, and they let you manage what they contain as a collection.\n\nIndicators show only the most recent value. Indicators are useful when you don't\nwant to be notified that a single value is outside a desired operational range,\nbut you do want a visual indication. The background color of an indicator\nchanges based on how the measured value compares to the thresholds you select.\nYou can create an alerting policy to notify you when all values recorded over\na time interval are outside the desired range.\n\n### Charts that show data over time\n\nTo view time series data over a time interval, add one of the following\ntypes to your dashboard:\n\n- Line chart\n- Stacked-area chart\n- Stacked-bar chart\n- Heatmap chart\n\nThe following screenshot is an example of a line chart in color mode:\n\nTo display your time series with the highest possible resolution, use a line\nchart or a stacked-area chart. Choose a stacked-area chart when you want to\nview the sum of the time series, in addition to the contribution of each\ntime series to the total. You can configure these\ncharts to show only outliers, to compare current to past data, or to\ndisplay statistical measures such as the \"50th percentile\". For more\ninformation, see [Set chart display options](/monitoring/charts/chart-view-options).\n\nTo display time series with infrequent samples, such as quota metrics,\nuse stacked-bar charts and\nset the time selector for the dashboard to at least one week.\nFor examples that show how to chart quota metrics, see\n[Chart and monitor quota metrics](/monitoring/alerts/using-quota-metrics).\n\nTo display metrics with distribution values, use heatmap charts. Heatmaps\nuse color to represent the values in the distribution. You can also display\npercentile lines or outliers. For more information,\nsee [About distribution-valued metrics](/monitoring/charts/charting-distribution-metrics).\n\n### Charts that show the most recent data\n\nTo view the most recent measurement, add a table, a gauge, or a scorecard\nto your dashboard. Tables can display multiple time series, and they let you\nsort and filter rows. In contrast, gauges and scorecards are indicators that\ndisplay a single time series as compared to a color-coded threshold. For\nexample, a red gauge indicates that the most recent measurement is in a\ndanger range.\n\nThe following screenshot is an example of a gauge:\n\nAvoid dashboard performance issues\n----------------------------------\n\nThe performance of a dashboard is sensitive to the number of charts it\ndisplays, and to the number of time series each chart displays.\nFor example, when a chart displays many time series,\nit might take a long time to load or to refresh.\nThe number of time series depends, in part,\non the structure of the metric type and monitored-resource type associated\nwith the time series. Each of these types has several labels;\nthe [Metrics list](/monitoring/api/metrics) and [Monitored resource list](/monitoring/api/resources)\ninclude the labels for each metric and monitored-resource type.\n\nThere is a single time series for each unique combination of values\nfor the set of labels. The number of possible combinations is\ncalled the *cardinality* .\nFor more information about labels, values, and cardinality, see\n[Cardinality](/monitoring/api/v3/metric-model#cardinality).\n\nIf you encounter performance issues when opening a dashboard or when\ndisplaying metric data, you can\noften mitigate the issues by using one of the techniques:\n\n- Remove unnecessary information by [filtering](/monitoring/charts/selecting-aggregating-metrics#filter-option).\n- Combine related information together by [grouping time series](/monitoring/charts/selecting-aggregating-metrics#groupby-option).\n- Focus on unusual data by sorting the time series that match a query, and then limiting the number of time series that are charted. For more information, see [Show outliers](/monitoring/charts/working-with-charts#using-outlier-mode).\n- Reduce the number of labels or the range of values possible for a label for your user-defined metrics.\n- Remove charts or other widgets from dashboards.\n- Prioritize loading of metric data by [grouping dashboard widgets](/monitoring/dashboards/text-and-grouping).\n\nQuotas and limits\n-----------------\n\nFor information about dashboard-specific quotas and limits,\nsee [Limits for charts](/monitoring/quotas#charting_limits).\n\nWhat's next\n-----------\n\n- Create dashboards:\n\n - [Create and manage dashboards](/monitoring/charts/dashboards)\n - [Create and manage dashboards by API](/monitoring/dashboards/api-dashboard)\n - [Import Grafana dashboards](/monitoring/dashboards/import-grafana-dashboards)\n- Add widgets to your dashboards:\n\n - [Add charts, tables, and indicators](/monitoring/charts)\n - [Display incidents and charts for alerting policies](/monitoring/dashboards/alerts-and-incidents)\n - [Display logs and errors](/monitoring/charts/view-logs)\n - [Add text and groupings](/monitoring/dashboards/text-and-grouping)\n - [Display service-level objectives for a set of services](/monitoring/dashboards/slos)\n- Configure dashboard properties:\n\n - [Add dashboard filters and variables](/monitoring/dashboards/filter-permanent)\n - [Add or remove labels](/monitoring/charts/dashboards#add-remove-labels)\n - [Show events on a dashboard](/monitoring/dashboards/show-events)"]]
