측정항목 탐색기나 Monitoring API를 사용하여 측정항목 데이터를 읽을 때 집계를 사용하여 시계열 데이터를 요약할 수 있습니다. 일반적으로 집계는 각 시계열 데이터가 동일한 시간 경계에 있는 정렬 단계부터 시작합니다. 그런 다음 평균, 합계, 최솟값, 최댓값 등의 연산을 사용하여 여러 시계열의 데이터 포인트를 조합하면 새로운 시계열이 생성됩니다.
Cloud Monitoring에는 기본 제공되는 시스템 측정항목이 많이 있지만 커스텀 측정항목을 만들 수도 있습니다. 커스텀 측정항목과 데이터가 포함된 하나 이상의 시계열을 설명하는 측정항목 설명을 만들어야 합니다.
차트 및 알림에서 커스텀 측정항목 데이터를 사용할 수 있습니다. 로그 데이터를 기반으로 커스텀 측정항목을 만들 수도 있습니다. 자세한 내용은 다음 페이지를 참조하세요.
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2025-07-29(UTC)"],[],[],null,["# Learn more about...\n\n| **Beta**\n|\n|\n| This product or feature is subject to the \"Pre-GA Offerings Terms\" in the General Service Terms section\n| of the [Service Specific Terms](/terms/service-terms#1).\n|\n| Pre-GA products and features are available \"as is\" and might have limited support.\n|\n| For more information, see the\n| [launch stage descriptions](/products#product-launch-stages).\n\nAggregation\n-----------\n\nWhen you read metric data using the Metrics Explorer or the Monitoring API,\nyou can use *aggregation* to summarize the time series data. Aggregation\ntypically starts with an alignment step in which each time series' data is\nplaced on the same time boundaries. Next, a new time series is created by\ncombining the data points from multiple time series, using operations like\naverage, sum, minimum, maximum, and so forth.\n\nFor more information about aggregation, see the\n[`projects.timeSeries.list`](/monitoring/api/ref_v3/rest/v3/projects.timeSeries/list)\nAPI method.\n\nCustom metrics\n--------------\n\nCloud Monitoring has a large number of built-in system metrics, but you can\nalso create custom metrics. You must create a metric descriptor that\ndescribes your custom metric and one or more time series that contain its data.\nYou can use your custom metric data in charts and alerts. You can also create\ncustom metrics based on logs data. For more information, see the following\npages:\n\n- [Metrics, Time Series, and Resources](/monitoring/api/v3/metrics) provides an overview.\n- [Using Custom Metrics](/monitoring/custom-metrics) shows you how to create, write, and read custom metrics.\n- [Logs-based Metrics](/logging/docs/view/logs_based_metrics) describes how to create custom metrics from logs.\n- [Monitoring API](/monitoring/api/ref_v3/rest), is the API used to for custom metrics. See the `projects.metricDescriptors` and `projects.timeSeries` collections.\n\nFiltering\n---------\n\nCloud Logging and Cloud Monitoring provide different kinds of filters\nthat let you select\nsets of items. Filters are strings that contain combinations of comparisons\nappropriate to their kind. For example:\n\n- [Logging filters](/logging/docs/view/advanced_filters) let you select particular log entries based on log names, where the logs came from, their payload content, and so on.\n- [Monitoring filters](/monitoring/api/v3/filters) let you select particular metric descriptors, resource groups, and time series data.\n- [Trace filters](/trace/docs/trace-filters) let you select traces based on span names, latency, and label values.\n\nMetrics scope\n-------------\n\nMonitoring organizes itself around metrics scopes that\nlet you view and monitor metrics for one or more Google Cloud projects.\nFor more information about metrics scopes, see\n[Configuring your Google Cloud project for Cloud Monitoring](/monitoring/settings)."]]
