GET https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.alloydb.cluster.PerformanceRecommender/recommendations?filter=recommenderSubtype=INCREASE_PRIMARY_INSTANCE_SIZE
替换以下内容：
PROJECT_ID：您的项目 ID。
LOCATION：集群所在的区域，例如 us-central1。
查看数据分析和详细建议
您可以使用 Google Cloud 控制台、gcloud CLI 或 Recommender API 查看有关需要优化的预配不足的集群的分析洞见和详细建议。
GET https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/insightTypes/google.alloydb.cluster.PerformanceInsight/insights?filter=insightSubtype=INSIGHT_SUBTYPE
替换以下内容：
PROJECT_ID：您的项目 ID。
LOCATION：集群所在的区域，例如 us-central1。
INSIGHT_SUBTYPE：将此参数设置为以下其中一项：
HIGH_INSTANCE_CPU_UTILIZATION：显示有关 CPU 用量的数据分析
HIGH_INSTANCE_MEMORY_UTILIZATION：显示有关内存的数据分析
下表列出了 AlloyDB for PostgreSQL 预配不足的集群 Recommender 可能生成的数据分析和建议，以帮助您避免高 CPU 和内存用量造成的瓶颈，并最大限度地降低发生内存不足事件的可能性。gcloud 和 API 结果中显示子类型。
分析洞见
建议
根据当前 CPU 利用率趋势，集群标记为具有高 CPU 使用率。
子类型：HIGH_INSTANCE_CPU_UTILIZATION
增加 CPU 大小或降低 CPU 利用率。
子类型：INCREASE_PRIMARY_INSTANCE_SIZE
[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC)：2025-08-25。"],[[["\u003cp\u003eThe underprovisioned cluster recommender identifies clusters with high CPU and/or memory utilization and suggests optimizations to enhance performance.\u003c/p\u003e\n"],["\u003cp\u003eRecommendations to increase the instance size of underprovisioned clusters are generated daily and can be viewed after enabling the Recommender API and having the correct IAM roles.\u003c/p\u003e\n"],["\u003cp\u003eYou can list and apply underprovisioned cluster recommendations using the Google Cloud console, gcloud CLI, or the Recommender API.\u003c/p\u003e\n"],["\u003cp\u003eInsights on high CPU and memory utilization can be viewed via the console, CLI, or API, detailing the type of usage issue, such as \u003ccode\u003eHIGH_INSTANCE_CPU_UTILIZATION\u003c/code\u003e or \u003ccode\u003eHIGH_INSTANCE_MEMORY_UTILIZATION\u003c/code\u003e.\u003c/p\u003e\n"],["\u003cp\u003eImplementing the recommended instance size increase involves editing the cluster settings in the console, updating the primary instance to a machine type with more vCPUs and memory.\u003c/p\u003e\n"]]],[],null,["# Optimize underprovisioned clusters\n\nThis page describes how to optimize the performance of your AlloyDB for PostgreSQL clusters by using the\nunderprovisioned cluster [recommender](/recommender/docs/overview).\nThe recommender helps you detect clusters that have high CPU and memory\nutilization and provides recommendations for improving your cluster configuration.\n\nHow the underprovisioned cluster recommender works\n--------------------------------------------------\n\nWhen there is high CPU and or memory utilization detected, you see a\nrecommendation to increase the size of the affected instance in the cluster\nto reduce CPU or memory utilization at peak. Recommendations are generated daily.\n\nBefore you begin\n----------------\n\nBefore you can view recommendations and insights, do the following:\n\n- Ensure that you [enable the Recommender API](/recommender/docs/enabling).\n\n- To get the permissions to view and work with insights and recommendations,\n ensure that you have the required [Identity and Access Management (IAM) roles](/iam/docs/understanding-roles#cloud-alloydb-roles).\n\n \u003cbr /\u003e\n\n See [Grant access to other users](/alloydb/docs/user-grant-access) for more information.\n\nList underprovisioned cluster recommendations\n---------------------------------------------\n\nYou can list recommendations for underprovisioned clusters\nusing the Google Cloud console, `gcloud CLI`, or the Recommender API. \n\n### Console\n\nTo list recommendations about underprovisioned clusters, complete the following steps:\n\n1. In the Google Cloud console, go to the **Clusters** page.\n\n [Go to Clusters](https://console.cloud.google.com/alloydb/clusters)\n\n For more information, see\n [Find recommendations with Recommendation Hub](/recommender/docs/recommendation-hub/identify-configuration-problems).\n2. In the **Performance** card, click **Underprovisioned primary instance**.\n\n A list of clusters to which the **Underprovisioned primary instance** recommendation applies is displayed.\n\n### gcloud CLI\n\nTo list recommendations about underprovisioned clusters using gcloud CLI, run the [`gcloud recommender recommendations list`](/sdk/gcloud/reference/recommender/recommendations/list) command as follows: \n\n```\ngcloud recommender recommendations list \\\n--project=PROJECT_ID \\\n--location=LOCATION \\\n--recommender=google.alloydb.cluster.PerformanceRecommender \\\n--filter=recommenderSubtype=INCREASE_PRIMARY_INSTANCE_SIZE\n```\n\nReplace the following:\n\n- \u003cvar translate=\"no\"\u003ePROJECT_ID\u003c/var\u003e: Your project ID.\n- \u003cvar translate=\"no\"\u003eLOCATION\u003c/var\u003e: A region where your clusters are located, such as `us-central1`.\n\n### API\n\nTo list recommendations for underprovisioned clusters using the [Recommendations API](/recommender/docs/using-api), call the\n[`recommendations.list`](/recommender/docs/reference/rest/v1/projects.locations.recommenders.recommendations/list)\nmethod as follows: \n\n```\nGET https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.alloydb.cluster.PerformanceRecommender/recommendations?filter=recommenderSubtype=INCREASE_PRIMARY_INSTANCE_SIZE\n```\n\nReplace the following:\n\n- \u003cvar translate=\"no\"\u003ePROJECT_ID\u003c/var\u003e: Your project ID.\n- \u003cvar translate=\"no\"\u003eLOCATION\u003c/var\u003e: A region where your clusters are located, such as `us-central1`.\n\nView insights and detailed recommendations\n------------------------------------------\n\nYou can view insights and detailed recommendations about underprovisioned clusters\nthat require optimization using the Google Cloud console,\n`gcloud CLI`, or the Recommender API. \n\n### Console\n\n1. In the Google Cloud console, go to the **Clusters** page.\n\n [Go to Clusters](https://console.cloud.google.com/alloydb/clusters)\n2. Click the recommendation button for a cluster in the **Issues** column.\n\n The recommendation panel appears, which contains insights and detailed recommendations about an underprovisioned cluster.\n\n### gcloud CLI\n\nRun the [`gcloud recommender insights list`](/sdk/gcloud/reference/recommender/insights/list) command as follows: \n\n```\ngcloud recommender insights list \\\n--project=PROJECT_ID \\\n--location=LOCATION \\\n--insight-type=google.alloydb.cluster.PerformanceInsight\n--filter=insightSubtype=INSIGHT_SUBTYPE\n```\n\nReplace the following:\n\n- \u003cvar translate=\"no\"\u003ePROJECT_ID\u003c/var\u003e: Your project ID.\n- \u003cvar translate=\"no\"\u003eLOCATION\u003c/var\u003e : A region where your clusters are located, such as `us-central1`.\n- \u003cvar translate=\"no\"\u003eINSIGHT_SUBTYPE\u003c/var\u003e: set this parameter to one of the following:\n - `HIGH_INSTANCE_CPU_UTILIZATION`: display insights about CPU usage\n - `HIGH_INSTANCE_MEMORY_UTILIZATION`: display insights about memory\n\n### API\n\nCall the [`insights.list`](/recommender/docs/reference/rest/v1/projects.locations.insightTypes.insights/list) method as follows: \n\n```\nGET https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/insightTypes/google.alloydb.cluster.PerformanceInsight/insights?filter=insightSubtype=INSIGHT_SUBTYPE\n```\n\nReplace the following:\n\n- \u003cvar translate=\"no\"\u003ePROJECT_ID\u003c/var\u003e: Your project ID.\n- \u003cvar translate=\"no\"\u003eLOCATION\u003c/var\u003e: A region where your clusters are located, for example, `us-central1`.\n- \u003cvar translate=\"no\"\u003eINSIGHT_SUBTYPE\u003c/var\u003e: set this parameter to one of the following:\n - `HIGH_INSTANCE_CPU_UTILIZATION`: display insights about CPU usage\n - `HIGH_INSTANCE_MEMORY_UTILIZATION`: display insights about memory\n\nThe following table lists the insights and recommendations that the AlloyDB for PostgreSQL\nunderprovisioned cluster recommender might generate to help you avoid bottlenecks from high CPU and memory\nusage and minimize the likelihood of out-of-memory events.\nThe subtypes are visible in the `gcloud` and API results.\n\nApply recommendations using the Google Cloud console\n----------------------------------------------------\n\nEvaluate the recommendations carefully and do the following in the\nGoogle Cloud console to implement the recommendation:\n\n1. Click **Edit** on your cluster.\n2. In the **Edit primary instance** window, switch to a machine type with more vCPUs and more memory.\n You don't need to rightsize the cluster exactly as recommended. Use your\n judgement and resize based on how you intend to provision the cluster.\n\n3. Click **Update instance**.\n\n | **Note:** You must carefully evaluate before you update the cluster. Applying recommendations might impact your pricing.\n\nWhat's next\n-----------\n\n- [Google Cloud recommenders](/recommender/docs/recommenders)"]]
