GET https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.alloydb.cluster.PerformanceRecommender/recommendations?filter=recommenderSubtype=INCREASE_PRIMARY_INSTANCE_SIZE
更改下列內容：
PROJECT_ID：您的專案 ID。
LOCATION：叢集所在的區域，例如 us-central1。
查看洞察資料和詳細建議
如要查看資源不足的叢集相關洞察資料和詳細建議，請使用 Google Cloud 控制台、gcloud CLI 或 Recommender API。
GET https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/insightTypes/google.alloydb.cluster.PerformanceInsight/insights?filter=insightSubtype=INSIGHT_SUBTYPE
更改下列內容：
PROJECT_ID：您的專案 ID。
LOCATION：叢集所在的區域，例如 us-central1。
INSIGHT_SUBTYPE：將此參數設為下列其中一個值：
HIGH_INSTANCE_CPU_UTILIZATION：顯示 CPU 使用情況的深入分析
HIGH_INSTANCE_MEMORY_UTILIZATION：顯示記憶體深入分析資訊
下表列出 AlloyDB for PostgreSQL 資源不足叢集建議工具可能會產生的洞察資料和建議，協助您避免 CPU 和記憶體用量過高造成瓶頸，並盡量減少記憶體不足事件。子類型會顯示在 gcloud 和 API 結果中。
深入分析
建議
根據目前的 CPU 使用率趨勢，系統會將叢集標示為 CPU 使用率偏高。
子類型：HIGH_INSTANCE_CPU_UTILIZATION
增加 CPU 大小或降低 CPU 使用率。
子類型：INCREASE_PRIMARY_INSTANCE_SIZE
[[["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：2025-09-04 (世界標準時間)。"],[[["\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)"]]
