Ottimizzare i cluster con provisioning insufficiente
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Questa pagina descrive come ottimizzare le prestazioni dei cluster AlloyDB per PostgreSQL utilizzando il
consigliere per i cluster con provisioning insufficiente.
Il motore per suggerimenti ti aiuta a rilevare i cluster con un utilizzo elevato di CPU e memoria e fornisce suggerimenti per migliorare la configurazione del cluster.
Come funziona il recommender per i cluster con provisioning insufficiente
Quando viene rilevato un utilizzo elevato di CPU e/o memoria, viene visualizzato un
consiglio per aumentare le dimensioni dell'istanza interessata nel cluster
per ridurre l'utilizzo di CPU o memoria al picco. I consigli vengono generati ogni giorno.
Prima di iniziare
Prima di poter visualizzare consigli e approfondimenti, procedi nel seguente modo:
Per ottenere le autorizzazioni per visualizzare e utilizzare approfondimenti e consigli,
assicurati di disporre dei ruoli Identity and Access Management (IAM) necessari.
Nella scheda Rendimento, fai clic su Istanza principale con provisioning insufficiente.
Viene visualizzato un elenco di cluster a cui si applica il consiglio Istanza principale con underprovisioning.
Interfaccia a riga di comando gcloud
Per elencare i suggerimenti sui cluster con provisioning insufficiente utilizzando gcloud CLI, esegui il comando gcloud recommender recommendations list nel seguente modo:
LOCATION: una regione in cui si trovano i tuoi cluster, ad esempio us-central1.
API
Per elencare i suggerimenti per i cluster con provisioning insufficiente utilizzando l'API Recommendations, chiama il metodo
recommendations.list come segue:
GET https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.alloydb.cluster.PerformanceRecommender/recommendations?filter=recommenderSubtype=INCREASE_PRIMARY_INSTANCE_SIZE
Sostituisci quanto segue:
PROJECT_ID: il tuo ID progetto.
LOCATION: una regione in cui si trovano i tuoi cluster, ad esempio us-central1.
Visualizzare approfondimenti e consigli dettagliati
Puoi visualizzare approfondimenti e consigli dettagliati sui cluster con provisioning insufficiente
che richiedono l'ottimizzazione utilizzando la console Google Cloud ,
gcloud CLI o l'API Recommender.
Console
Nella console Google Cloud , vai alla pagina Cluster.
GET https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/insightTypes/google.alloydb.cluster.PerformanceInsight/insights?filter=insightSubtype=INSIGHT_SUBTYPE
Sostituisci quanto segue:
PROJECT_ID: il tuo ID progetto.
LOCATION: una regione in cui si trovano i tuoi cluster, ad esempio us-central1.
INSIGHT_SUBTYPE: imposta questo parametro su uno dei seguenti valori:
HIGH_INSTANCE_CPU_UTILIZATION: mostra
informazioni sull'utilizzo della CPU
HIGH_INSTANCE_MEMORY_UTILIZATION: visualizza
informazioni sulla memoria
La seguente tabella elenca gli approfondimenti e i suggerimenti che il recommender per i cluster con provisioning insufficiente di AlloyDB per PostgreSQL potrebbe generare per aiutarti a evitare colli di bottiglia dovuti a un elevato utilizzo di CPU e memoria e ridurre al minimo la probabilità di eventi di esaurimento della memoria.
I sottotipi sono visibili nei risultati dell'API e in gcloud.
Approfondimenti
Consigli
In base alle tendenze attuali di utilizzo della CPU, il cluster è contrassegnato come
con utilizzo elevato della CPU.
Sottotipo: HIGH_INSTANCE_CPU_UTILIZATION
Aumenta le dimensioni della CPU o riduci l'utilizzo della CPU.
Sottotipo: INCREASE_PRIMARY_INSTANCE_SIZE
In base alle tendenze attuali di utilizzo della memoria, il cluster è contrassegnato
come cluster con un utilizzo elevato della memoria.
Sottotipo: HIGH_INSTANCE_MEMORY_UTILIZATION
Aumenta le dimensioni della memoria o riduci l'utilizzo della memoria.
Sottotipo: INCREASE_PRIMARY_INSTANCE_SIZE
Applica i consigli utilizzando la console Google Cloud
Valuta attentamente i consigli e procedi nel seguente modo nellaGoogle Cloud console per implementare il consiglio:
Fai clic su Modifica sul cluster.
Nella finestra Modifica istanza primaria, passa a un tipo di macchina con più vCPU e più memoria.
Non è necessario dimensionare correttamente il cluster esattamente come consigliato. Utilizza il tuo
giudizio e ridimensiona in base a come intendi eseguire il provisioning del cluster.
[[["Facile da capire","easyToUnderstand","thumb-up"],["Il problema è stato risolto","solvedMyProblem","thumb-up"],["Altra","otherUp","thumb-up"]],[["Difficile da capire","hardToUnderstand","thumb-down"],["Informazioni o codice di esempio errati","incorrectInformationOrSampleCode","thumb-down"],["Mancano le informazioni o gli esempi di cui ho bisogno","missingTheInformationSamplesINeed","thumb-down"],["Problema di traduzione","translationIssue","thumb-down"],["Altra","otherDown","thumb-down"]],["Ultimo aggiornamento 2025-09-04 UTC."],[[["\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)"]]
