Active Assist 是指在Google Cloud 中用來產生最佳化建議和洞察資料的工具組合，可協助您將 Google Cloud 專案調整至最佳狀態。詳情請參閱「什麼是 Active Assist」。
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透過 Google Cloud Observability 工具和第三方解決方案提供的警示和資訊主頁，主動找出並解決問題。
查看 Google Cloud 可觀測性指標、記錄和追蹤記錄，深入瞭解資源使用率、效能特徵和資源的整體健康狀態。監控與系統健康狀態指標一致的重要指標，例如 CPU 使用率、記憶體用量、網路流量、磁碟 I/O 和應用程式回應時間。您也應考慮商家專屬指標。追蹤這些指標，您就能找出潛在瓶頸、效能問題和資源限制。此外，您也可以設定快訊，主動通知相關團隊潛在問題或異常狀況。
[[["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：2025-09-09 (世界標準時間)。"],[],[],null,["# Optimize your cloud resources\n\nBefore your peak capacity event occurs, manage and optimize the resources that\nare used by your Google Cloud workloads. This involves right-sizing resources\nbased on actual usage and demand, using autoscaling for dynamic resource\nallocation, and reviewing architecture and security recommendations. Both\n[Cloud Monitoring](/monitoring/docs/monitoring-overview) and\n[Recommender](/recommender) (Active Assist) can help you to\nidentify opportunities to optimize your cloud resources. By using these tools,\nyou can gain insights into resource usage and make informed decisions prior to\nyour event.\n\nReview Google Cloud best practices\n----------------------------------\n\nMany peak capacity event issues can be avoided by following the recommended best\npractices for the Google Cloud product that you are using. The following\nare examples of some best practice guides:\n\nReview scalability\n------------------\n\nAutoscaling can ensure that your cloud-based applications have the resources\nthat they need to handle varying workloads, while avoiding over provisioning and\nunnecessary costs. Google Cloud offers several product-specific\nautoscaling options, including the following:\n\n- [Compute Engine managed instance groups (MIGs)](/compute/docs/instance-groups#managed_instance_groups) are groups of VMs that are managed and scaled as a single entity. With MIGs, you can define autoscaling policies that specify the minimum and maximum number of VMs to maintain in the group, and the conditions that trigger autoscaling.\n- [Google Kubernetes Engine (GKE) autoscaling](/kubernetes-engine/docs/concepts/cluster-autoscaler) dynamically adjusts your cluster resources to match your application's needs. It offers tools that can optimize resource utilization, ensure application performance, and simplify cluster management.\n- [Cloud Run](/run/docs/about-instance-autoscaling) offers built-in autoscaling, which automatically adjusts the number of instances based on the incoming traffic.\n\nBefore your event, we recommend that you scale up manually. Although you might\nhave autoscaling configured, due to the velocity of event traffic, autoscaling\nmight not be able to catch up with demand. So pre-warm resources ahead of\ntime, including the following:\n\n- Virtual machines\n- Caches if you want to pre-load\n- Serverless components to prevent cold starts\n\n| **Note:** Google [Cloud Load Balancing](/load-balancing) doesn't require pre-warming. However, other cloud providers might require load balancer pre-warming. Make sure to check with those providers.\n\nReview Active Assist recommendations\n------------------------------------\n\nActive Assist refers to the portfolio of tools used in\nGoogle Cloud to generate recommendations and insights to help you optimize\nyour Google Cloud projects. For more information, see\n[What is Active Assist](/recommender/docs/whatis-activeassist).\n\nReview your product versions\n----------------------------\n\nEnsure that all your cloud products and services are up-to-date with the latest\nstable version.\n\nReview alerts and dashboards\n----------------------------\n\nProactively identify and address issues by evaluating the alerts and dashboards\nprovided to you through Google Cloud Observability tools and third-party solutions.\n\nCheck your [Google Cloud Observability metrics, logs, and traces](/stackdriver/docs) to\ngain insights into resource utilization, performance characteristics, and the\noverall health of your resources. Monitor important metrics that align with\nsystem health indicators such as CPU utilization, memory usage, network traffic,\ndisk I/O, and application response times. You should also consider\nbusiness-specific metrics. By tracking these metrics, you can identify potential\nbottlenecks, performance issues, and resource constraints. Additionally, you can\nset up alerts to notify relevant teams proactively about potential issues or\nanomalies.\n\nFor alerts, focus on critical metrics, set appropriate thresholds to minimize\nalert fatigue, and ensure timely responses to significant issues. This targeted\napproach lets you proactively maintain workload reliability. For more\ninformation, see the [Alerting overview](/monitoring/alerts).\n\nWhat's next\n-----------\n\n- [Conduct load testing](/support/docs/peak-events/conduct-load-testing)"]]
