[[["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):2024-12-06。"],[[["\u003cp\u003eDefine performance requirements as granularly as possible for the entire application and each layer of the application stack before starting design and development.\u003c/p\u003e\n"],["\u003cp\u003ePlan application designs from the beginning with performance and scalability in mind, considering factors such as the number of users, data volume, and potential growth.\u003c/p\u003e\n"],["\u003cp\u003eSelect services and features that align with the performance goals of each workload, as there is no one-size-fits-all solution for performance optimization.\u003c/p\u003e\n"],["\u003cp\u003eConsider workload characteristics such as deployment archetype, resource placement, network connectivity, application hosting options, storage strategy, and resource configurations, which can influence performance requirements.\u003c/p\u003e\n"],["\u003cp\u003eRegularly monitor the capacity and usage of quotas to ensure adequate resource availability and identify potential scaling constraints or over-allocation issues.\u003c/p\u003e\n"]]],[],null,["# Plan resource allocation\n\nThis principle in the performance optimization pillar of the\n[Google Cloud Well-Architected Framework](/architecture/framework)\nprovides recommendations to help you plan resources for your workloads in\nGoogle Cloud. It emphasizes the importance of defining granular\nrequirements before you design and develop applications for cloud deployment or\nmigration.\n\nPrinciple overview\n------------------\n\nTo meet your business requirements, it's important that you define the performance\nrequirements for your applications, before design and development. Define these\nrequirements as granularly as possible for the application as a whole and for\neach layer of the application stack. For example, in the storage layer, you\nmust consider the throughput and I/O operations per second (IOPS) that the\napplications need.\n\nFrom the beginning, plan application designs with performance and scalability in\nmind. Consider factors such as the number of users, data volume, and potential\ngrowth over time.\n\nPerformance requirements for each workload vary and depend on the type of\nworkload. Each workload can contain a mix of component systems and services that\nhave unique sets of performance characteristics. For example, a system that's\nresponsible for periodic batch processing of large datasets has different\nperformance demands than an interactive virtual desktop solution.\nYour optimization strategies must address the specific needs of each workload.\n\nSelect services and features that align with the performance goals of each\nworkload. For performance optimization, there's no one-size-fits-all solution. When you\noptimize each workload, the entire system can achieve optimal performance and\nefficiency.\n\nConsider the following workload characteristics that can influence your\nperformance requirements:\n\n- **Deployment archetype** : The [deployment archetype](/architecture/deployment-archetypes) that you select for an application can influence your choice of products and features, which then determine the performance that you can expect from your application.\n- **Resource placement** : When you select a Google Cloud [region](/docs/geography-and-regions) for your application resources, we recommend that you prioritize low latency for end users, adhere to data-locality regulations, and ensure the availability of required Google Cloud products and services.\n- **Network connectivity**: Choose networking services that optimize data access and content delivery. Take advantage of Google Cloud's global network, high-speed backbones, interconnect locations, and caching services.\n- **Application hosting options**: When you select a hosting platform, you must evaluate the performance advantages and disadvantages of each option. For example, consider bare metal, virtual machines, containers, and serverless platforms.\n- **Storage strategy** : Choose an [optimal storage strategy](/architecture/storage-advisor) that's based on your performance requirements.\n- **Resource configurations**: The machine type, IOPS, and throughput can have a significant impact on performance. Additionally, early in the design phase, you must consider appropriate security capabilities and their impact on resources. When you plan security features, be prepared to accommodate the necessary performance trade-offs to avoid any unforeseen effects.\n\nRecommendations\n---------------\n\nTo ensure optimal resource allocation, consider the recommendations in the\nfollowing sections.\n\n### Configure and manage quotas\n\nEnsure that your application uses only the necessary resources, such as memory,\nstorage, and processing power. Over-allocation can lead to unnecessary expenses,\nwhile under-allocation might result in performance degradation.\n\nTo accommodate elastic scaling and to ensure that adequate resources are\navailable, regularly monitor the capacity of your quotas. Additionally, track\nquota usage to identify potential scaling constraints or over-allocation issues,\nand then make informed decisions about resource allocation.\n\n### Educate and promote awareness\n\nInform your users about the performance requirements and provide\n[educational resources](https://www.cloudskillsboost.google/course_templates/734)\nabout effective performance management techniques.\n\nTo evaluate progress and to identify areas for improvement, regularly document the\ntarget performance and the actual performance. Load test your application to find\npotential breakpoints and to understand how you can scale the application.\n\n### Monitor performance metrics\n\nUse\n[Cloud Monitoring](/monitoring/docs/monitoring-overview)\nto analyze trends in performance metrics, to analyze the effects of experiments,\nto define alerts for critical metrics, and to perform retrospective analyses.\n\n[Active Assist](/recommender/docs/whatis-activeassist)\nis a set of tools that can provide insights and recommendations to help optimize\nresource utilization. These recommendations can help you to adjust resource\nallocation and improve performance."]]