This principle in the performance optimization pillar of theGoogle Cloud Well-Architected Framework provides recommendations to help you plan resources for your workloads inGoogle Cloud. It emphasizes the importance of defining granularrequirements before you design and develop applications for cloud deployment ormigration.

Principle overview

To meet your business requirements, it's important that you define the performancerequirements for your applications, before design and development. Define theserequirements as granularly as possible for the application as a whole and foreach layer of the application stack. For example, in the storage layer, youmust consider the throughput and I/O operations per second (IOPS) that theapplications need.

From the beginning, plan application designs with performance and scalability inmind. Consider factors such as the number of users, data volume, and potentialgrowth over time.

Performance requirements for each workload vary and depend on the type ofworkload. Each workload can contain a mix of component systems and services thathave unique sets of performance characteristics. For example, a system that'sresponsible for periodic batch processing of large datasets has differentperformance demands than an interactive virtual desktop solution.Your optimization strategies must address the specific needs of each workload.

Select services and features that align with the performance goals of eachworkload. For performance optimization, there's no one-size-fits-all solution. When youoptimize each workload, the entire system can achieve optimal performance andefficiency.

Consider the following workload characteristics that can influence yourperformance requirements:

• Deployment archetype: Thedeployment archetype 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.
• Resource placement: When you select a Google Cloudregion for your application resources, we recommend that you prioritize low latency for endusers, adhere to data-locality regulations, and ensure the availability ofrequired Google Cloud products and services.
• Network connectivity: Choose networking services that optimize dataaccess and content delivery. Take advantage of Google Cloud's globalnetwork, high-speed backbones, interconnect locations, and caching services.
• Application hosting options: When you select a hosting platform, youmust evaluate the performance advantages and disadvantages of each option.For example, consider bare metal, virtual machines, containers, and serverlessplatforms.
• Storage strategy: Choose anoptimal storage strategy that's based on your performance requirements.
• Resource configurations: The machine type, IOPS, and throughput canhave a significant impact on performance. Additionally, early in the designphase, you must consider appropriate security capabilities and their impact onresources. When you plan security features, be prepared to accommodate thenecessary performance trade-offs to avoid any unforeseen effects.

Recommendations

To ensure optimal resource allocation, consider the recommendations in thefollowing sections.

Configure and manage quotas

Ensure that your application uses only the necessary resources, such as memory,storage, and processing power. Over-allocation can lead to unnecessary expenses,while under-allocation might result in performance degradation.

To accommodate elastic scaling and to ensure that adequate resources areavailable, regularly monitor the capacity of your quotas. Additionally, trackquota usage to identify potential scaling constraints or over-allocation issues,and then make informed decisions about resource allocation.

Educate and promote awareness

Inform your users about the performance requirements and provideeducational resources about effective performance management techniques.

To evaluate progress and to identify areas for improvement, regularly document thetarget performance and the actual performance. Load test your application to findpotential breakpoints and to understand how you can scale the application.

Monitor performance metrics

UseCloud Monitoring to analyze trends in performance metrics, to analyze the effects of experiments,to define alerts for critical metrics, and to perform retrospective analyses.

Active Assist is a set of tools that can provide insights and recommendations to help optimizeresource utilization. These recommendations can help you to adjust resourceallocation and improve performance.