Data managers have decided that the 云 is how IT is done. 在一个 高德纳最新预测这家分析公司预测，全球公共云服务提供商将创造260美元的收入.2 billion in sales this year, an 18.5-percent annual increase. By 2020, that figure is expected to jump to $411.40亿年. And that’s just for public 云.
What’s your 云 crowd? 你有很多选择. 有多种云开发模式:在PaaS层上的下一代云原生应用和在基础设施即服务上运行的传统应用是两大模式. But 云 is an operating model, not where things run – and they can run in lots of places: public 云, 私有云, a combination of both known as hybrid 云, 直连公共, 共存, hosted 私有云 and more. 大多数企业云环境是复杂的，尽管使用云来简化IT. There’s more complexity in selecting the right 私有云 platform. 你自己的活动地板? 主机托管? 专用主机? It’s a fluid situation. 你现在所处的位置和你对自己未来几年的期望可能会有很大的不同.
IT looks hybrid and multi-云
最常见的云体验是在云和遗留的混合环境中的IaaS. 试用公共云通常从一个小的试点项目开始，然后在kpi达到并且试点成功后迁移更多的工作负载. Even once you’re a public 云 customer, you might have reasons to keep some workloads on your 私有云, particularly those with low latency and high security requirements, or compliance requirements (e.g., Sarbannes-Oxley or other federal regulations). Data migration remains a constant as well. 例如, as workloads on the public 云 grow more massive, 应用程序所有者经常将应用程序(或部分应用程序)带回本地，以降低成本并利用规模经济.
结果, balancing on- versus off-prem 云 performance, compliance and security, for the best TCO has revealed the best response may be: 所有的选择. This was confirmed in a survey performed last year by F5 Networks 五分之四的基础设施专家正在采用多云环境.
Hybrid 云 reflects the reality of managing a portfolio that can include new, 云-native applications, 公共云服务, as well as traditional workloads managed at the Virtual Machine level. Hybrid允许您将计算和存储放在最适合的位置，并在情况发生变化时迁移工作负载. 它还允许您继续从传统It基础设施投资中获得价值，同时还可以充分利用现代云平台和服务.
Challenge: 云 Sprawl
\nWhen organizations lack control of or visibility into their IT resources, 结果可能是在太多不同的云服务器上有太多的云实例, even too many vendor relationships. 它不仅成本高昂，而且会损害数据安全性、完整性和并发性. 云 sprawl is more of a problem for clients who pay for it than to service providers; even so, 一些服务提供商提供服务器标签，而其他服务提供商提供自动扩展/缩小规模来帮助处理扩展. All providers allow you to set budget and performance thresholds.
\n另一个云管理改进是按工作负载进行管理，而不是按工作负载运行的位置进行管理. Optimizing IT 云 infrastructure means understanding your workloads, where 微米 has deep expertise. 注意那些可能有过度分配资源的工作负载，或者可能有在非持久性功能上全天候运行的进程. Delete or reduce resources for idle or forgotten workloads.
\nChallenge: Resource Provisioning
\nThough archiving data to the 云 was an early storage trend, 现在，IT经理们正在通过提供和扩展基于云的共享资源来满足高峰需求，从而取代过度供应. They are also consolidating workloads that exist across multiple environments. To manage this efficiently and without incurring downtime, 好的云计算原则可以使企业在公共云和内部部署环境之间动态调整工作负载. Automating the optimization of data location is a good job for AI-driven 云-based systems platformsIDC表示. 许多云服务提供商也在为客户构建机器学习和人工智能平台，以便将其集成到应用程序开发管道中. 微米 is innovating to 改进数据科学 出于这些目的.
\nChallenge: Application Performance
\nMoving applications to the 云 helps eliminate traditional, 定制的, 过度供给的, 孤立的基础设施. 但是，云承诺的大规模水平扩展可能不会使那些没有有效扩展和利用快速弹性的遗留应用程序受益. 应用程序所有者和IT经理已经学会了根据资源需求和功能对应用程序进行分类, 并且必须考虑什么时候重写应用程序以利用云功能是有意义的. Creating and recreating dynamic pools of compute, storage and networking (或结构)在共享平台上按需处理多个独立工作负载是虚拟化的核心. Tunable storage can also enhance performance, endurance and lower latency on 服务器 hosting 云 workloads.
\n"}}' id="text-5cc262b91f">Hybrid 云 brings challenges
While hybrid 云 is the prevailing choice, it does bring some complications. 事实上, “将混合云视为一系列挑战而不是特定的部署模型更有用,” Forrester’s 云 expert Dave Bartoletti 在最近的一次采访中.
One challenge that 微米 has heard from customers and others in the marketplace concerns modernizing on-premises systems; specifically, how to achieve 云-like agility, low costs and efficiency. We draw on our deep relationships with many of the top 云 service, SaaS和XaaS(“一切即服务”)公司都希望与云计算的发展保持同步. 我们能够利用我们的快速存储和持久内存经验来构建高性能的公共和私有云环境，以帮助客户“云化”他们的本地云, such as moving from storage arrays to platform-attached flash with high-capacity solid state drives. 美光的下一代云基础设施和我们的合作伙伴生态系统也有助于为追求统一云交付平台的组织提供基础.
Perhaps most importantly, 下一代和更注重传统的IaaS架构都依赖于由软件管理的直接连接的存储. 云原生平台通常通过内置在数据服务层中的功能提供数据保护和扩展, 软件定义存储(SDS)是IaaS的最佳选择.
以下是沙巴体育安卓版下载混合云复杂性如何推动IT管理创新的一些其他想法, monitoring and provisioning.
Challenge: 云 Sprawl
When organizations lack control of or visibility into their IT resources, 结果可能是在太多不同的云服务器上有太多的云实例, even too many vendor relationships. 它不仅成本高昂，而且会损害数据安全性、完整性和并发性. 云 sprawl is more of a problem for clients who pay for it than to service providers; even so, 一些服务提供商提供服务器标签，而其他服务提供商提供自动扩展/缩小规模来帮助处理扩展. All providers allow you to set budget and performance thresholds.
另一个云管理改进是按工作负载进行管理，而不是按工作负载运行的位置进行管理. Optimizing IT 云 infrastructure means understanding your workloads, where 微米 has deep expertise. 注意那些可能有过度分配资源的工作负载，或者可能有在非持久性功能上全天候运行的进程. Delete or reduce resources for idle or forgotten workloads.
Challenge: Resource Provisioning
Though archiving data to the 云 was an early storage trend, 现在，IT经理们正在通过提供和扩展基于云的共享资源来满足高峰需求，从而取代过度供应. They are also consolidating workloads that exist across multiple environments. To manage this efficiently and without incurring downtime, 好的云计算原则可以使企业在公共云和内部部署环境之间动态调整工作负载. Automating the optimization of data location is a good job for AI-driven 云-based systems platformsIDC表示. 许多云服务提供商也在为客户构建机器学习和人工智能平台，以便将其集成到应用程序开发管道中. 微米 is innovating to 改进数据科学 出于这些目的.
Challenge: Application Performance
Moving applications to the 云 helps eliminate traditional, 定制的, 过度供给的, 孤立的基础设施. 但是，云承诺的大规模水平扩展可能不会使那些没有有效扩展和利用快速弹性的遗留应用程序受益. 应用程序所有者和IT经理已经学会了根据资源需求和功能对应用程序进行分类, 并且必须考虑什么时候重写应用程序以利用云功能是有意义的. Creating and recreating dynamic pools of compute, storage and networking (或结构)在共享平台上按需处理多个独立工作负载是虚拟化的核心. Tunable storage can also enhance performance, endurance and lower latency on 服务器 hosting 云 workloads.
微米 storage and memory
Whichever group you see yourself in, 将您的应用程序和工作负载定位为最适合云计算的能力将帮助您保持飞速发展. As a global leader in 固态硬盘s, 美光为托管云工作负载的服务器带来了广泛的存储功能. 微米’s fast flash storage and persistent memory, proven at some of the world’s largest and most innovative 云 companies, help boost workload and application performance. 阅读与云计算领导者阿里巴巴在云计算和数据中心基础设施方面的合作如何为我们赢得了它 Delivery Partner of the Year award.