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2025-01-27 Update From: SLTechnology News&Howtos shulou NAV: SLTechnology News&Howtos > Servers >
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Today, cloud computing has become a basic IT infrastructure strategy for almost all enterprises. Last year, Gartner predicted that demand for infrastructure as a service (IaaS) would increase by 36.8%. A cloud survey conducted by another consulting firm in 2018 showed that 95% of enterprises had a cloud strategy, and 51% of them adopted a hybrid cloud strategy.
However, although the cloud is ubiquitous and HPC has been in the cloud for more than a decade-Univa commissioned the first HPC cluster on AWS in 2008-enterprises have been reluctant to put HPC workloads in cloud computing. Concerns about data security and lack of technology have outweighed the benefits of reducing administrative costs and avoiding hardware ownership.
Only in the past year have we really reached a tipping point. According to a customer survey, corporate interest in and use of HPC cloud increased tenfold in 2017. With fewer challenges related to cloud computing, these enterprises see economic and commercial opportunities to adopt a hybrid cloud strategy. In the public cloud, they can use dedicated hardware like Nvidia GPU without affecting CAPEX, or they can extend computationally heavy workloads, such as the TensorFlow machine learning model that usually affects other clusters. And in a hybrid model, they can achieve these goals without sacrificing existing investment.
Hybrid cloud has become an important competitive strategy for HPC. But why start?
Hybrid cloud strategy
In the HPC space, most companies are starting to use the cloud to expand their existing resources. This maximizes current investment and provides a way to simplify the new cloud infrastructure model. However, it also has the potential to exacerbate existing complexity. If enterprises do not have a good understanding of how their existing infrastructure is used, it is impossible to know whether the increase in cloud services will give them the results they really need. Therefore, before introducing new cloud resources, they should consolidate silo-style closed workloads as much as possible and ensure that they have the right tools to see usage patterns and optimize resources.
In this way, enterprises can introduce public cloud resources into their existing workflows. Most companies start this transition by moving in only a small number of workloads and then adding them in an orderly manner. Starting with the following strategy and fine-tuning it as you increase your public cloud investment may help you achieve a seamless transition:
Policy automation is critical for hybrid cloud environments and HPC. Companies with HPC workloads are probably aware of the benefits of having the right policy management tools and should consider developing strategies that will help them maximize their use of hybrid cloud resources. They can improve throughput by developing policies that automatically determine which workloads are running locally rather than in the cloud, or they can reliably monitor, respond, and make decisions based on workload metrics and history. For example, you can set a policy to assign a cloud instance to a task that has been waiting for resources for too long, or automatically terminate unused cloud instances.
Cloud explosion (an application deployment model that runs in a private cloud or data center and suddenly enters the public cloud when the demand for computing power reaches its peak.) It can be used to adjust a company's capacity to meet demand, greatly speed up computing, and constantly require HPC workloads from the impact on other clusters. Organizations should be careful to bind cloud burst capabilities to the workload management layer, not the application or infrastructure layer. This allows HPC cloud management software to decide when to provide server instances, phase data, and demolition resources based on the company's broader infrastructure needs. When used effectively, cloud outbursts provide flexibility in hardware budget decisions while helping organizations move forward at a faster pace.
End users should be able to interact with the cloud infrastructure in ways they already know and trust. If an organization suddenly changes their pipelining and submission methods when adopting cloud computing, they will inevitably experience errors and delays. Instead, they should keep existing workflows and associated schedulers, whether they are simple steps, such as "qsub" submitting a single task-- or a process as complex as environment settings, observing work status, data movement, or a sequence from task to task.
Finally, bring your own image. Using the same machine image helps to migrate applications between local and cloud-based nodes. Companies should use their own cloud provisioning software to customize the image instead of using each vendor-specific VM image.
HPC embraces hybrid cloud
The hybrid cloud is a victory for public cloud service providers and HPC users, and we are just at the beginning of this big change. HPC tends to have millions of servers and billions of computing time each year. As companies move these workloads to the cloud, they will affect the quality of public cloud services and the state of the IaaS market. Security, GPU, and machine learning services provided by public cloud providers will continue to improve, attract more and more enterprise users, and consolidate the HPC architecture in the hybrid cloud.
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