One of the selling points for hybrid cloud is the cost savings that IT teams can achieve when they right-size their...
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private clouds to match average workloads, and then burst into the public cloud to support demand peaks.
But despite the advantages of a cloud bursting architecture, there are challenges. For example, some enterprises struggle with how to best position data files, since copying that data between cloud environments is time-consuming.
The IT industry addresses some of the latency issues associated with cloud bursting in a few ways. For example, the deployment of a private cloud as a single-tenant cluster within a public cloud, or the use of storage as a service to speed data delivery, can help. Still, cloud bursting is a work in progress.
So which applications are the best fit for a cloud bursting architecture? Generally, any application that mostly reads data from storage, such as a content delivery system, will be a good candidate for cloud bursting -- except for applications that require low-latency write operations.
Database applications can also be good candidates for a cloud bursting architecture, though admins usually need to shard the database to optimize performance. Admins can also map big data applications across private and public clouds with big-memory and GPU cloud instances to more effectively resize resources to match load.
While many scientific applications involve simulation, which creates too much node-to-node traffic for a cloud bursting architecture, there are certain use cases for these applications where data streams in large volumes, and, thus, requires preprocessing. If these data streams fluctuate daily, such as those in radio telescope arrays, the load shifts back and forth between applications.
To avoid a lot of data movement, you can bring the applications to the data and place the results of one stage of processing -- preprocessing, in this example -- in a private or public cloud. This allows cloud bursting to take place, even with huge amounts of data.
Remember that cloud storage is much more parallel than traditional storage area networks, so networking will define latency, and appropriate caching will be critical.
If you overcome these networking challenges through the use of storage as a service or other means, then many more applications -- except those with very low-latency requirements -- can become candidates for a cloud bursting architecture.
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